JP6301730B2 - Electric vehicle operation management device and operation planning method - Google Patents

Description

  Embodiments described herein relate generally to an operation management device and an operation plan planning method for an electric vehicle.

  In recent years, commercial vehicles such as route buses and bus rapid transit systems (BRT) operating according to the schedule have been increasingly used as electric vehicles. When planning such an electric vehicle operation plan, it is necessary to consider many dynamic factors. For example, in the case of an EV bus, the number of passengers and power consumption change due to time and external factors, delay due to traffic jams, and energy available at a charging base changes due to the issue of DR (Demand Response). If these electric factors cause the electric vehicle to be unable to be charged at the charging base as planned, the possibility that the electric vehicle will run out of electricity increases.

  In addition, since a large amount of electric power is required for charging an electric vehicle, a planned peak shift to suppress the charging load of the charging facility, and supply power and supply supplied from the power supply side (system and charging facility) It is also necessary to observe restrictions such as the amount of power.

  However, it has been difficult to create an operation plan in consideration of many such dynamic factors. For example, most of the conventional operation management methods that take into account electric shortage of electric vehicles take into account that each electric vehicle does not become electric shortage while traveling alone.

  On the other hand, the operation management method of the electric vehicle considering the charging load of the charging facility is only for the case where each electric vehicle to be managed is connected to the charger, and for the electric vehicle in operation, Not considered. As described above, no operation management method has been proposed for the purpose of realizing the shortage of electric vehicles and the suppression of the charging load of the charging facility.

JP 2011-244563 A JP 2011-120327 A

  Provided is an operation management device and an operation plan planning method capable of planning an operation plan in which a plurality of electric vehicles operate without causing electric shortage.

  The operation management apparatus according to the embodiment includes vehicle information means, charging facility information means, diamond means, route information means, and operation plan planning means. A vehicle information means memorize | stores the vehicle information regarding the some electric vehicle carrying a storage battery. The charging facility information means stores charging facility information relating to the charging capability of the charging facility that can be charged to the electric vehicle, which is disposed at a plurality of charging bases. The diagram means stores diagram information defining a plurality of operation diagrams including a route connecting a plurality of stop positions operated by the electric vehicle and at least one of a departure time and an arrival time of each stop position on the route. The route information means stores route information related to the route. The operation plan planning means allocates an electric vehicle to each operation schedule determined by the schedule information and prepares an operation plan. The operation planning means calculates the amount of electric power consumed when the electric vehicle operates on each route, calculates the amount of electric power charged in the electric vehicle at each charging base based on the amount of electric power consumed, Based on the above, the electric vehicle is allocated to the operation schedule.

FIG. 1 is a block diagram showing a functional configuration of an operation management apparatus according to the first embodiment of the present invention. FIG. 2 is a diagram for explaining the basic diagram. FIG. 3 is a diagram illustrating an example of a basic diagram. FIG. 4 is a diagram illustrating an example of operation information. FIG. 5 is a diagram illustrating an example of storage battery information. FIG. 6 is a diagram illustrating an example of route information. FIG. 7 is a diagram illustrating an example of stationary storage battery information. FIG. 8 is a diagram illustrating an example of system power information. FIG. 9 is a diagram illustrating an example of a vehicle allocation plan. FIG. 10 is a diagram illustrating an example of a charging plan. FIG. 11 is a diagram illustrating hardware of the operation management device. FIG. 12 is a diagram for explaining an operation planning method. FIG. 13 is a flowchart showing an operation plan planning process. FIG. 14 is a diagram for explaining a calculation method of the required energy of the operation diagram. FIG. 15 is a diagram illustrating an example of the required energy list. FIG. 16 is a flowchart showing a process for creating an assignable EV list. FIG. 17 is a diagram illustrating an example of an assignable EV list. FIG. 18 is a diagram illustrating a method for estimating the remaining power amount. FIG. 19 is a diagram for explaining a candidate solution creation method. FIG. 20 is a diagram for explaining a candidate solution decoding method. FIG. 21 is a diagram illustrating a vehicle allocation method. FIG. 22 is a flowchart showing a charging feasibility evaluation process. FIG. 23 is a diagram illustrating an example of system power supply. FIG. 24 is a diagram illustrating an example of the arrival point list. FIG. 25 is a flowchart showing the determination process of the feasibility of charging. FIG. 26 is a flowchart showing a calculation process of the remaining power amount of the stationary storage battery. FIG. 27 is a flowchart showing a calculation process of the amount of electric power charged to the EV bus. FIG. 28 is a flowchart illustrating a system power supply update process. FIG. 29 is a diagram for explaining a method of calculating the grid power supply. FIG. 30 is a flowchart showing a process for updating the remaining power amount of the stationary storage battery. FIG. 31 is a flowchart showing an operation plan planning process according to the second embodiment. FIG. 32 is a diagram illustrating an example of a candidate solution list. FIG. 33 is a diagram for explaining a method for creating a candidate solution using a genetic algorithm. FIG. 34 is a diagram illustrating an operation plan planning method according to the third embodiment. FIG. 35 is a flowchart illustrating an operation plan planning process according to the third embodiment. FIG. 36 is a diagram illustrating an example of a vehicle allocation list. FIG. 37 is a diagram for explaining a charging list update method. FIG. 38 is a flowchart showing a delay process of the departure time of the candidate departure point. FIG. 39 is a flowchart illustrating the rescheduling determination process according to the fourth embodiment. FIG. 40 is a flowchart showing a process for determining a decrease in the remaining electric energy of the EV bus. FIG. 41 is a flowchart illustrating the determination process of the feasibility of charging. FIG. 42 is a flowchart showing the adjustment process of the parameter α. FIG. 43 is a diagram illustrating an example of a basic diagram to which the operation plan planning method of the fifth embodiment is applied. FIG. 44 is a flowchart showing a calculation process of required energy of an operation diagram whose arrival point is a non-charging node. FIG. 45 is a diagram for explaining route information update processing according to the sixth embodiment. FIG. 46 is a diagram illustrating an example of the SOH mapping table and the target SOH table according to the seventh embodiment. FIG. 47 is a diagram illustrating an example of an operation plan in consideration of wireless power feeding. FIG. 48 is a flowchart illustrating the determination process of the feasibility of charging according to the eighth embodiment. FIG. 49 is a block diagram illustrating a functional configuration of an operation management apparatus according to the ninth embodiment. FIG. 50 is a flowchart showing an operation plan planning process according to the ninth embodiment. FIG. 51 is a diagram for explaining a method for extracting candidate departure points.

  Hereinafter, an operation management device according to an embodiment of the present invention will be described with reference to the drawings. This operation management device manages a plurality of registered electric vehicles so as to operate according to a predetermined diagram. Electric vehicles managed by the operation management apparatus include EV buses, electric cars, EV taxis, trains equipped with storage batteries (storage battery trains), and the like. In the operation management device, a non-electric vehicle such as a gasoline vehicle may be registered together with the electric vehicle. In the following, the operation management device will be described by taking EV bus operation management as an example, but the electric vehicle that the operation management device manages the operation is arbitrary.

(First embodiment)
FIG. 1 is a block diagram showing a functional configuration of an operation management apparatus according to an embodiment of the present invention. The operation management device prepares an operation plan for an EV bus that operates according to a schedule, considering dynamic factors. The operation plan includes an EV bus vehicle allocation plan for each operation schedule determined by the basic schedule and a charging plan at the charging base.

  The operation management device includes an operation plan planning means 10 for planning an operation plan, a basic diagram means 11 for storing a basic diagram in which an operation schedule for operating an EV bus is defined, and a vehicle information means for storing vehicle information about the EV bus. 12, route information means 13 for storing route information relating to the route on which the EV bus operates, charging facility information means 14 for storing charging facility information relating to the charging facility provided at the charging base on the operation schedule, and operation planning The plan storage means 15 for storing the operation plan prepared by the means 10, the replan determination means 16 for determining whether or not to replan the current operation plan according to dynamic factors, and the replan determination means 16 Re-planning requesting means 17 for notifying the plan request and starting the re-planning determination.

  The operation planning means 10 acquires the basic diagram, vehicle information, route information, and charging facility information from the basic diagram means 11, vehicle information means 12, route information means 13, and charging facility information means 14, The vehicle allocation plan for determining the allocation of the EV bus to a plurality of operation schedules determined in (1) and the charging plan for determining the amount of electric power charged to the EV bus at each charging base are made. The operation plan planning unit 10 includes a vehicle allocation unit 101 that creates a vehicle allocation plan based on the remaining electric energy of the EV bus, an operation diagram connection unit 102 that connects the arrival point and the departure point of each operation diagram, and each charge Charge amount calculation means 103 for calculating the amount of electric power charged on the EV bus at the base, and charge feasibility evaluation means 104 for evaluating the charge feasibility at the charging base. The connection between the arrival point and the departure point of each bus schedule means that one or a plurality of bus schedules operated by the same EV bus are determined from a plurality of bus schedules determined by the basic schedule. In addition, when the non-electric vehicle is registered in the operation management device, the operation plan creation unit 10 can obtain a vehicle including the non-electric vehicle and make a plan.

  The basic diagram means 11 stores a basic diagram (diagram information) of the EV bus. The basic diagram defines a plurality of operation diagrams including a route connecting a plurality of stop positions where the EV bus stops and at least one of arrival time and departure time of each stop position. By assigning an EV bus to each operation schedule determined by the basic schedule and determining the amount of charge power at each charging base, an operation plan for operating a plurality of EV buses registered in the operation management device is determined. In other words, the operation plan includes a basic schedule, a vehicle allocation plan that determines EV buses allocated to the operation schedules included in the basic diagram, and a charging plan that determines the amount of electric power charged by each EV bus at each charging base. Consists of.

  FIG. 2 is an explanatory diagram for explaining the outline of the basic diagram, and FIG. 2A shows the entire bus system. In this bus system, charging bases (such as a bus sales office) A and F and bus stops B, C, D, and E are provided as stop positions. The EV bus operates between each stop position according to a route indicated by a solid line in FIG.

  FIG. 2B is a basic diagram prepared for the bus system of FIG. 2A, and the basic diagram includes a plurality of operation diagrams. Here, the operation schedule defines the route that the EV bus operates and the schedule (time), and is shown in FIG. 2B by connecting the route from the departure point to the arrival point with a solid line. Has been. A basic diagram is configured by collecting a plurality of such operation schedules (for example, for one day).

  On the other hand, the service schedule includes one or more lines. Here, the streak defines the route and schedule (time) of each stop position on the operation diagram, and in FIG. 2 (b), connects each stop position on the operation diagram with a solid line. Is indicated by The operation diagram is formed by connecting such lines from the departure point to the arrival point.

  In addition, the service diagram (stripes) defines at least one (schedule) of arrival time and departure time of each stop position on the service diagram. In FIG. 2B, the earliest departure time is referred to as a plan start time Ts, and the last arrival time is referred to as a plan end time Te.

  FIG. 2C is a basic diagram for planning an operation, which shows the basic diagram of FIG. 2B in a simplified manner. In the basic diagram of FIG. 2 (c), only the starting point and the arriving point of each operation diagram are shown, and the intermediate stop position is omitted. In the description of the operation of the operation management apparatus to be described later, a basic diagram omitted for planning the operation is used.

  FIG. 3 is a diagram illustrating an example of a basic diagram. In FIG. 3, the basic diagram is shown in a table format in which the stop position, arrival time, and departure time are associated with each other. 3 includes an operation diagram ID for identifying each operation diagram shown in FIG. 2B, a route ID, a node ID indicating each stop position (node), and a departure time and an arrival time at each stop position. It is included. The route ID is used when the actual operation schedule cannot be specified only by the operation schedule ID. For example, in the bus system of FIG. 2 (a), when the bus schedule specified by the bus schedule ID indicates only the departure point A and the arrival point F, a plurality of actual bus schedules are assumed (AEF and AEDF). Such). In such a case, the route ID is used to identify the operation schedule. Accordingly, the route ID may not be used when the operation diagram can be uniquely specified by the operation diagram ID.

  The vehicle information means 12 stores vehicle information related to the EV bus. The vehicle information may be stored in advance in the vehicle information unit 12, or may be updated based on information acquired from the EV by the vehicle information unit 12 at a predetermined timing. Further, when a non-electric vehicle is registered in the operation management device, vehicle information related to the non-electric vehicle can also be stored. The vehicle information includes EV bus operation information and storage battery information of a storage battery mounted on the EV bus.

  FIG. 4 is a diagram illustrating an example of operation information. As shown in FIG. 4, the operation information includes a vehicle ID identifying each EV bus, a type of registered vehicle, a status indicating the current state of the EV bus (running, charging, standby, etc.), and the EV bus. The node ID of the stop position that passed most recently, the distance (km) from the stop position that passed most recently to the current position of the EV bus, the latest position time, the node ID of the stop position where the EV bus next passes, the current EV bus The distance (km) from the position to the next stop position, the latest SOC (%) of the storage battery mounted on the EV bus, and the like are included.

  The type of registered vehicle is used when an EV bus and a non-electric vehicle are registered in the operation management device, and is classified so that the EV bus and the non-electric vehicle can be distinguished. Moreover, in addition to the classification which distinguishes EV bus and a non-electric vehicle, you may classify | categorize for every kind of storage battery mounted in EV bus. The latest position time is the time when the latest position information is acquired from the EV bus. Based on the position information acquired at the latest position time, the distance from the latest stop position to the current position of the EV bus and the distance from the current position of the EV bus to the next stop position are calculated. The latest SOC (State of Charge) is the latest state of charge of the storage battery obtained from the EV bus, and is expressed as a ratio (%) to the effective capacity of the storage battery. When a non-electric vehicle is registered in the operation management device, the operation information of the non-electric vehicle is also stored in the vehicle information means 12 in the same manner as the EV bus operation information. In this case, the latest SOC of the non-electric vehicle is a null value.

  FIG. 5 is a diagram illustrating an example of storage battery information. As shown in FIG. 5, the battery information includes EV bus vehicle ID, battery initial capacity (kWh), SOH (%), remaining power lower limit (kWh), remaining power upper limit (kWh), and maximum charge. Rate (kW) and maximum discharge rate (kW). SOH (State of Health) indicates a ratio (%) of the chargeable electric energy to the battery initial capacity of the storage battery mounted on the EV bus. That is, the product of the battery initial capacity and SOH is the effective capacity (kWh) of the storage battery. The remaining power amount lower limit value and the remaining power amount upper limit value are determined in advance within the effective capacity range in order to suppress the deterioration rate of the storage battery. In FIG. 5, the lower limit value of the remaining electric energy and the upper limit value of the remaining electric energy are determined by the electric energy (kWh), but can also be determined by the ratio (SOC) to the effective capacity. The maximum charge rate and the maximum discharge rate are the maximum power that can be charged and discharged in the storage battery, and are determined in advance according to the type of the battery in order to suppress the deterioration rate of the storage battery.

  The route information means 13 stores route information related to the route on which the EV bus operates. The route information may be stored in advance in the route information means 13 or may be updated based on the vehicle information acquired from the vehicle information means 12. Further, the route information means 13 may acquire information from an external service that provides weather forecasts and traffic information.

  FIG. 6 is a diagram illustrating an example of route information. As shown in FIG. 6, the route information includes the distance (km) between the stop positions, the information update time, the required time between the stop positions, the electricity cost between the stop positions, and the like. The route information means 13 can update the required time between the stop positions and the power consumption based on the vehicle information. In addition, the required time and electricity costs between stop positions vary depending on dynamic factors such as road conditions (such as traffic congestion), road characteristics (uphill and downhill), external environment (temperature and weather), and number of passengers. The route information means 13 may update the route information in response to changes in these factors. Here, the electricity consumption is an average value of power consumption consumed per unit distance when the EV bus operates each route. Therefore, the power consumption can be calculated by dividing the amount of power consumed by the EV bus operating through each route by the distance of each route.

  The charging facility information means 14 stores charging facility information related to the charging capacity of the charging facility provided at each charging base, and a stationary storage battery information means 141 that stores information on a stationary storage battery provided at the charging base; And grid power information means 142 for storing information on power available from the grid. The charging facility information includes stationary storage battery information and system power information.

  The stationary storage battery information means 141 stores stationary storage battery information related to the stationary storage battery. The stationary storage battery information may be stored in advance in the stationary storage battery information unit 141, or may be updated based on information acquired from the stationary storage battery or the like by the stationary storage battery information unit 141 at a predetermined timing. FIG. 7 is a diagram illustrating an example of stationary storage battery information. As shown in FIG. 7, the stationary storage battery information includes a node ID that identifies a charging base where the stationary storage battery is installed, a storage battery ID that identifies the stationary storage battery, a battery initial capacity (kWh) of the stationary storage battery, and SOH. (%), Remaining power lower limit (kWh), remaining power upper limit (kWh), maximum charge rate (kW), maximum discharge rate (kW), and remaining power (kWh). In FIG. 7, one stationary storage battery is installed at each charging site, but a plurality of stationary storage batteries can be installed at the same charging site. In this case, the stationary storage battery information means 141 may individually store the stationary storage battery information of each stationary storage battery, or the initial battery capacity and the remaining power amount of the stationary storage battery installed at the same charging base. May be stored as stationary storage battery information of each charging base. The upper and lower limits of the remaining power amount and the maximum charge / discharge rate are set in advance in order to suppress deterioration of the storage battery.

  The grid power information unit 142 stores grid power information related to energy (amount of power) available from the grid and contract power. The system power information may be stored in advance in the system power information unit 142 based on the contract contents with the system, or may be updated based on a demand response (DR) issued from the system. FIG. 8 is a diagram illustrating an example of system power information. The grid power information includes energy information available from the grid and contract power information.

  As shown in FIG. 8 (a), the energy information includes a node ID for identifying a charging base, a time at which usage conditions for each power level are applied, an electricity charge for each power level (yen / kWh), and available information. Electricity (kWh) is included. In FIG. 8A, two power levels, power levels 1 and 2, are set, but one power level or three or more power levels may be set. According to FIG. 8A, the contractor of this system can use 250 kWh at 25 yen / kWh from 0:00 to 8:00 at the charging base A (power level 1). To use more energy, an electricity charge of 30 yen / kWh is required (power level 2). When power is used up to the amount of power set at power level 2 (350 kWh), power supply from the system cannot be received from 0:00 to 8:00. Further, as shown in FIG. 8B, the contract power information includes a node ID for specifying a charging base, contract power (kW), and the like. The amount of power that can be used at each power level at each charging base described above is determined within the range of power that can be used in accordance with the contract power. For example, according to FIG. 8B, the contract power at the charging base A is 200 kW, and therefore the amount of power available at the charging base A from 0:00 to 8:00 according to the contract power is 1600 kWh (= 200 kW × 8h). Accordingly, the amount of power that can be used from 0:00 to 8:00 at the charging site A at each power level is determined within a range of 1600 kWh or less.

  The plan storage unit 15 stores information on the vehicle allocation plan and the charging plan prepared by the operation plan planning unit 10. FIG. 9 is a diagram illustrating an example of a vehicle allocation plan (vehicle allocation list). As shown in FIG. 9, in the vehicle allocation plan, EV bus allocation is determined for each schedule, and information (node ID, arrival time, departure time) for identifying each schedule defined by the basic schedule is shown. And the like, and the vehicle ID that identifies the EV bus assigned to each bus schedule, and the presence or absence of charging at the stop position (with charging: Y, without charging: N), and the like. For example, in FIG. 9, an EV bus with a vehicle ID of 001 is assigned to an operation diagram AEDF that operates in the order of stop positions A, E, D, and F. As shown in FIG. 9, the vehicle allocation plan shown in a table format is called a vehicle allocation list.

  FIG. 10 is a diagram illustrating an example of a charging plan (charging list). As shown in FIG. 10, the charging plan includes a vehicle ID that specifies the EV bus, a node ID that specifies the charging base to which the EV bus is charged, and an estimated arrival time at which the EV bus is expected to arrive at the charging base. The estimated departure time at which the EV bus is expected to depart from the charging base, the expected remaining electric energy (kWh) of the EV bus upon arrival at the charging base, the target residual electric energy (kWh), and the like are included. The target remaining power amount is a target value of the remaining power amount after the EV bus is charged at the charging base. As shown in FIG. 10, the charging plan expressed in a tabular form is called a charging list.

  The re-planning determination unit 16 determines whether or not to re-plan the current operation plan when receiving a re-planning request notification from the re-planning request unit 17 or at a predetermined time interval. For the re-planning determination by the re-planning determination means 16, the EV bus delay information and the remaining power amount during operation, the energy available at the charging base, the remaining power amount of the stationary storage battery, and the electricity cost and required between the stop positions Dynamic factors that change during EV bus operation, such as time, are used. When the re-planning determination unit 16 determines that the re-planning is executed, the operation plan planning unit 10 re-plans the operation plan.

  The replanning request unit 17 notifies the replanning determination unit 16 of a replanning request for starting the replanning determination. The re-planning request unit 17 detects a dynamic factor change, for example, a change in energy available at the charging base, and notifies the re-planning request. As shown in FIG. 1, the replanning request unit 17 may be provided independently, and the vehicle information unit 12, the route information unit 13, the charging facility information unit 14, etc. function as the replanning request unit 17. May be. For example, when the vehicle information unit 12 functions as the re-planning request unit 17, the vehicle information unit 12 may notify the re-planning request based on the delay information of the EV bus being operated and the remaining power amount. In addition, when the route information unit 13 functions as the replanning request unit 17, the route information unit 13 may detect a change in power consumption or required time between the stop positions and notify the replanning request. When the charging facility information unit 14 functions as the re-planning request unit 17, the charging facility information unit 14 detects a change in the energy available at the charging base and the remaining power amount of the stationary storage battery, and re-plans. Just notify the request.

  Here, FIG. 11 is a diagram illustrating hardware of the operation management apparatus. This operation management device can be realized by using a computer device as basic hardware. As shown in FIG. 11, the computer device includes a CPU 111, an input unit 112, a display unit 113, a communication unit 114, a main storage unit 115, and an external storage unit 116, which are connected to be communicable with each other via a bus 117. .

  The input unit 112 includes input devices such as a keyboard and a mouse, and outputs an operation signal generated by operating the input device to the CPU 111. The display unit 113 includes a display such as an LCD (Liquid Crystal Display) and a CRT (Cathode Ray Tube). The communication unit 114 includes a wireless or wired communication unit, and performs communication using a predetermined communication method. The external storage unit 116 includes, for example, a hard disk, a memory device, a storage medium such as a CD-R, a CD-RW, a DVD-RAM, or a DVD-R. The external storage unit 116 stores a control program for causing the CPU 111 to execute processing of the operation management device. Moreover, the data of each memory | storage means with which an operation management apparatus is provided are memorize | stored. The main storage unit 115 expands a control program stored in the external storage unit 116 under the control of the CPU 111, and stores data necessary for executing the program, data generated by the execution of the program, and the like. The main storage unit 115 includes an arbitrary memory such as a nonvolatile memory.

  Each functional configuration of the operation management apparatus as described above is realized by the CPU executing the control program. The control program may be installed in advance in the computer device. In addition, a control program stored in a storage medium such as a CD-ROM or a control program distributed via a network may be appropriately installed in a computer device and used. A configuration without the input unit 112 and the display unit 113 is also possible.

  Next, an outline of the operation plan planning process in the present embodiment will be described with reference to FIGS. FIG. 12 is a diagram for explaining the operation plan planning process, and FIG. 13 is a flowchart showing the operation plan planning process. In addition, each basic diagram shown in FIG. 12 is the above-described omitted basic diagram (see FIG. 2C). Hereinafter, the starting point and the arriving point on the basic diagram are referred to as the starting point i and the arriving point i according to the number i assigned to each, and the operation diagram from the starting point i to the arriving point i is referred to as the operating diagram i. Called.

  First, the operation planning means 10 calculates the required energy when the EV bus operates from the departure point to the arrival point on the route determined by each operation schedule using the route information (step S101). The required energy means the amount of power consumed when the EV bus operates. Hereinafter, the energy required when the EV bus operates from the departure point to the arrival point on the route determined by the operation diagram is referred to as required energy of the operation diagram.

  Next, an allocatable EV list is created using vehicle information or the like (step S102). The assignable EV list is a list in which storage battery information and position information of EV buses that can be assigned to each operation schedule is collected, and is used for vehicle allocation to each operation diagram in step 104 described later. When re-planning the operation plan, an allocatable EV list can be created by using an existing vehicle allocation list (vehicle allocation plan) or charging list (charging plan).

  Next, by connecting the arrival point and the departure point of each operation diagram determined by the basic diagram, the operation diagram is connected, and one or a plurality of connection method candidate solutions are created (step S103). That is, the candidate solution defines a set of one or a plurality of operation schedules operated by the same EV bus. Connection between the arrival point and the departure point is possible when the arrival time at the arrival point is earlier than the departure time at the departure point, and the arrival point and the departure point are at the same stop position.

  FIG. 12A shows two examples of candidate solutions (candidate solution 1, candidate solution 2). In the candidate solution 1, the operation diagram 1, the operation diagram 2, and the operation diagram 4 are connected. In this case, the operation schedules 1, 2, and 4 are operated by the same EV bus, and the operation diagram 3 is operated by another EV bus. In the candidate solution 2, the operation diagram 1 and the operation diagram 3 are connected, and the operation diagram 2 and the operation diagram 4 are connected. In this case, the operation schedules 1 and 3 operate on the same EV bus, and the operation schedules 2 and 4 operate on other EV buses. A connection method candidate solution defines such a connection method for each schedule.

  Next, the operation planning means 10 allocates an EV bus to each operation diagram of the created candidate solutions (step S104), and creates a vehicle allocation list for each candidate solution. The same EV bus is assigned to each of the plurality of bus schedules connected in the candidate solution. As shown in FIG. 12 (b), in candidate solution 1, EV 2 is assigned to operation diagram 1 and EV 3 is assigned to operation diagram 3. Since the operation diagrams 2 and 4 are connected to the operation diagram 1, the EV 2 is assigned in the same manner as the operation diagram 1. In candidate solution 2, EV1 is assigned to operation diagram 1, and EV4 is assigned to operation diagram 2. Since the operation diagram 3 is connected to the operation diagram 1, EV 1 is assigned, and since the operation diagram 4 is connected to the operation diagram 2, EV 4 is assigned.

  The operation planning means 10 considers the effective capacity of the storage battery of the EV bus and the remaining power amount when allocating the EV bus to each operation schedule. Specifically, each bus schedule is assigned an EV bus that can be charged with the required charging power amount at the charging base. The required amount of charging power is the minimum amount of charging power required for the EV bus to operate without power shortage according to each schedule. When the effective capacity of the EV bus is smaller than the required charging power amount of each bus schedule, the EV bus cannot charge the required charging power amount, and there is a possibility of running out of electricity during the operation of the route defined by the bus schedule. high. Therefore, the operation planning means 10 allocates to each operation diagram an EV bus having a larger effective capacity than the required charging power amount of each operation diagram.

  Further, the operation planning means 10 evaluates the feasibility of charging each candidate solution to which the EV bus is assigned (step S105). That is, whether or not EV buses operating on a route defined by a plurality of connected operation schedules can be charged so that the remaining power amount is equal to or greater than a predetermined power amount at each charging base (charging feasibility). Judgment is made, and based on the judgment result, charging feasibility of the entire connected operation schedules is evaluated. The predetermined power amount is, for example, a lower limit value of the remaining power amount of the storage battery of the EV bus.

  Further, in the above determination of the feasibility of charging, the charging power amount at the charging base is calculated for the charging base determined to be chargeable (step S105), and a charge list is created. The charging power amount at the charging base is the amount of power to charge the EV bus between the arrival time and the departure time at the charging base where the arrival point and the departure point of the connected service schedule are located. For example, in the candidate solution 1 in FIG. 12B, the charging power amount at the connection portion between the operation diagram 1 and the operation diagram 2 is 10 kWh, which is the starting point from the arrival time of the arrival point 1 at the charging base F. 2 is the amount of electric power charged in the EV bus by the departure time of 2. Hereinafter, a connection portion between operation schedules where the EV bus is charged, that is, a connection portion between an arrival point and a departure point is referred to as a charging point.

  After the vehicle allocation and the calculation of the charging power amount are completed for each candidate solution created in step S103, it is determined whether or not the termination condition is satisfied (step S106). As an end condition, there are candidate solutions in which the number of assigned EV buses is smaller than the number of assignable EV buses among the created candidate solutions, and the predetermined restrictions are satisfied at all charging points. That there is a candidate solution that can be charged to the EV bus. In addition, an upper limit value may be provided for the number of candidate solutions created, processing time, and the number of processing iterations, and the end condition may be set.

  If the termination condition is not satisfied in step S106 (NO in step S106), one or more new candidate solutions are created (step S107), and the process returns to step S104. On the other hand, when the termination condition is satisfied in step S106 (YES in step S106), the candidate solution with the highest evaluation is selected from the created candidate solutions, and the vehicle allocation list and charging created for the candidate solution are selected. A list is output (step S108).

  Evaluation of the candidate solution can be performed based on the charge feasibility score calculated for each candidate solution in accordance with the evaluation of the charge feasibility. The charge feasibility score is an evaluation value calculated according to the number of charge points that can be charged to the EV bus so as to satisfy a predetermined constraint. In the present embodiment, the charge feasibility score has a minimum value of 0, and the maximum value is the number of charge points of each candidate solution. As a candidate solution with the highest evaluation, a candidate solution that can charge the EV bus so as to satisfy a predetermined constraint at all charging points, that is, a candidate solution whose charging feasibility score matches the number of charging points is selected. Can do. A candidate solution with the smallest number of allocated EV buses may be selected as a candidate solution with the highest evaluation. Furthermore, the charge feasibility score and the number of allocated EV buses may be used in combination.

  In the processing of step S101 to step S108 described above, the vehicle allocation process of step S104 is performed by the vehicle allocation unit 101, and the charging feasibility evaluation of step S105 is performed by the charging feasibility evaluation unit 104, and the calculation of the charging electric energy is performed. Is performed by the charge amount calculation means 103, and the remaining steps including the creation of the connection method candidate solution in step S103 can be performed by the operation diagram connection means 102.

  Below, each step of step S101-step S105 of the above-mentioned operation planning process is demonstrated in detail.

(Step S101)
The calculation method of the required energy of each service diagram in step S101 will be described with reference to FIGS. The required energy of the operation schedule can be calculated based on the distance (km) between each stop position and the electricity cost (kWh / km). The operation planning means 10 acquires route information from the route information means 13 and calculates the required energy between each stop position included in the operation diagram for calculating the required energy, that is, the required energy of each stripe. The required energy of each streak can be calculated by the distance between each stop position × electricity cost × safety parameter α. Then, the calculated required energy of each streak is totaled to calculate the required energy of the travel schedule. Therefore, the required energy of the operation schedule can be calculated by the following formula.

  Here, n is the number of connected stop positions (= number of connected stop positions−1). For example, in the case of the operation diagram of FIG. 14, the required energy of the operation diagram is 42.02 kWh. In FIG. 14, the safety parameter α is 1.1. This safety parameter α is a parameter for adding the surplus power amount to the required energy of the operation diagram, and is set in a range of α ≧ 1. Hereinafter, the safety parameter α is simply referred to as parameter α. By calculating a large amount of energy required for operation schedules in advance using parameter α and calculating vehicle allocation and charging power based on this required energy, the possibility of electric shortage occurring on the EV bus may be reduced. it can. In addition, by changing the parameter α according to the above-described dynamic factor, it is possible to calculate an appropriate required energy according to the dynamic factor. As shown in FIG. 15, the operation planning means 10 creates a required energy list for each operation diagram defined by the basic diagram.

(Step S102)
The assignable EV list creation process in step S102 will be described with reference to FIGS. FIG. 16 is a flowchart showing a process for creating an assignable EV list. First, the operation planning means 10 obtains EV bus vehicle information, route information, a vehicle allocation list, a charging list, and the like (step S1201). When the first operation plan is created, the vehicle allocation list and the charge list are empty lists. From the acquired vehicle information, vehicle information whose status is in standby / running / charging is extracted (step S1022). When a non-electric vehicle is registered in the operation management device, the vehicle information of the non-electric vehicle can be excluded by extracting the vehicle information of type EV. Next, the effective capacity of each EV bus is calculated based on the initial battery capacity and SOH included in the vehicle information (step S1023). The effective capacity can be calculated by the following formula.

  Next, the status of each EV bus is determined (step S1024). If the status of the EV bus is standby, the remaining power is calculated (step S1025). The remaining power amount can be calculated by the following formula based on the latest SOC included in the vehicle information and the effective capacity calculated in step S1023.

  After the remaining power is calculated, based on the information extracted from the EV bus vehicle information (node ID, vehicle ID, remaining power lower limit, maximum charging rate, etc.), and the calculated effective capacity and remaining power Then, an allocatable EV list as shown in FIG. 17 is created (step S1028). As the node ID, the most recently passed node ID (standby node ID) can be used.

  In step S1024, the remaining electric energy is set for the EV bus whose status is being charged (step S1026). When the operation of the EV bus has already been started and the operation plan is re-planned, the target remaining electric energy (kWh) can be extracted from the charging plan and set as the remaining electric energy. Moreover, what is necessary is just to set the electric energy which is scheduled to be charged before EV bus starts an operation as a remaining electric energy, when preparing the first operation plan.

  In step S1024, the remaining electric energy at the charging base where the EV bus arrives next is estimated for the EV bus whose status is traveling (step S1027). The case where the EV bus is running is a case where the EV bus has already started operation and the operation plan is re-planned. In this case, the remaining electric energy of the EV bus is estimated based on the vehicle information, the route information, and the charging list. The remaining power amount can be estimated by subtracting the required energy from the latest position to the next charging base from the remaining power amount at the latest position.

  Here, a method of estimating the remaining power amount will be specifically described with reference to FIG. In FIG. 18, it is assumed that the EV bus is operating according to an operation schedule that stops in the order of stop positions A, B, C, D, and F, and is traveling toward the charging base F. In FIG. 18A, it is assumed that the EV bus has departed from the charging base A, and the remaining power at the time of departure is 50 kWh. In this case, the remaining electric energy (7.98 kWh) at the charging base F is estimated by subtracting the required energy (42.02 kWh) of the operation schedule calculated based on the route information from the remaining electric energy (50 kWh) at the time of departure. can do. On the other hand, in FIG. 18B, the EV bus is traveling from the stop position C to the stop position D. In this case, the required energy ((9km-2km) x 1.1kWh / km) from the latest position to the stop position D and the streak between the stop position DF and the remaining electric energy at the latest position (45kWh x 60%) By subtracting energy (7 km × 1.3 kWh / km), the remaining power amount (8.52 kWh) at the charging site F can be estimated.

(Step S103)
A method for creating candidate solutions for the connection method in step S103 will be described with reference to FIG. FIG. 19 is a diagram for explaining a candidate solution creation method. The operation plan planning means 10 encodes the arrival point and the departure point of each operation diagram in order to create one or more candidate solutions of connection methods based on the basic diagram.

  First, the operation planning means 10 creates a candidate departure point list to which each arrival point can be connected from the basic diagram (see FIG. 19A). As shown in FIG. 19B, the candidate departure point list includes each arrival point arranged in ascending order of arrival times, a candidate departure point that is connectable to each arrival point, and the position of each arrival point. Charging base and arrival point index. In the candidate departure point list, candidate departure points are all departure points that depart after the arrival time of each arrival point. In addition, since the arrival point may not be connected to any departure point, candidate departure point-1 is given to each arrival point as a temporary candidate departure point representing such a case. Thus, for example, the candidate departure points for arrival point 1 are departure points 4, 6, 7, and -1. Arrival points where there are no connectable candidate departure points (for example, arrival points 7, 8, 9) are deleted from the candidate departure point list.

  Next, a candidate solution is created based on the candidate departure point list. A candidate solution is created by selecting one candidate departure point for each arrival point index and arranging them in the order of arrival point indexes. Therefore, the length of the candidate solution is the number of arrival points where there are connectable candidate departure points (the number of arrival point indexes), and the j-th value of the candidate solution corresponds to the candidate departure point of the arrival point index j. For example, the candidate solution of FIG. 19C is 589476, and the third value (9) of this candidate solution is the candidate departure point of the arrival point index 3. In other words, the candidate solution indicates that the arrival point 6 and the candidate departure point 9 are connected.

  Selection of candidate departure points for each arrival point index is random. However, since the same starting point cannot be connected to a plurality of arrival points, the restriction that candidate starting points other than candidate starting point-1 can be selected only once in the same candidate solution is applied. The Candidate departure point-1 can be selected a plurality of times in the same candidate solution.

(Step S104)
The vehicle allocation method in step S104 will be described with reference to FIGS. The operation planning means 10 allocates an EV bus to one or a plurality of candidate solutions created in step S103, and creates a vehicle allocation list.

  First, the operation planning means 10 decodes the candidate solution using the basic diagram. FIG. 20 is a diagram for explaining a candidate solution decoding method. The operation planning means 10 extracts an arrival point corresponding to the arrival point index from the candidate departure point list and creates an arrival point list. As shown in FIG. 20A, arrival points are arranged in ascending order of arrival time in the arrival point list.

  Next, the generated arrival point list and the candidate solution are compared, the arrival point of the arrival point index j in the arrival point list is connected to the candidate departure point of the arrival point index j of the candidate solution, and the charging point connection graph Create In the charging point connection graph of FIG. 20B, operation diagrams 1, 4, and 8 are connected, operation diagrams 2, 5, 6, and 9 are connected, and operation diagrams 3 and 7 are connected. The connection part between each service schedule is a charging point which can charge EV bus. Hereinafter, the connection part between the connected operation diagram X and the operation diagram Y is referred to as charging points X and Y.

  Next, a vehicle is allocated to each service schedule connected in the charging point connection graph. FIG. 21 is a diagram illustrating a vehicle allocation method. The operation planning means 10 calculates the total distance of the connected operation diagrams and the total required energy of the operation diagrams based on the route information. For example, according to Fig.21 (a), the sum total of the distance of the operation | movement schedules 2, 5, 6, and 9 is 155km, and the sum total of the request | requirement energy of an operation | movement schedule is 90kWh. Next, based on the descending order of the total required energy of the calculated operation diagram, the connected operation diagrams are sorted. That is, the operation schedules connected in descending order of the total required energy of the operation diagrams are sorted. This sorting is performed for each charging base at the starting point of the first connected schedule. According to FIG. 20A, the starting point of the operation diagram 1 and the operation diagram 3 is the charging base A, and the starting point of the operation diagram 2 is the charging base F. Therefore, the operation schedules that are connected are sorted into operation schedules 1, 4, 8 and operation diagrams 3, 7 and operation diagrams 2, 5, 6, 9. Since operation schedules 1, 4, and 8 have a larger total energy required for operation schedules than operation diagrams 3 and 7, operation diagrams 1, 4, and 8 are sorted before operation diagrams 3 and 7 (FIG. 21A). reference).

  Furthermore, the required charging power amount is calculated for each charging point of the connected service schedule. The required charging power amount is the minimum charging power amount required for the EV bus to operate without running out of the route defined by each operation schedule. The required charge power amount at the charging points p and q between the operation diagram p and the operation diagram q is calculated by subtracting the remaining electric energy of the EV bus at the arrival point p of the operation diagram p from the required energy of the operation diagram q. be able to.

  For example, the required charging electric energy at the charging points 1 and 4 of the operation schedules 1, 4 and 8 in FIG. 21A can be calculated as follows.

  Assuming that the EV bus departs in a fully charged state, the remaining power amount at the starting point of the operation diagram 1 becomes the effective capacity of the EV bus. Moreover, the request | requirement charge electric energy of the charge points 4 and 8 of the service schedules 1 and 4 and 8 can be calculated as follows.

  Here, as the charging power amount at the charging points 1 and 4, the required charging power amount at the charging points 1 and 4 can be used. As described above, the required charging power amount at each charging point on the connected operation diagram is calculated, and the maximum required charging power amount that is the maximum required charging power amount on the connected operation diagram is extracted. As shown in FIG. 21 (a), in the case of operation schedules 1, 4, and 8, the maximum required charging power amount is 35 kWh at charging points 4 and 8.

  Further, a required charge rate is calculated based on the calculated required charge power amount. The required charge rate is the minimum charge rate for charging the required charge energy at the charge point, and the required charge rate at the charge points p and q is the chargeable period of the required charge energy at the charge points p and q. It can be calculated by dividing. The chargeable period is the period from the arrival time of the arrival point p to the departure time of the departure point q, that is, the whole or part of the stop time at the charging point. When the chargeable period is the stop time, the required charge rate can be calculated by the following formula.

  The maximum required charge rate that is the maximum required charge rate is extracted from the required charge rates at each charging point. For example, the maximum required charging rate of the service schedules 1, 4 and 8 is 90 kW (see FIG. 21 (a)). Since the required charge rate depends on the stop time at each charge point, the required charge rate at the charge point that is the maximum required charge power amount is not always the maximum required charge rate.

  Based on the maximum required charge power amount and the maximum required charge rate calculated as described above, an EV bus that satisfies the following conditions is assigned to each connected schedule, and a vehicle assignment list is created.

  By assigning an EV bus that satisfies such conditions, an EV bus that can be charged so as not to run out of power during operation on the route defined by the operation diagram can be assigned to each operation diagram. FIG. 21B shows the assigned EV bus.

  When there are a plurality of EV buses that satisfy the above conditions, vehicles are allocated based on the descending order of SOH. That is, an EV bus having a large SOH is allocated to a set of operation diagrams having a large total energy required for the operation diagram. The required energy of each bus schedule changes according to dynamic factors (external environment, road characteristics, etc.). For example, a bus schedule going up a long slope during morning rush hour requires higher energy. On the other hand, the required energy of the operation schedule with a short distance is low. Therefore, by assigning EV buses with high SOH to bus schedules with high required energy and allocating EV buses with low SOH to bus schedules with low required energy, taking into account dynamic factors, EV bus storage battery degradation Can be suppressed. In addition, instead of the total required energy of the operation schedule, an average or total required energy per unit distance (for example, 1 km) can be used. Moreover, when the battery initial capacity of the storage battery of each EV bus | bath is equal, it can also be used on the basis of effective capacity instead of SOH.

  In the above vehicle assignment, when there is no EV bus that satisfies the condition and there is a non-electric vehicle that can be assigned, the non-electric vehicle may be assigned. If there is no non-electric vehicle that can be assigned, the vehicle assignment fails, the vehicle assignment process for the candidate solution ends, and the vehicle assignment for the next candidate solution is performed. When the above-described vehicle assignment process is completed for all candidate solutions created in step S103, the operation plan planning process proceeds to step S105.

(Step S105)
The charge feasibility evaluation and the calculation of the charge power amount in step S105 will be described with reference to FIGS. The operation planning means 10 evaluates the charge feasibility with respect to one or a plurality of candidate solutions for which vehicle allocation has been performed in step S104, and calculates the amount of charging power for the chargeable candidate solutions. Hereinafter, a charging feasibility evaluation method and a charging power amount calculation method for each candidate solution to which vehicle allocation is performed will be described.

  First, the charge feasibility evaluation process for each candidate solution will be described with reference to FIG. FIG. 22 is a flowchart showing a charge feasibility evaluation process (hereinafter simply referred to as “evaluation process”). The operation plan planning means 10 acquires a candidate solution, a candidate departure point list, a vehicle allocation list, a required energy list, a plan start time Ts, a plan end time Te (see FIG. 2), and the like (step S10501).

  Next, stationary storage battery information, system power information, storage battery information, and the like are acquired (step S10502), and a charge feasibility score that is an evaluation value of charge feasibility is set to 0 (step S10503).

Next, based on the acquired grid power information, the grid supply power P _{i, 1} (t) (kW) that can be used from the grid at power level 1 at time t and the grid power that can be used from grid at power level 2 at time t System supply power P _{i, 2} (t) (kW) is calculated (step S10504). The grid supply power P _{i, 1} (t), P _{i, 2} (t) can be calculated as follows.

Here, i is the node ID of the charging base, s is the sampling interval, E _{i, 1} (t ₁ : t ₂ ) is the grid power supply amount (kWh) from time t ₁ to time t ₂ at power level 1, E _{i, 2} (t ₁ : t ₂ ) is the grid power supply amount (kWh) from time t ₁ to time t ₂ at power level 2. For example, when the energy information (system power information) shown in FIG. 23A is acquired, the system power supply from 7:00 (t ₁ ) to 7:59 (t ₂ ) is shown in FIG. Is calculated as follows. In FIG. 23B, the sampling interval s is 1 minute, but the sampling interval s is not limited to this, and can be arbitrarily set in units of seconds or minutes.

  Next, an arrival point list is created (step S10505). The arrival point list is a list in which arrival points are arranged in ascending order from the plan start time Ts to the plan end time Te, and can be created from the basic diagram (see FIG. 20A). When the basic diagram in FIG. 24A is acquired, the arrival points list shown in FIG. 24B is created by arranging the arrival points in order of arrival time.

  When the arrival point list is created, arrival points Ta are acquired based on the ascending order of time (step S10506). In the case of the arrival point list in FIG. 24B, the arrival point 1 is acquired as the first arrival point Ta. If the arrival point Ta cannot be acquired (NO in step S10507), that is, if the evaluation process has been completed for all arrival points in the arrival point list of the candidate solution for which the evaluation process is being performed, the operation planning means 10 Ends the evaluation process, stores the charge feasibility score and the charge list of the candidate solution (step S10514), and performs the evaluation process for the next candidate solution. When the next candidate solution does not exist, that is, when the evaluation process has been completed for all candidate solutions to which vehicle assignment has been performed in step S104, the process proceeds to the determination process in step S106.

  If the arrival point Ta can be acquired (YES in step S10507), it is determined whether there is a candidate departure point Td connected to the arrival point Ta (step S10508). If there is no candidate departure point Td connected to the arrival point Ta (NO in step S10508), the process returns to step S10506 to acquire the next arrival point Ta. The case where there is no candidate departure point Td is the case where the arrival point Ta is the final arrival point of a series of connected bus schedules, like the arrival point 8 in FIG.

  If there is a candidate departure point Td (YES in step S10508), the required energy Ereq (kWh) of the service schedule starting from the candidate departure point Td is acquired from the required energy list (step S10509). Hereinafter, an operation diagram starting from the departure point X is expressed as “operation diagram of departure point X”, and an operation diagram ending at the arrival point Y is expressed as “operation diagram of arrival point Y”.

  Next, it is determined whether or not a predetermined charging power amount can be charged between the arrival time at the arrival point Ta and the departure time at the candidate departure point Td based on the acquired energy required for the operation schedule (step S10510). Details of the determination of the feasibility of charging will be described later. If it is determined that charging is impossible in the determination of the feasibility of charging (NO in step S10510), the process proceeds to step S10514, and the evaluation process for the candidate solution ends. On the other hand, if it is determined that charging is possible in the determination of charge feasibility (YES in step S10510), the charge feasibility score is increased by 1 (step S10511).

Next, the amount of charging power to be charged between the arrival point Ta and the candidate departure point Td is calculated (step S10512), and the grid supply power P _{i, 1} (t), P _{i, 2} (t) and the stationary storage battery are calculated. Is updated (step S10513), and the process returns to step S10506 to acquire the next arrival point Ta.

In the following, determination of charge feasibility (step S10510), calculation of charge power amount (step S10512), update of system supply power P _{i, 1} (t), P _{i, 2} (t) (step S10513), and The update of the remaining power amount of the stationary storage battery (step S10513) will be described in detail.

First, details of the determination of the feasibility of charging (step S10510) will be described with reference to FIGS. FIG. 25 is a flowchart showing the determination process of the feasibility of charging. The operation planning means 10 first acquires the arrival point Ta and the candidate departure point Td (step S401), the grid supply power P _{i, 1} (t), P _{i, 2} (t), and the sampling interval s (sec). Then, stationary battery information, EV bus remaining power lower limit EVlow (battery information), and the like are acquired (step S402). The sampling interval s can be set arbitrarily.

Next, the arrival time of the arrival point Ta is set as the start time ts, the departure time of the candidate departure point Td is set as the end time te (step S403), and the grid supply power P (t) is set at the power level 1. The grid supply power P _{i, 1} (t) is set (step S404). Based on the set parameters, the system power supply amount Eg (kWh) supplied from the system between the start time ts and the end time te is calculated (step S405). The grid power supply amount Eg can be calculated by the following equation.

  The grid power supply amount Eg (kWh) calculated here is energy that can be used from the grid between the start time ts and the end time te in order to charge the EV bus. Further, the amount of power that can be used from the stationary storage battery between the start time ts and the end time te is calculated (steps S406 to S408).

  First, using the node ID of the arrival point Ta, the stationary storage battery information of the stationary storage battery SSB that can be used at the arrival point Ta (charging base) is acquired from the stationary storage battery information (step S406). Next, the arrival point Tap immediately before the arrival point Ta is extracted from the arrival point list (step S407). The arrival point Tap is the latest arrival point among the arrival points whose arrival time is earlier than the arrival point Ta and whose node ID is the same as the arrival point Ta. For example, if the arrival point Ta is the arrival point 5 in the arrival point list of FIG. 24 (b), the arrival point Tap is the arrival point 3.

Based on the extracted arrival point Tap, the stationary storage battery SSB arrives at the arrival point Ta when it is charged with the power supply of power level 1 between the arrival time at the arrival point Tap and the arrival time at the arrival point Ta. The remaining electric energy E _SSB (kWh) of the stationary storage battery SSB at the arrival time is calculated (step S408). The remaining power amount E _SSB (kWh) calculated here is the amount of power that can be used from the stationary storage battery between the start time ts and the end time te in order to charge the EV bus. The details of the calculation method of the remaining power amount E _SSB will be described later.

Available at the arrival point Ta from the start time ts to the end of determination te based on the grid power supply amount Eg (kWh) calculated in the above steps and the remaining power amount E _SSB (kWh) of the stationary storage battery SSB A simple energy Eavail (kWh) is calculated (step S409). The energy Eavail can be calculated by the following formula.

  Next, the remaining electric energy EVrem of the EV bus at the arrival point Ta is estimated (step S410). The remaining power amount EVrem can be estimated by the same estimation method as in step S1027. That is, it is estimated by subtracting the required energy of the operation diagram at the arrival point Ta from the remaining power amount at the starting point of the operation diagram at the arrival point Ta (operation diagram ending at the arrival point Ta).

  Next, EV bus remaining power lower limit EVlow, EV bus remaining power amount (estimated value) EVrem at arrival point Ta, required energy Ereq of operation schedule at candidate departure point Td (operation diagram starting from candidate departure point Td), Then, based on the energy Eavail that can be used at the arrival point Ta, it is determined whether or not the following equation holds (step S411).

In the above equation, since Ereq−EVrem is the required charging power amount, the available energy Eavail is compared with the total value of the remaining power amount lower limit EVlow and the required charging power amount (Ereq−EVrem). . If the above equation does not hold (NO in step S411), the grid supply power P (t) is set to P _{i, 2} (t) (step S413), and the determination process returns to step S405. And the determination process (step S405-step S411) similar to the above is performed also in the power level 2. In step S411 of the determination process at power level 2, if the above equation does not hold again (NO in step S411), it is determined that the predetermined power amount cannot be charged (step S414), and the process returns to step S10514 of the evaluation process. Evaluate the feasibility of charging the next candidate solution. That is, the determination process of the feasibility of charge is performed for each of the power level 1 and the power level 2. When three or more power levels are set, the determination process may be similarly performed for each power level.

On the other hand, if the above equation holds (YES in step S411), the energy Eavail that can be used at the arrival point Ta between the start time ts and the end time te is the remaining power amount lower limit EVlow and the required charge power amount. Greater than total value. Therefore, it means that the battery can be charged at the arrival point Ta so that the remaining electric energy of the EV bus does not become smaller than the lower limit value EVlow of the remaining electric energy during operation on the route determined by the operation schedule of the candidate departure point Td. . In this case, the required discharge amount E _SSB req is calculated (step S415), it is determined that the predetermined power amount can be charged (step S416), and the process proceeds to step S10511 of the evaluation process.

Here, the required discharge amount E _SSB req is the energy discharged from the stationary storage battery SSB to charge the EV bus between the arrival time of the arrival point Ta and the arrival time of the candidate departure point Td. It can be obtained by the following formula.

In the above equation, Ereq is the required energy of the operation schedule, EVlow is the lower limit value of the remaining electric energy of the EV bus, EVrem is an estimated value of the remaining electric energy of the EV bus at the arrival point Ta, and Eg is the arrival calculated in step S405. This is the energy available from the grid between the arrival time at the point Ta and the departure time at the candidate departure point Td. The calculated required discharge amount E _SSB req is stored in the stationary storage battery information means 141.

Next, the calculation process of the remaining power amount E _SSB (kWh) of the stationary storage battery SSB in step S408 of the determination process will be described with reference to FIG. FIG. 26 is a flowchart showing a calculation process of the remaining power amount E _SSB of the storage battery SSB.

  First, the stationary storage battery information of the stationary storage battery SSB, the system supply power P (t), the sampling interval s (sec), and the like are acquired (step S501). The grid supply power P (t) is the grid supply power used in the above determination process. The sampling interval s can be set arbitrarily. The arrival time at the arrival point Tap is set as the start time ts, and the arrival time at the arrival point Ta is set as the end time te.

Next, the total (Ereqtotal) of the required discharge amount E _SSB req of the stationary storage battery SSB from the start time ts to the end time te is calculated. Ereqtotal can be calculated by obtaining the required discharge amount E _SSB req calculated in step S415 described above from the stationary storage battery information unit 141.

Then, the amount of power remaining stationary battery SSB at start time ts is set to E _SSB, to set the time variable t to start time ts (Step S503). The remaining power amount of the stationary storage battery SSB at the start time ts can be acquired from, for example, stationary storage battery information.

Next, charging power P _SSB (t) to stationary storage battery SSB at each sampling interval is calculated, and charging to stationary storage battery SSB at each sampling interval is performed based on charging power P _SSB (t) (kW). The electric energy E (t) (kWh) is calculated (step S504), and E _SSB (kWh) is updated (step S505). The charging power P _SSB (t), the charging power amount E (t), and E _SSB can be calculated as follows (step S506).

As described above, the charging power P _SSB (t) to the stationary storage battery SSB is equal to or less than the maximum charging rate of the stationary storage battery SSB, and the charging power amount E _SSB of the stationary storage battery _SSB is the remaining power amount of the stationary storage battery _SSB. Below the upper limit. By providing such a restriction, deterioration of the stationary storage battery can be suppressed.

The remaining power amount _ESSB is updated until the time variable t becomes larger than the end time te (YES in step S504) or _ESSB becomes equal to or greater than the upper limit value of the remaining power amount of the stationary storage battery SSB (YES in step S507). The process is repeated every sampling interval (step S508), and if any of the conditions is satisfied, E _SSB -Ereqtotal is returned, and the process proceeds to step S409 of the determination process (step S509). At step S409, the as E _SSB for computing the energy available Eavail, above E _SSB -Ereqtotal it is used.

  Next, the calculation of the charging power amount in step 10512 of the evaluation process will be described with reference to FIG. FIG. 27 is a flowchart showing a calculation process of the amount of charging power at the arrival point Ta.

First, the arrival point Ta, the candidate departure point Td, the required energy Ereq of the operation schedule at the candidate departure point Td, the EV bus remaining electric energy EVrem, the EV bus remaining electric energy lower limit EVlow, the EV bus remaining electric energy upper limit EVhigh The EV bus maximum charging rate P _EV (t), the energy Eavail available at the arrival point Ta, the sampling interval s (sec), and the like are acquired (step S601). Each vehicle information described above is EV bus vehicle information assigned to the arrival point Ta. The sampling interval s can be set arbitrarily.

  Next, the arrival time at the arrival point Ta is set as the start time ts, the departure time at the candidate departure point Td is set as the end time te (step S602), and the EV bus is charged from the start time ts to the end time te. A possible electric energy Einmax (kWh) is calculated (step S603). The electric energy Einmax is an electric energy that can be charged to the EV bus when charging is performed at the maximum charging rate from the start time ts to the end time te. The electric energy Einmax can be calculated by the following equation.

  The required energy Ereq of the operation schedule at the candidate departure point Td obtained in the above steps, the energy Eavail that can be used at the arrival point Ta, the EV bus remaining power upper limit EVhigh, and the EV bus remaining power amount at the arrival point Ta (Estimated value) Based on EVrem and the maximum electric energy Einmax that can be charged to the EV bus, the charging electric energy is calculated as follows (step S604).

  The charging power amount calculated by the above equation is the amount of power that can be charged to the EV bus at the arrival point Ta from the start time ts to the end time te at a charging rate equal to or lower than the maximum charging rate of the EV bus. In addition, by charging this charging power amount to the EV bus, the remaining power amount of the EV bus can be smaller than the lower limit value EVlow of the remaining power amount even if the route defined by the operation schedule at the candidate departure point Td is operated. The nature is low. Furthermore, even if this charging power amount is charged, the remaining power amount of the EV bus does not exceed the upper limit value of the remaining power amount. A charge list is created on the basis of the calculated charging power amount.

  As described above, according to the present embodiment, charging is possible at the charging base, that is, it is possible to calculate the charging power amount in consideration of the charging load at the charging base. In addition, it is possible to calculate the amount of charging power with a low possibility of running out of electric power in consideration of the remaining amount of electric power of the EV bus. Furthermore, it is possible to calculate the charging power amount in consideration of the upper and lower limit values of the remaining power amount preset in the EV bus, the maximum charging rate, and the like. The upper and lower limits and the maximum charge / discharge rate of the remaining electric energy are battery life-related parameters that are set to suppress the deterioration of the storage battery of the EV bus and extend the life, and charging that takes these battery life-related parameters into consideration By charging the amount of electric power, deterioration of the storage battery of the EV bus can be suppressed and the life of the storage battery can be extended.

Next, the update of the system power supply P _{i, 1} (t), P _{i, 2} (t) in step S10513 of the evaluation process will be described with reference to FIGS. FIG. 28 is a flowchart illustrating a system power supply update process. This update is a temporary update for the evaluation process of each candidate solution and the calculation of the amount of charging power, and is reset to the actual system power supply every time the evaluation process of each candidate solution is completed. . That is, this update is effective only while the same candidate solution evaluation process is being performed.

First, an arrival point Ta, a candidate departure point Td, a system supply power level, a system supply power P _{i, 1} (t), P _{i, 2} (t), a sampling interval s (sec), and the like are acquired (step S701). . The sampling interval s can be set arbitrarily.

  Next, the arrival time of the arrival point Ta is set as the start time ts, the departure time of the candidate departure point Td is set as the end time te (step S702), and the grid power supply P (t) is set (step S703). S705). The grid power supply P (t) set here is the grid power P (t) used when it is determined that charging is possible in step S416 in the above-described determination process (see FIG. 25). Based on the set grid supply power P (t), a grid supply power amount Eg is calculated (step S706). The calculation method of the grid power supply amount Eg is the same as that in step S405.

  Next, the grid power supply amount Eg is compared with the charge power amount calculated in step 10512 of the evaluation process (step S707). When the grid supply power amount Eg is equal to or less than the charge power amount (NO in step S707), The system power supply P (t) after charging is set to 0 (step S709), the system power supply P (t) is updated (step S714), and the process proceeds to the process for updating the remaining power amount of the stationary storage battery. Since the grid supply power P (t) is preferentially used for charging the EV bus, when the grid supply power Eg is less than or equal to the charge power, all the grid supply power Eg is charged to the EV bus and charged. The shortage of the electric energy is charged from the remaining electric energy of the stationary storage battery.

  When the grid power supply amount Eg is larger than the charging power amount (YES in step S707), the charging power amount calculated in step 10512 of the evaluation process is set as the power amount E (step S708), and the average required charging power Pc (t ) Is calculated (step S710). The average required charging power Pc (t) is used to charge the EV bus with charging energy from the start time ts (arrival time of the arrival point Ta) to the end time te (departure time of the candidate departure point Td). Average power supplied by the grid. In FIG. 29 (a), the charging power amount is the area of the portion surrounded by the thick line. The average required charging power Pc (t) can be calculated by the following equation.

  Next, an insufficient power amount Einsuff is calculated (step S711). The insufficient power amount Einsuff is a power amount that is insufficient when charging with the average required charging power Pc (t) because the grid supply power P (t) is lower than the average required charging power Pc (t). In FIG. 29A, the insufficient power amount Einsuff is the area of the shaded portion on the left side. The insufficient electric energy Einsuff can be calculated by the following equation.

  Further, the surplus power amount Esurplus is calculated (step S712). The surplus power amount Esurplus is a surplus power amount when charging with the average required charging power Pc (t) because the grid supply power P (t) is higher than the average required charging power Pc (t). In FIG. 29A, the surplus power amount Esurplus is the area of the hatched portion on the right side. The surplus power amount Esurplus can be calculated by the following equation.

  Next, based on the calculated insufficient power amount Einsuff and surplus power amount Esurplus, the system supply power P (t) ′ from the start time ts to the end time te after charging the EV bus with the charged power amount is calculated. (Step S713). The grid power supply amount P (t) ′ can be calculated by the following equation.

  As shown in FIG. 29 (c), it is assumed that all the grid supply power P (t) is used in the time range where the grid supply power P (t) is equal to or less than the average required charge power Pc (t). P (t) ′ after charging is calculated as 0 (kw). On the other hand, in a time range in which the grid supply power P (t) is greater than the average required charge power Pc (t), the grid supply power P (t) ′ after charging is (P (t) −Pc (t)) × (1 -Einsuff / Esurplus). That is, as shown in FIG. 29B, the grid supply power P (t) ′ is calculated as the power remaining after charging the insufficient power amount Einsuff from the surplus power amount Esurplus.

  Finally, the grid supply power P (t) is updated to the calculated grid supply power P (t) ′ (step S714), and the process proceeds to a process for updating the remaining power amount of the stationary storage battery. The updated grid power supply amount P (t) is the grid power supply power P (t) in the time range from the start time ts to the end time te of the power level set in steps S703 to S705.

  Next, the update of the remaining power amount of the stationary storage battery in step S10513 of the evaluation process will be described with reference to FIG. FIG. 30 is a flowchart showing a process for updating the remaining power amount of the stationary storage battery. This update is a temporary update for the evaluation process of each candidate solution and the calculation of the charging power amount, and is reset to the actual remaining power amount every time the evaluation process of each candidate solution is completed. . That is, this update is effective only while the same candidate solution evaluation process is being performed.

First, an arrival point Ta, a departure point Td, an arrival point list, stationary storage battery information, system supply power P _{i, 1} (t), a required discharge amount E _SSB req from the stationary storage battery SSB, and the like are acquired (step S801). ).

Next, using the node ID of the arrival point Ta, the stationary storage battery information of the stationary storage battery SSB that can be used at the arrival point Ta is acquired from the stationary storage battery information (step S802), and immediately before the arrival point Ta from the arrival point list. Arrival point Tap is extracted (step S803), and the stationary storage battery SSB is charged with the power supply of power level 1 from the arrival time of the arrival point Tap to the arrival time of the arrival point Ta. The remaining electric energy E _SSB (kWh) of the stationary storage battery SSB that can be used with Ta is calculated (step S804). The above steps S802 to S804 are the same as the above-described steps S406 to S408.

Next, the remaining electric energy E _{SSB, Td} of the stationary storage battery SSB at the departure time of the candidate departure point _Td is calculated (step S805). E _{SSB, Td} can be calculated by subtracting the required discharge amount E _SSB req from the remaining power amount E _SSB . After calculating E _{SSB, Td} , all required discharge amounts E _SSB req of the stationary storage battery SSB from the arrival time of the arrival point Tap to the arrival time of the arrival point Ta stored in the stationary storage battery information means 141 are set to 0. (Step S806). Then, the remaining power amount E _SSB of the stationary storage battery SSB at the departure time of the candidate departure point _Td is updated to the remaining power amount E _{SSB, Td} calculated in step S805 (step S807). If the residual power amount E _SSB stationary storage batteries SSB is updated, the process proceeds to step S10506 evaluation process.

  As described above, according to the operation management apparatus according to the present embodiment, vehicle allocation and charge energy calculation are performed so that the remaining power amount of the EV bus (electric vehicle) in operation is larger than the lower limit value of the remaining power amount. In order to do so, it is possible to formulate an operation plan in which a plurality of EV buses operate without causing electric shortage. In addition, the operation plan should be designed to comply with restrictions on the amount of power that can be used at the charging base (such as the amount of power that can be used from the grid and the remaining power of stationary storage batteries) and the charging load (such as grid power supply). be able to. Thereby, dispersion | distribution and peak shift of the charging load in each charging base are attained. Moreover, since the amount of electric power charged to the EV bus is calculated based on the battery life-related parameters, it is possible to suppress the deterioration of the storage battery mounted on the EV bus and extend the battery life.

(Second Embodiment)
Hereinafter, a second embodiment of the present invention will be described with reference to FIGS. Here, FIG. 31 is a flowchart showing the operation plan planning process of the second embodiment. In the second embodiment, the operation planning means 10 creates a candidate solution using a genetic algorithm (GA) (step S903). Assignment of vehicles to the created candidate solutions (steps S901 and 904), evaluation of charge feasibility (steps S901 and 904), determination of termination conditions (step S902), and selection of candidate solutions with good evaluation (step S906) Can be implemented in the same manner as in the first embodiment.

  First, the operation plan creation means 10 creates a plurality of connection method candidate solutions (step S901). Candidate solutions are created randomly under the constraint that candidate departure points other than -1 (no connection) can only be selected once. FIG. 32 is a diagram illustrating an example of a candidate solution list. FIG. 32A shows a candidate solution list including a plurality of candidate solutions created in step S901, and includes N candidate solutions (hereinafter referred to as “N candidate solutions”). In step S901, the operation plan planning means 10 assigns an EV bus to the N candidate solutions, and performs a charge feasibility evaluation process on the candidate solutions to which the EV bus is assigned. The EV bus allocation and the charge feasibility evaluation process can be performed by the same method as in the first embodiment. Therefore, the determination process of charge feasibility, the calculation of the charge power amount, the update of the grid supply power P (t), and the update of the remaining power amount of the stationary storage battery can be performed. As shown in FIG. 32A, the charge feasibility score and the number of assigned EV buses can be used as the evaluation value of the candidate solution.

  Next, it is determined whether the N candidate solution satisfies the end condition (step S902). If the end condition is satisfied (YES in step S902), the candidate solution having the best evaluation value among the N candidate solutions is selected. Then, the candidate solution and the vehicle allocation list and charging power amount list created for the candidate solution are output (step S906). If the termination condition is not satisfied (NO in step S902), the genetic algorithm selection, crossover, and mutation operations are applied M / 2 times (M is an even number) to the above-mentioned N candidate solutions, and a new M candidate solutions (hereinafter referred to as “M candidate solutions”) are created (step S903).

  Here, a method for creating an M candidate solution will be described. First, two candidate solutions are selected from the N candidate solutions created in step S901 according to the evaluation value. The method for selecting a candidate solution is arbitrary. For example, roulette selection for selecting a candidate solution based on a selection probability calculated according to the evaluation value can be used. Also, ranking selection for selecting candidate solutions based on a selection probability set in advance according to the ranking of evaluation values, tournament selection for selecting candidate solutions with the best evaluation value from a subset of randomly selected N candidate solutions, etc. This method can also be used. Here, it is assumed that candidate solutions 2 and 3 in FIG.

  Next, as shown in FIG. 33A, for the two selected candidate solutions 2 and 3, one crossing point is randomly set at an arbitrary position within the length of the candidate solution (one-point crossing). ). Then, crossover operation is performed on the candidate solutions 2 and 3 before and after the crossover point, and new candidate solutions 2 and 3 are created. The crossover operation refers to exchanging portions of two selected candidate solutions before or after the crossover point. Thus, as shown in FIG. 33 (b), a new candidate solution (new candidate solution 2) consisting of a portion on the front side of the intersection point of the candidate solution 2 and a portion on the rear side of the intersection point of the candidate point 3; A new candidate solution (new candidate solution 3) composed of a portion after the crossing point of candidate solution 2 and a portion before the crossing point of candidate point 3 is created. Such a crossover operation is applied with a crossover probability Pc. Note that the crossover operation is not limited to one-point crossover as described above, but two-point crossover for setting two crosspoints, multipoint crossover for setting three or more crosspoints, or independent for each candidate start point included in the candidate solution. Thus, uniform crossover that changes with a predetermined probability may be used.

  Further, the mutation operation is applied with the mutation probability Pm to the two new candidate solutions created in this way. The mutation operation refers to selecting one arbitrary position within the length of the candidate solution and randomly changing the candidate starting point at the selected position to another candidate starting point. FIG. 33 (c) shows two new candidate solutions created by applying the mutation operation to the new candidate solution 2.

  By repeating the above operation M / 2 times, M new candidate solutions (M candidate solutions) are created. Then, an EV bus is assigned to this M candidate solution, and charging feasibility is evaluated (step S904). Then, N candidate solutions having good evaluation values are selected from the N candidate solutions and the M candidate solutions to create a new N candidate solution (step S905), and whether or not the new N candidate solution satisfies the termination condition. Determination is made (step S902). FIG. 32B is a candidate solution list showing new N candidate solutions. As shown in FIG. 32B, the new N candidate solutions include a candidate solution included in the original N candidate solution and a candidate solution included in the newly created M candidate solution.

  As described above, according to the second embodiment, a candidate solution having a good evaluation value is searched using a genetic algorithm. Therefore, it is possible to efficiently find a good candidate solution in a short time.

  In this embodiment, when a new candidate solution is created by a crossover operation or a mutation operation, candidate candidate points other than -1 (no connection) are selected only once from the same candidate solution. There may be a restriction that you cannot. In this case, new candidate solutions are randomly generated within a range that satisfies the constraint. Alternatively, after such a restriction is not imposed and a new candidate solution is randomly created, it may be determined that the created new candidate solution is a candidate solution that satisfies the restriction. In this case, the candidate solution determined not to satisfy the restriction is excluded from the M candidate solutions. Further, a configuration in which only one of the crossover operation and the mutation operation is performed is also possible.

(Third embodiment)
Hereinafter, a third embodiment of the present invention will be described with reference to FIGS. 34 to 38. First, an outline of the operation plan planning method will be described with reference to FIG. Here, FIG. 34 is a schematic diagram for explaining an operation planning method.

  In this embodiment, based on the basic diagram, an arrival point list in which the arrival points of each operation diagram are arranged in ascending order of arrival times is selected, the arrival points are selected in the order of the generated arrival point list, and the departure point and Connect. That is, the arrival point and the departure point are connected in ascending order of arrival time at the arrival point. If no vehicle is assigned to an operation schedule whose departure time is earlier than the arrival time of the selected arrival point, an EV bus is assigned to the operation diagram.

  For example, in the case of the basic diagram shown in FIG. 34 (a), an arrival point list in which arrival points are arranged in the order of arrival points 1, 2, 3, 4 as shown in FIG. 34 (b) is created. Arrival point 1 is selected. The operation diagrams 1 and 2 are operation diagrams whose departure time is earlier than the arrival time of the selected arrival point 1, and no vehicle assignment is performed. Therefore, an EV bus is assigned to the operation schedules 1 and 2. In FIG. 34 (c), the EV bus 1 is assigned to the service diagram 1, and the EV bus 4 is assigned to the service diagram 2.

  Next, the nearest candidate departure point is connected to the selected arrival point. Departure points that can be connected to the arrival point are only departure points that are located at the same stop position as the arrival point and whose departure time is after the arrival time of the arrival point. The candidate departure point closest to the arrival point is a candidate departure point whose departure time is closest to the arrival time of the arrival points among candidate departure points that satisfy the above conditions.

  Next, the feasibility of charging with a predetermined amount of electric power is determined at a charging point between the connected service schedules. If charging is possible, the amount of charging power at the charging point is calculated. If charging is impossible, the connection between the arrival point and the candidate departure point is stopped, and it is determined whether the candidate departure point can be connected to another arrival point. If the candidate departure point cannot be connected to another arrival point, another EV bus that can be assigned to the candidate departure point is assigned. If there is no other EV bus that can be assigned to the candidate departure point, a non-electric vehicle registered in the operation management device may be assigned. If there is neither an assignable EV bus nor a non-electric vehicle, the departure time of the candidate departure point is delayed (shifted), and the connection is reestablished with the arrival point where the connection is stopped, and the charging feasibility is determined.

  In FIG. 34 (c), since the nearest candidate departure point of arrival point 1 is departure point 4, arrival point 1 and candidate departure point 4 are connected, and charging feasibility at the charging point is determined. As shown in FIG. 34 (d), when charging is possible, the amount of charging power at the charging point is calculated. If charging is impossible, the connection between the arrival point 1 and the departure point 4 is stopped. Since there is no arrival point that can be connected to the departure point 4, the EV bus 3 that can be assigned to the bus schedule 4 is assigned.

  When the processing for the first arrival point in the arrival point list is completed, the next arrival point in the arrival point list is selected, and the same processing is repeated. Thereby, a vehicle allocation list and a charge list are created. That is, in this embodiment, vehicle allocation and operation schedule connection are performed in parallel.

Next, with reference to FIG. 35, the operation plan planning process of this embodiment is demonstrated in detail. FIG. 35 is a flowchart illustrating an operation plan planning process according to the third embodiment. First, the operation planning means 10 acquires information such as basic schedule, vehicle information, route information, charging facility information, vehicle allocation list, and charging list (step S2001), and each operation schedule defined by the basic schedule is acquired. The required energy is calculated and a required energy list is created (step S2002), an allocatable EV list is created (step S2003), a candidate starting point list is created (step S2004), and the power supply power of power levels 1 and 2 is supplied. P _{i, 1} (t) and P _{i, 2} (t) are calculated (step S2005). Each of the above steps can be performed by the same method as described in the first embodiment.

  Next, an arrival point list in which arrival points are arranged based on the ascending order of arrival times is created, and arrival points Ta are acquired in the order of the created arrival point list (ascending order of arrival times) (step S2006). If an operation schedule whose departure time is earlier than the arrival time of the arrival point Ta is acquired and no vehicle is assigned to the operation schedule, it is determined whether the vehicle can be assigned to the operation diagram (step S2007). ).

  If vehicle allocation is not possible (NO in step S2007), the operation plan is unsuccessful, and the operation plan planning process ends (step S2008). The case where vehicle assignment is impossible in step S2007 is a case where the EV bus cannot be assigned to the departure points 1 and 2 with arrival point 1 selected in FIG. 34 (c). For example, when no EV bus stops at the charging base A, the EV bus cannot be assigned to the departure point 1. In such a case, the operation plan cannot be made unless the basic diagram is changed or an assignable EV bus is added, so that the operation plan is unsuccessful. However, when re-planning the operation plan, the number of EV buses that can be allocated changes by shifting the arrival time and departure time of the operation schedule, and it may become possible to create an operation plan. The planning process may continue.

  On the other hand, if vehicle assignment is possible (YES in step S2007), vehicle assignment is performed to the departure point, and the vehicle assignment list is updated (step S2009). FIG. 36 shows an example of a vehicle assignment list. Each time an EV bus is assigned to an operation schedule, records are added and the list is updated. In addition, the method demonstrated in 1st Embodiment can be utilized for the vehicle allocation to the starting point in step S2007. That is, it is possible to calculate the maximum required charging power amount based on the required energy of the starting timetable and assign an EV bus having a larger effective capacity than the maximum required charging power amount.

  Next, it is determined whether or not an end condition is satisfied (step S2010). The termination condition is, for example, when the acquired arrival point Ta is the last arrival point in the arrival point list. If the end condition is satisfied (YES in step S2010), the charging list and the vehicle allocation list are output, and the operation plan planning process is ended (step S2012). On the other hand, if the end condition is not satisfied (NO in step S2010), the candidate departure point Td is extracted from the candidate departure point list with respect to the arrival point Ta based on the ascending order of the departure time (step S2011). In this embodiment, only the candidate departure point Td closest to the arrival point Ta can be connected to the arrival point Ta.

When there is no candidate departure point Td (NO in step S2013), the operation planning process returns to step S2006, and the next arrival point Ta is acquired from the arrival point list. If there is a candidate departure point Td (YES in step S2013), it is determined whether a predetermined amount of power can be charged between the arrival point Ta and the candidate departure point Td (step S2014). The determination of the feasibility of charging can be performed by the same method as in the first embodiment. That is, the system supply power Eg supplied from the system between the arrival time of the arrival point Ta and the departure time of the candidate departure point Td and the remaining power amount E _SSB of the stationary storage battery are calculated and summed up. The energy Eavail available at the arrival point Ta is calculated. Then, by comparing the energy Eavail, the remaining electric energy (estimated value) EVrem of the EV bus, the remaining electric energy lower limit EVlow of the EV bus, and the required energy Ereq of the operation schedule at the candidate departure point Td, It is possible to determine the feasibility of charging between the arrival point Ta and the candidate departure point Td.

  If charging is possible (YES in step S2014), the amount of charging power charged between the arrival point Ta and the candidate departure point Td is calculated (step S2018). The charge power amount can be calculated by the same method as in the first embodiment. That is, the required energy Ereq of the operation schedule at the candidate departure point Td, the energy Eavail that can be used at the arrival point Ta, the EV bus remaining power upper limit EVhigh, and the EV bus remaining energy (estimated value) EVrem at the arrival point Ta , And the maximum electric energy Einmax that can be charged to the EV bus, the electric energy charged between the arrival point Ta and the candidate departure point Td can be calculated.

  Next, the system supply power and the remaining power amount of the stationary storage battery are updated (step S2019). The update of the system supply power can be performed by the same method as described in the first embodiment. That is, first, the grid supply power amount Eg is calculated based on the grid supply power P (t). Next, the grid power supply amount Eg is compared with the charge power amount calculated in step S2018. When the grid supply power amount Eg is equal to or less than the charge power amount, the grid supply power P (t) is updated to zero. When the grid power supply amount Eg is larger than the charging power amount, the average required charging power Pc (t) is calculated, and the insufficient power amount Einsuff and the surplus power amount Esurplus are calculated based on the average required charging power Pc (t). . Then, the grid supply power P (t) in the time range where the grid supply power P (t) is equal to or less than the average required charge power Pc (t) is updated to 0, and the grid supply power P (t) is updated to the average required charge power Pc ( The grid power supply P (t) in the time range larger than t) is updated to a value calculated based on the insufficient power amount Einsuff and the surplus power amount Esurplus.

Moreover, the update of the residual electric energy of a stationary storage battery can also be implemented by the same method as described in the first embodiment. That is, first, the required discharge amount E _SSB req from the stationary storage battery SSB that can be used at the arrival point Ta and the remaining power amount E _SSB of the stationary storage battery SSB are calculated. Next, it is determined whether a request discharge amount E _SSB req, if there is no request discharge amount E _SSB req updates the remaining power amount in the residual power amount E _SSB, when there is a request discharge amount E _SSB req Updates the remaining power amount to the remaining power amount E _{SSB −the} required discharge amount E _SSB req.

  Finally, the vehicle allocation list and the charge list are updated (step S2020), and the operation plan planning process returns to step 2006. The charging list update method will be described later.

If it is determined in step S2014 that a predetermined amount of power cannot be charged between the arrival point Ta and the candidate departure point Td (NO in step S2014), in addition to the arrival point Ta currently being processed, candidates It is determined whether there is an arrival point Ta ′ that can be connected to the departure point Td (step S2015). The arrival point Ta ′ is an arrival point that satisfies all of the following conditions.
Condition 1. 1. Arrival time of arrival point Ta ≦ arrival time of arrival point Ta ′ ≦ departure time condition of candidate departure point Td Node ID of arrival point Ta = node ID of arrival point Ta ′

  If there is an arrival point Ta ′ that satisfies the above conditions (YES in step S2015), the operation plan planning process returns to step S2006 to acquire the next arrival point Ta from the arrival point list. On the other hand, if there is no arrival point Ta ′ (NO in step S2015), it is determined whether or not a vehicle can be assigned to the candidate departure point Td (step S2016). If the vehicle assignment to the candidate departure point Td is possible (YES in step S2016), the EV bus is assigned to the candidate departure point Td and the vehicle assignment list is updated. Thereafter, the operation planning process returns to step S2006, and the next arrival point Ta is acquired from the arrival point list. If there is a non-electric vehicle that can be assigned to the candidate departure point Td in step S2016, a non-electric vehicle may be assigned.

  On the other hand, if vehicle allocation to the candidate departure point Td is impossible (NO in step S2016), the candidate departure point Td is set so that a predetermined amount of power can be charged between the arrival point Ta and the candidate departure point Td. The departure time is delayed (step S2017). The process of delaying the departure time of the candidate departure point Td will be described later.

  In step S2017, after delaying the departure time of the candidate departure point Td, the operation planning process proceeds to step S2019, and the charging power charged between the arrival time of the arrival point Ta and the new departure time of the candidate departure point Td. Calculate the quantity.

  Next, the charging list update method in step S2020 will be described. FIG. 37A is a flowchart showing a charging list update method. First, the arrival point Ta, the candidate departure point Td, the arrival point Ta ′ of the operation schedule at the candidate departure point Td, the vehicle ID of the EV bus assigned to the arrival point Ta, etc. are acquired (step S2101). Next, a new charge record is created (step S2102), and a value is set in each field of the charge record (step S2013). The fields are vehicle ID, node ID, estimated arrival time, estimated departure time, expected remaining power amount at arrival, target remaining power amount, and the like. Values can be set for these fields as follows. it can.

Vehicle ID = Vehicle ID assigned to arrival point Ta
Node ID = node ID of arrival point Ta
Expected arrival time = arrival time of arrival point Ta Expected departure time = departure time of candidate departure point Td Expected remaining power amount at arrival (kWh) = Remaining energy amount of allocated EV at arrival point Ta (kWh)
Target remaining energy (kWh) = Expected remaining energy upon arrival (kWh) + Charged energy (kWh)

  When values are set in the fields of the new record, the new record is added to the charge list (step S2014), and the charge list is updated. FIG. 37B is a diagram showing an example of the charge list.

  Next, the delay process of the departure time of the candidate departure point Td in step S2017 will be described. FIG. 38 is a flowchart showing a delay process of the departure time of the candidate departure point Td. First, the arrival point Ta, the candidate departure point Td, the required energy Ereq of the operation schedule at the candidate departure point Td, the energy Eavail that can be used at the charging base, the remaining electric energy EVrem at the arrival at the arrival point Ta, and the remaining battery of the EV bus The electric energy lower limit EVlow, the sampling interval s (sec), and the like are acquired (step S3101). The sampling interval s can be set arbitrarily.

  Next, the arrival time at the arrival point Ta is set as the time ta, and the departure time at the candidate departure point Td is set as the time td (step S3102). Then, the energy Eneed (kWh) that is insufficient with respect to the predetermined amount of power charged between the arrival point Ta and the candidate departure point Td is calculated (step S3103). The insufficient energy Eneed can be calculated by the following formula.

Next, a time tdc at which the insufficient energy Eneed can be charged is searched using the power supply power P _{i, 1} (t) at the power level 1. That is, the time tdc means that when charging is performed with the grid supply power P _{i, 1} (t) from the time ta, charging of a predetermined amount of power charged between the arrival point Ta and the candidate departure point Td is completed. Time tdc> time td.

The search for time tdc will be described. First, time td is set as time tdc, and energy E (kWh) supplied from system supply power P _{i, 1} (t) from time td to time tdc is set to 0 (step S31041). Next, the time tdc is updated by adding one minute (step S31042). The time added to the time tdc can be set arbitrarily. And the energy E supplied from a system | strain is calculated with the following formula | equation (step S31043).

  The calculated energy E and the deficient energy Eneed are compared (step S31044). If the energy E is smaller than the deficient energy Eneed (NO in step S31044), the process returns to step S31042 to update the time tdc and the energy E is deficient energy. If it is equal to or greater than Eneed (YES in step S31044), tdc is returned (step S31045), and the process proceeds to step S3105.

  Then, the arrival time tai and departure time tdci of the EV bus at each node on the operation schedule of the candidate departure point Td are calculated and updated by the following formula (step S3105).

  That is, the arrival time and the departure time determined by the basic diagram of each node on the operation diagram are delayed by tdc-td. As a result, the entire service schedule moves backward by tdc-td. At this time, the departure time of the candidate departure point Td is also delayed by tdc-td, and a new departure time is set. The new route information changed in this way is returned (step S3106), and based on the new route information (departure time and arrival time), calculation of the charging power amount in step S2018 is performed.

(Fourth embodiment)
Hereinafter, a fourth embodiment of the present invention will be described with reference to FIGS. 39 to 42. The operation management apparatus according to the present embodiment detects a dynamic factor such as energy available at a charging base and an operation state, and reschedules the operation plan. Whether or not to execute the replanning is determined by the replanning determination unit 16. The replan determination unit 16 determines replanning when a replan request is notified from the replan request unit 17 or at predetermined time intervals. When it is determined that the re-plan is to be executed, the operation plan planning unit 10 is instructed to perform the re-plan, and the operation plan planning unit 10 re-plans the operation plan after the time point when the re-plan is determined. For the re-planning determination by the re-planning determination means 16, the EV bus delay information and the remaining power amount during operation, the energy available at the charging base, the remaining power amount of the stationary storage battery, and the electricity cost and required between the stop positions Dynamic factors that change during EV bus operation, such as time, are used. Hereinafter, the re-planning determination process in the present embodiment will be described with reference to FIG.

  First, the replan determination unit 16 acquires the current time t, the previous replan determination time tprev, the parameter αprev, and the like (step S4001). When the first replan determination is performed, the replan determination time tprev is a null value. The parameter αprev is a safety parameter for calculating the required energy of the operation diagram set at the time of the previous operation planning or re-planning.

  Next, it is determined whether or not a re-planning request is notified from the re-planning request unit 17 (step S4002). The information included in the replanning request notified by the replanning requesting unit 17 differs depending on the cause of the replanning request. For example, in the re-planning request notified when the charging power to the EV bus at the charging base exceeds the contract power, information such as the node ID of the charging base, the power level at which charging was performed, and the contract deviation power included. Contract deviation power refers to the portion of the charging power at the charging base that exceeds the contract power. The re-planning request notified in the case of a delay of the EV bus includes information such as the node ID of each stop position where the delayed EV bus operates, the vehicle ID of the delayed EV bus, and the delay time for the operation plan. included.

  Hereinafter, the case where the replanning request is not notified in step S4002 (NO in step S4002) will be described first, and then the case where the replanning request is notified (YES in step S4002) will be described.

  When the replanning request is not notified in step S4002, the replanning determination unit 16 determines whether or not a predetermined time has elapsed from the time tprev at which the previous replanning determination was performed (step S4003). If the predetermined time has not elapsed since the replan determination time tprev (NO in step S4003), the replan flag is set to false (step S4013), and the replan determination unit ends the replan determination process (step S4021). ).

  When the predetermined time has elapsed from the replanning determination time tprev (YES in step S4003), the replanning determination unit 16 acquires vehicle information (step S4004), and the latest position time of each EV bus is the operation plan. It is determined whether or not it is later than the scheduled time (step S4005). Specifically, the latest position time of the EV bus acquired from the vehicle information is compared with the estimated arrival time of the current position of the EV bus in the vehicle allocation plan to determine whether or not a delay has occurred.

  If a delay has occurred (YES in step S4005), it is determined whether or not the delay time is greater than the threshold (step S4016). If no delay has occurred (NO in step S4005), It is determined whether or not the remaining amount of electric power of the EV bus at the arrival charging base has decreased (step S4006). The determination (step S4006) of whether or not the remaining electric energy of the EV bus has decreased will be described in detail later.

  If it is determined in step S4006 that the remaining power amount is decreasing (YES in step S4006), it is determined whether charging is possible at the charging station where the EV bus arrives next (step S4017). Details of the determination of the feasibility of charging at the next charging base (step S4017) will be described later.

  If it is determined in step S4006 that the remaining power amount has not decreased (NO in step S4006), energy information that can be used at each charging site is acquired (step S4007), and there is a change in the available energy information. It is determined whether or not (step S4008). For example, when DR is issued from the grid, available energy information may be changed. If there is a change in the available energy information (YES in step S4008), the replanning flag is set to true (step S4019), and the replanning determination unit 16 re-plans the operation plan in the operation plan planning unit 10. (Step S4020), and the re-planning determination process ends (step S4021). The operation plan planning means 10 executes the re-planning of the operation plan with respect to each arrival point after the re-plan determination time.

  When there is no change in the available energy information (NO in step S4008), the re-planning determination unit 16 acquires stationary storage battery information (step S4009), and the stationary type at the charging base where each EV bus has passed most recently. It is determined whether or not the remaining power amount of the storage battery is lower than the expected remaining power amount based on the current operation plan (step S4010). If it is determined that the remaining power amount of the stationary storage battery is decreasing (NO in step S4010), the re-planning flag is set to true (step S4019), and the re-planning determination unit 16 is the operation plan planning unit 10. Is instructed to re-plan the operation plan (step S4020), and the re-plan determination process is terminated (step S4021).

  In step S4010, when it is determined that the remaining power amount of the stationary storage battery has not decreased (YES in step S4010), the re-planning determination unit 16 acquires route information (step S4011), and between the stop positions. It is determined whether or not there is a change in at least one of the power consumption or the required time (step S4012). If there is a change in at least one of the electricity cost or the required time between the stop positions (YES in step S4012), the replanning flag is set to true (step S4019), and the replanning determination unit 16 sets the operation plan planning unit 10 to The re-planning of the operation plan is instructed (step S4020), and the re-planning determination process is ended (step S4021). If there is no change in either the power consumption between the stop positions or the required time (NO in step S4012), the replan flag is set to false (step S4013), and the replan determination unit 16 ends the replan determination process. (Step S4021).

  Next, a case where a replanning request is notified in step S4002 (YES in step S4002) will be described. Note that step S4016 described below is the same as the process performed when it is determined in step S4005 that a delay has occurred (YES in step S4005). Also, step S4017 described below is the same as the process performed when it is determined in step S4006 that the remaining amount of electric power on the EV bus is decreasing (YES in step S4006).

  If a replanning request is notified in step S4002 (YES in step S4002), the replanning determination unit 16 adjusts the parameter α used during replanning based on the acquired parameter αprev (step S4014). In step S4014, the parameter α is adjusted and the duplicate replanning request is eliminated. Details of the adjustment of the parameter α in step S4014 will be described later.

  Next, it is determined whether or not the charging power to the EV bus at the charging base exceeds the contract power, that is, whether or not there is contract deviation power (step S4015). If there is contract deviation power (YES in step S4015), the replanning flag is set to true (step S4019), and the replanning determination unit 16 instructs the operation planning unit 10 to replan the operation plan (step S4020). Then, the re-planning determination process is terminated (step S4021). The operation plan planning means 10 re-plans the operation plan using the parameter α adjusted in step S4014.

  If there is no contract departure power in step S4015 (NO in step S4015), it is determined whether or not the delay time is greater than the threshold (step S4016). If the delay time is equal to or less than the threshold (NO in step S4016), the replanning flag is set to false, and the replanning determination unit 16 ends the replanning determination process (step S4021). The delay time may frequently occur due to the influence of road conditions or the like, and if the re-plan is performed every time a slight delay time occurs, the operation plan is frequently re-planned, which is not preferable. However, the number of re-planning can be reduced by comparing the delay time with the threshold value and determining the re-planning.

  If the delay time is larger than the threshold value in step S4016 (YES in step S4016), the possibility of charging at the next charging site is determined (step S4017). In step S4017, the feasibility of charging at the charging base where the EV bus arrives next is determined. If charging is possible, the re-planning flag is set to true; otherwise, the re-planning flag is false. Set to When the replanning flag is set to true, the replanning determination unit 16 instructs the operation plan planning unit 10 to replan the operation plan (step S4020), and ends the replanning determination process (step S4021). The operation plan planning means 10 re-plans the operation plan using the parameter α adjusted in step S4014. If the replanning flag is false, the replanning determination unit 16 ends the replanning determination process (step S4021).

  Even when the re-planning request is not notified (NO in step S4002) and the re-planning determination process performed when a predetermined time has elapsed from the previous re-planning, the parameter α is adjusted. And re-planning may be performed using the adjusted parameter α. The parameter α adjustment method may be the same as in step S4014.

  Next, determination of whether or not the remaining amount of electric power of the EV bus at the next charging base in step S4006 has decreased will be described with reference to FIG. FIG. 40 is a flowchart showing a process of determining whether or not the remaining amount of electric power on the EV bus at the next charging base is decreasing.

  First, the operation information (node ID to pass next, distance to the next node to pass, latest SOC), parameter α used to calculate the required energy of the starting timetable, calculated at the time of planning the current operation plan The remaining electric energy Eplan at the next charging base, the remaining electric energy threshold β (%), and the like are acquired (step S5001).

  Next, the remaining electric energy Epred (kWh) of the EV bus at the next charging base where the EV bus arrives is estimated (step S5002). The remaining power Epred can be estimated by the method described in step S1027 described above. That is, the remaining power amount Epred can be estimated by subtracting the required energy from the latest position to the next charging base from the remaining power amount at the latest position.

  Next, the remaining power amount Epred and the remaining power amount Eplan are compared (step S5003). If the remaining power amount Epred is equal to or greater than the remaining power amount Eplan (YES in step S5003), the remaining power amount reduction flag is set to NO. (Step S5004), a remaining amount decrease flag is returned (step S5007). When the remaining amount decrease flag set to NO is returned, the re-planning determination process proceeds to step S4007.

  On the other hand, when the remaining power amount Epred is smaller than the remaining power amount Eplan (NO in step S5003), the difference between the remaining power amount Epred and the remaining power amount Eplan is compared with the remaining power amount threshold value β (step S5005). If (Eplan−Epred) / Eplan is less than or equal to the remaining power threshold value β (YES in step S5005), the remaining power amount decrease flag is set to NO (step S5004), and the remaining amount decrease flag is returned (step S5007). When the remaining amount decrease flag set to NO is returned, the re-planning determination process proceeds to step S4007.

  When (Eplan−Epred) / Eplan is greater than the remaining power threshold value β (NO in step S5005), the remaining amount decrease flag is set to YES (step S5006), and the remaining amount decrease flag is returned (step S5007). When the remaining amount reduction flag set to YES is returned, the re-planning determination process proceeds to step S4017.

  Here, a method for setting the remaining power threshold value β will be described. The remaining amount threshold β is (used parameter α−minimum value of parameter α) / used based on the preset minimum value of the parameter α and the value of the parameter α used when calculating the remaining power amount Eplan. It can be set by calculating the parameter α. For example, when the minimum value of the parameter α is set to 1.1 and the value of the used parameter α is 1.25, the remaining power threshold value β = 12% (= (1.25-1.1) / 1. 25). The remaining power amount threshold value β may be set in advance for each value of the parameter α to be used, or may be set anew for each re-planning determination process.

  The decrease in the remaining power amount Epred may frequently occur due to the influence of road conditions and the like, and it is not preferable to perform re-planning every time the remaining power amount Epred slightly decreases. However, the number of re-planning can be reduced by comparing the remaining power amount with the threshold and determining the re-planning.

  Next, determination of the feasibility of charging at the charging base where the EV bus arrives next in step S4017 will be described with reference to FIG. In the re-planning judgment process, if there is a delay in the EV bus, or if the remaining electric energy Epred of the EV bus is lower than the remaining electric energy Eplan predicted at the time of planning the operation, the next arrival Charging feasibility is determined at a point. FIG. 41 is a flowchart showing the determination process of the feasibility of charging at the charging base where the EV bus arrives next.

  First, a vehicle allocation plan, a charging plan, current position information, and the like are acquired (step S6001). Next, the next arrival point (charging base) of the EV bus is extracted from the vehicle allocation plan (step S6002), and the charging plan at the charging base is extracted from the acquired charging plan (step S6003). If there is no charging plan at the charging site, that is, the extracted charging plan is an empty value (YES in step S6004), the replanning flag is set to false (step S6005), and the replanning flag is returned (step S6009). When the re-planning flag set to false is returned, the re-planning determination process ends (step S4021). The case where there is no charging plan at the charging base is, for example, the case where the EV bus ends operation at the next charging base.

  If there is a charging plan at the next charging base (NO in step S6004), the arrival time of the next charging base and the remaining electric energy Epred at the next charging base are estimated (step S6006). Based on the charging plan at the charging base, the estimated arrival time, and the remaining electric energy Epred, the charging feasibility at the next charging base is determined (step S6007).

  If it is determined that charging is possible at the next charging base (YES in step S6007), the replanning flag is set to false (step S6005), and the replanning flag is returned (step S6009). When the re-planning flag set to false is returned, the re-planning determination process ends (step S4021).

  If it is determined that charging is not possible at the next charging base (NO in step S6007), the replanning flag is set to true (step S6008), and the replanning flag is returned (step S6009). When the replanning flag set to True is returned, the replanning determination unit 16 instructs the operation plan planning unit 10 to replan the operation plan (step S4020), and ends the replanning determination process (step S4021).

The determination of the feasibility of charging in step S6007 can be performed by the same method as in step S10510 described above. That is, the estimated arrival time of the next charging base is set as the start time ts, and the departure time from the next charging base scheduled in the vehicle allocation plan is set as the end time te (step S403). The power supply P (t) is set to the power supply power P _{i, 1} (t) at power level 1 (step S404), and the system is set between the start time ts and the end time te based on the set parameters. The grid power supply amount Eg (kWh) supplied from is calculated (step S405).

Further, the amount of power available from the stationary storage battery is calculated from the start time ts to the end time te (steps S406 to S408), and the grid power supply amount Eg (kWh) and the next charging base are provided. Based on the remaining electric energy E _SSB (kWh) of the stationary storage battery SSB, energy Eavail (kWh) that can be used from the start time ts to the end time te at the next charging base is calculated (step S409).

  Then, the remaining electric energy lower limit EVlow of the EV bus, the remaining electric energy (estimated value) Epred at the next charging base, the required energy Ereq of the operation schedule starting from the next charging base, and the energy Eavail available at the next charging base Based on the above, it is determined whether or not the predetermined charging power amount can be charged from the arrival time (estimated value) of the next charging base to the departure time (step S411). When Eavail + Epred−EVlow ≧ Ereq holds, it is determined that charging is possible, and when it does not hold, it is determined that charging is impossible.

  Next, the adjustment of the parameter α in step S4014 will be described with reference to FIG. In step S4014, the parameter α used for replanning is adjusted. FIG. 42 is a flowchart showing the adjustment process of the parameter α. First, the replan determination means 16 obtains the current time t, the previous replan determination time tprev, the parameter αprev used for the previous replan determination or operation plan, the default value αd of the parameter α, and the like (step S7001). ). The default value αd is set to be larger than 1, for example, 1.25.

  Next, the current time t is compared with the previous replan time tprev, and if it is determined that the current time t is different from the replan time tprev (NO in step S7002), it is determined that the request is a new replan request, and the parameters α is set to the default value αd (step S7003), the value of the set parameter α is returned (step S7007), and the re-planning determination process proceeds to step S4015.

  If it is determined in step S7002 that the current time t is equal to the replan time tprev (YES in step S7002), it is determined that the request is a duplicate replan request, and it is determined whether or not the previous parameter αprev is 1.0 ( Step S7004). In step S7002, when the elapsed time from the replan time tprev to the current time t is within a predetermined time, it is determined that the current time t is equal to the replan time tprev.

  In step S7004, if the parameter αprev is 1.0 (YES in step S7004), the value of the parameter α cannot be decreased any more, so the replan flag is set to false (step S7005), and the replan determination means. 16 finishes the re-planning process (step S4021).

  If the parameter αprev is not 1.0 in step S7004 (NO in step S7004), the parameter α is set to a value smaller than the parameter αprev (step S7006), the parameter α is returned (step S7007), and the re-planning determination process Advances to step S4015. The newly set parameter α is set in the range of αprev> α ≧ 1.0.

  As described above, the replan determination unit 16 gradually decreases the parameter α every time a duplicate replanning request is notified. Thereby, the operation plan based on the parameter α as large as possible can be re-planned.

(Fifth embodiment)
Hereinafter, the operation plan planning process according to the fifth embodiment of the present invention will be described with reference to FIGS. 43 and 44. Here, FIG. 43 is an example of a basic diagram to which the operation plan planning process of the fifth embodiment is applied, and FIG. 44 shows the required energy of the operation diagram whose arrival point is a non-charging node (non-charging base). It is a flowchart which shows a calculation process. In the basic diagram of FIG. 43, nodes A and C are charging bases, and node B is a non-charging node that cannot charge the EV bus. In this embodiment, when connecting the arrival point and the departure point of the operation diagram, if the arrival point of the operation diagram at the departure point is a non-charging node, the required energy from the non-charging node to the reachable charging point is considered. Then make an operation plan.

  In FIG. 43, when connecting the arrival point 11 and the departure point 32, the arrival point 32 of the service diagram 32 is located at the non-charging node B. In such a case, as the required energy of the operation diagram 32, the sum of the required energy of the operation diagram 32 and the required energy from the non-charging node B to the charging base A or the charging base C is calculated.

  Specifically, first, the required energy E1 (kWh) of the operation diagram 32 from the charging base C to the non-charging node B is calculated (step S8001). Next, the charging bases A and C that can arrive from the non-charging node B are acquired (step S8002), and the operation schedule to each charging base A and C is acquired (step S8003). The operation diagram acquired in step S8003 is an operation diagram that can be connected to the operation diagram 32 and whose arrival point is the charging base A or the charging base C. In the case of the basic diagram of FIG. 43, the operation diagram 23 and the operation diagram 24 are acquired.

  Next, the required energy to each charging base A, C, that is, the required energy of the operation diagram 23 and the operation diagram 24 acquired in step S8003 is calculated (step S8004). The maximum required energy E2 to each charging base E2 (KWh) is acquired (step S8005). The maximum value E2 of the required energy is the larger of the required energy of the operation diagram 23 and the required energy of the operation diagram 24.

  Then, the total value of the required energy E1 and the required energy E2 is calculated as the required energy of the operation diagram 32 (step S8006). In the present embodiment, determination of charge feasibility, calculation of charge power amount, and the like are performed based on the calculated required energy.

  With the configuration as described above, even if the basic diagram includes an operation diagram whose arrival point is a non-charging node, an operation plan that anticipates the required energy from the non-charging node to the charging node can be made in advance. Therefore, it is possible to prevent the EV bus from running out of electricity during traveling from the non-charging node to the charging base.

(Sixth embodiment)
Hereinafter, a sixth embodiment of the present invention will be described with reference to FIG. In the present embodiment, the route information stored in the route information means 13 is updated based on vehicle information and the like. The route information is updated by the route information means 13 or the operation plan making means 10, and the updated route information is stored in the route information means 13. The route information update process in the present embodiment will be described below. Here, FIG. 45 is a diagram illustrating the update processing of the route information according to the sixth embodiment.

  First, the operation information acquired from each EV bus in operation is sorted based on the vehicle ID and the latest position time (time stamp). FIG. 45A shows an example of sorted operation information. The operation information is sorted by vehicle ID and then sorted by latest position time. The EV bus transmits its own operation information to the vehicle information means 12 at predetermined time intervals, and the vehicle information means 12 stores the operation information acquired at each timing. The EV bus may transmit the latest operation information of the own vehicle at predetermined time intervals, or may be transmitted at the timing of arrival at each stop position or at the timing of departure from each stop position.

  Next, the route information means 13 calculates the required time between each stop position and the amount of change in SOC (%) based on the sorted operation information. The required time between each stop position is calculated by subtracting the departure time of the departure point from the arrival time of the arrival point. Also, the SOC change amount is calculated by subtracting the arrival point SOC from the departure point SOC. The arrival time and departure time of each stop position are acquired from the latest position time. As shown in FIG. 45 (b), the required time between the nodes AB calculated from the operation information of FIG. 45 (a) is 19 minutes, and the change amount of the SOC of the EV bus operated between the nodes AB is 10%. .

  Next, the route information means 13 obtains the distance (km) between the stop positions from the route information, obtains the initial battery capacity (kWh) and SOH (%) from the storage battery information, and consumes energy between the stop positions ( kWh). The storage battery information having the same vehicle ID as the operation information is used. Then, the power consumption between the stop positions is calculated based on the calculated energy consumption and the distance between the stop positions. Energy consumption and electricity consumption can be calculated as follows.

  In the example of FIG. 45, when the initial battery capacity of the EV bus (vehicle ID001) is 50 kWh, SOH is 90%, and the distance between the nodes AB is 4 km, the amount of change in SOC is 10% as shown in FIG. Therefore, the electricity cost is 1.125 kWh / km. Note that the power consumption calculated here is an average power consumption between the nodes AB.

  The route information is updated based on the required time and the electricity consumption thus obtained. The route information can be updated by adding or overwriting the newly calculated route information. For example, as shown in FIG. 45C, the route information may be updated by overwriting the newly calculated route information in each field of the route information. Alternatively, the newly calculated route information may be sequentially added to the past route information, and the route information with the latest information update time may be used when planning or replanning the operation plan.

  Finally, the route information means 13 deletes the operation information acquired for updating the route information and ends the route information update process. Thus, by updating the route information to the latest information, it is possible to accurately estimate the remaining power amount of the EV bus. Therefore, an appropriate operation plan with a small deviation from the actual operation state can be made.

(Seventh embodiment)
Next, a seventh embodiment of the present invention will be described with reference to FIG. In the present embodiment, the vehicle information unit 12 calculates a battery life-related parameter in consideration of the actual deterioration state (SOH) of the EV bus based on the SOH mapping table and the target SOH table prepared in advance. The battery life-related parameters (hereinafter referred to as “lifetime parameters”) are parameters such as the upper and lower limits of the remaining power amount and the maximum charge / discharge rate set for extending the battery life of the EV bus. First, the SOH mapping table and the target SOH table will be described, where Fig. 46 is a diagram showing an example of the SOH mapping table and the target SOH table.

  In the SOH mapping table, as shown in FIG. 46A, the actual SOH (actual SOH) of the storage battery of the EV bus and the life parameter set for the actual SOH are mapped for each EV bus. . The life parameter of each EV bus is set based on the SOH mapping table, and the set life parameter is stored as storage battery information. For example, according to the SOH mapping table of FIG. 46A, the EV bus with the vehicle ID 001 is set based on 6 kWh as the remaining electric energy lower limit when the SOH is 95%.

  In the SOH mapping table, the actual SOH (and the lifetime parameter) are mapped discretely (for example, every 5%) at an arbitrary interval. Since the appropriate lifetime parameter changes according to the actual SOH, for example, as shown in FIG. 46 (a), the remaining power lower limit value (kWh) is mapped so as to increase as the actual SOH decreases. ing. Further, the remaining power upper limit (kWh), the maximum charge rate (kW), and the maximum discharge rate (kW) are mapped so as to decrease as the actual SOH decreases. The SOH mapping table may be prepared for each EV bus, or an SOH mapping table that is commonly used for a plurality of EV buses having the same vehicle type may be prepared.

  In the target SOH table, as shown in FIG. 46 (b), the accumulated travel distance (km) of the EV bus and the target SOH corresponding to the accumulated travel distance are mapped for each EV bus. The target SOH is a reference SOH that is set according to the accumulated travel distance of each EV bus. When the actual SOH is higher than the target SOH, the deterioration of the storage battery is suppressed, and when the actual SOH is lower than the target SOH, it is considered that the deterioration of the storage battery is progressing. For example, according to the target SOH table of FIG. 46B, the EV bus with vehicle ID001 has a target SOH set to 95% when the cumulative travel distance is 1000 km.

  In the target SOH table, the accumulated travel distance is mapped discretely (for example, every 1000 km) at an arbitrary interval. The target SOH table may be prepared for each EV bus, or a target SOH table that is commonly used for a plurality of EV buses having the same vehicle type may be prepared.

  Next, a method in which the vehicle information unit 12 calculates the life parameter of the EV bus will be described. In the following, a description will be given of a case where the lifetime parameter is calculated for the EV bus (hereinafter referred to as “EV1”) having the vehicle ID 001. For EV1, it is assumed that the actual accumulated travel distance is 1400 km and the actual SOH is 91%.

  First, the vehicle information means 12 refers to the target SOH table and calculates a target SOH according to the accumulated travel distance of the EV bus. The target SOH can be calculated by the following equation.

Here, the result D is the result accumulated travel distance, and the target D _low and the target D _high are the accumulated travel distances such that target D _low <result D <target D _high mapped on the target SOH table. In the case of EV1, since the result D is 1400 km, referring to the target SOH table in FIG. 46B, the target D _low is 1000 km and the target D _high is 2000 km.

The target SOH _low and the target SOH _high are target SOHs corresponding to the target D _low and the target D _high on the target SOH table, respectively. Since the target D _low of EV1 is 1000 km and the target D _high is 2000 km, the target SOH _low is 95% and the target SOH _high is 90%. When the above values are applied to the above equation, the target SOH of EV1 is 93%. Since the actual SOH of EV1 is 91%, it is considered that the deterioration of the storage battery of EV1 is progressing.

  Next, the vehicle information means 12 refers to the SOH mapping table and calculates a life parameter y corresponding to the actual SOH of the EV bus. The life parameter y can be calculated by the following formula.

Here, y is the upper / lower limit value of the remaining electric energy, the maximum charge / discharge rate, etc., and the actual SOH _low and the actual SOH _high are the actual SOH _{low and the} actual SOH <actual SOH _high mapped on the SOH mapping table. SOH. In the case of EV1, since the actual SOH is 91%, referring to the SOH mapping table in FIG. 46A, the actual SOH _low is 90% and the actual SOH _high is 95%.

Further, y _low and y _high are lifetime parameters y corresponding to the actual SOH _low and the actual SOH _high , respectively, on the SOH mapping table. Since EV1 actual SOH _low is 90% and actual SOH _high is 95%, for example, when life parameter y is the remaining power lower limit, y _low is 7 kWh, y _high is 6 kWh, and EV1 remaining power lower limit The value y is 6.8 kWh.

The vehicle information means 12 calculates the life parameter y _adjusted considering the deterioration of the storage battery based on the target SOH calculated as described above and the battery life related parameter y. When the life parameter y is the remaining power lower limit, the life parameter y _adjusted can be calculated by the following equation.

Since the remaining electric energy lower limit y of EV1 is 6.8 kWh, the actual SOH is 91%, and the target SOH is 93%, the remaining electric energy lower limit y _adjusted is about 6.9 kWh. Therefore, the lower limit value of the remaining power amount of the storage battery information of EV1 is set to about 6.9 kWh.

Further, when the life parameter y is the remaining power upper limit value or the maximum charge / discharge rate, the life parameter y _adjusted can be calculated by the following equation.

  Thus, by comparing the actual SOH (actual SOH) with a preset reference SOH (target SOH) and setting the battery life-related parameters according to the deterioration of the storage battery, the deterioration rate of the storage battery Can be reduced and deterioration can be suppressed.

(Eighth embodiment)
The eighth embodiment of the present invention will be described below with reference to FIGS. 47 and 48. In this embodiment, the operation plan drafting means 10 drafts an operation plan in consideration of wireless power feeding or non-contact power feeding at a stop position (such as a bus stop) other than the charging base. Specifically, the EV bus remaining power EVrem used for the evaluation of the feasibility of charging and the calculation of the charging power at the charging base is taken into account the charging power from the wireless power supply at the stop position. calculate.

  FIG. 47 is a diagram illustrating an example of an operation plan designed in consideration of wireless power feeding at the stop position. In FIG. 47, charging bases A and F are provided with a charging facility capable of rapid charging and slow charging, and a bus stop D is provided with a wireless power feeding facility capable of wirelessly feeding the EV bus. The EV bus is wirelessly powered from the wireless power supply facility while stopping at the bus stop D. As shown in FIG. 47, in this operation plan, not only the charging power amount at the charging base but also the charging power amount at the bus stop D is planned.

  The operation plan planning process of this embodiment will be described in detail with reference to FIG. Here, FIG. 48 is a flowchart showing the determination process of the feasibility of charging according to the present embodiment. As shown in FIG. 48, steps S401 to S409 are the same as the charge feasibility determination process of the first embodiment described with reference to FIG.

That is, the operation planning means 10 first acquires the arrival point Ta and the candidate departure point Td (step S401), and supplies the grid supply power P _{i, 1} (t) (kW), P _{i, 2} (t) (kW ), Sampling interval s (sec), stationary battery information, EV bus remaining power lower limit EVlow (kWh), etc. are acquired (step S402). Next, the arrival time of the arrival point Ta is set as the start time ts, the departure time of the candidate departure point Td is set as the end time te (step S403), and the grid supply power P (t) is set at the power level 1. The grid power supply power P _{i, 1} (t) is set (step S404), and the grid power supply amount Eg (kWh) supplied from the grid from the start time ts to the end time te based on the set parameters. ) Is calculated (step S405). Then, using the node ID of the arrival point Ta, the stationary storage battery information of the stationary storage battery SSB that can be used at the arrival point Ta is extracted from the stationary storage battery information (step S406), and immediately before the arrival point Ta from the arrival point list. Arrival point Tap is extracted (step S407), and based on the extracted arrival point Tap, the stationary storage battery SSB has power level 1 power supply from the arrival time of arrival point Tap to the arrival time of arrival point Ta. The remaining electric energy E _SSB (kWh) when charged at is calculated (step S408). Further, based on the grid power supply amount Eg (kWh) calculated in the above steps and the remaining power amount E _SSB (kWh) of the stationary storage battery SSB, it is used from the start time ts to the determination end te at the arrival point Ta. The possible energy Eavail (kWh) is calculated (step S409).

  When the available energy Eavail is calculated, the coefficient R of the charging power amount from the wireless power supply is set (step S41001). The coefficient R is a ratio with respect to the maximum charge power amount from the wireless power feeding, and is used for estimating the remaining power amount EVrem at the arrival point Ta. When the coefficient R is set to 1, the remaining power amount EVrem is estimated on the assumption that the EV bus is charged with the maximum charging power amount from wireless power feeding. When the coefficient R is set to 0, the EV bus is wirelessly powered. Assuming that the person is not charged at all, the remaining electric energy EVrem is estimated.

  Next, by using the set coefficient R, the remaining electric energy EVrem (kWh) of the EV bus at the arrival point Ta considering wireless power feeding is estimated (step S41002). The remaining electric energy EVrem is calculated by the following equation.

Here, EVrem _TD is the remaining electric energy at the departure point of the service schedule at the arrival point Ta. Therefore, EVrem calculated in the present embodiment is obtained by adding R × Ewc to EVrem calculated in the first embodiment (remaining electric energy at the starting point of the operation diagram at the arrival point Ta−required energy of the operation diagram). It is. Here, Ewc is the maximum charging power amount by wireless power feeding, and is calculated by the following equation assuming that the EV bus is charged with the maximum output power of the wireless power feeding equipment while stopping at the bus stop.

P _{mc, i} (kW) is the maximum output power of the wireless power supply facility at the bus stop i, and T _{s, i} (sec) is the stop time at the bus stop i. That is, Ewc (kWh) is the maximum amount of charge power that can be charged when the EV bus stops at the stop position as planned and is always charged with the maximum output power of the wireless power supply facility during the stop. Information on the power supply capability of the wireless power supply facility such as P _{mc, i} (kW) is stored in, for example, the charging facility information means 14.

  When an EV bus actually operates, the stop time at the bus stop may change depending on the number of passengers, and the EV bus may pass through a bus stop where there are no passengers, so Ewc (kWh) Can not be charged. Therefore, the coefficient R is set in consideration of such dynamic factors. In the present embodiment, the coefficient R is set within a range of 0.5 ≦ R ≦ 1.0, and R is set to 0.5 in step S41001. The coefficient R can be arbitrarily set as long as it is within the range of 0 ≦ R ≦ 1.

In steps S411 to S416, it is determined whether or not a predetermined charging power amount can be charged at the charging point based on EVrem calculated in step S41002. Steps S411 to S416 are the same as the charge feasibility determination process of the first embodiment. That is, the EV bus remaining power lower limit EVlow, the EV bus remaining power EVrem at the arrival point Ta, the required energy Ereq of the operation schedule at the departure point Td, and the energy Eavail available at the arrival point Ta are compared (step S411). ) If Eavail + EVrem−EVlow ≧ Ereq holds (YES in step S411), the required discharge amount E _SSB req is calculated (step S415), and it is determined that the predetermined power amount can be charged (step S416). Proceed to step S10511 of the evaluation process. On the other hand, if Eavail + EVrem−EVlow ≧ Ereq does not hold (NO in step S411), the grid supply power P (t) is set to P _{i, 2} (t) (step S413). The same processing (step S405 to step S411) is performed. If the above equation does not hold again at step 411 in the power level 2 state, it is determined that charging is not possible (step S414).

  In the present embodiment, when the expression of step S411 does not hold, the process does not immediately proceed to step S412, but first, it is determined whether R is smaller than 1 (step S41003). If R is 1 (NO in step S41003), the process proceeds to step S412, and if R is smaller than 1 (YES in step S41003), the coefficient R is increased by a predetermined amount ΔR (R = R + ΔR). (Step S41004), it returns to Step S41002. If it is determined that charging is possible (step S416), the amount of charging power is calculated using the coefficient R set at that time.

  As described above, in the present embodiment, while gradually increasing EVrem by gradually increasing the charging power amount Ewc by wireless power feeding from half amount (R = 0.5) to full amount (R = 1.0). Determine the feasibility of charging. As a result, it is possible to determine the feasibility of charging in consideration of dynamic factors such as changes in the stop time at the bus stop and the passage of the bus stop. In the determination in step S41003, a threshold value r (for example, 0.9 or 0.8) smaller than 1 may be set to determine R <r. Thereby, the operation plan which can be charged with a margin can be drawn up.

(Ninth embodiment)
The ninth embodiment of the present invention will be described below with reference to FIGS. In the present embodiment, as in the third embodiment, arrival points are acquired based on the ascending order of time, and connection with candidate departure points is performed. In this case, a predetermined number of chargeable candidate departure points are extracted from the acquired arrival departure point candidate departure points. Then, an operation plan is created by selecting candidate departure points that satisfy a predetermined condition from the extracted candidate departure points and connecting them to the arrival points. The operation plan creation means 10 creates a plurality of operation plans while changing the number of candidate departure points to be extracted, calculates an evaluation value of each operation plan, and selects an operation plan to be actually used according to the evaluation value. .

  Here, FIG. 49 is a block diagram illustrating a functional configuration of the operation management apparatus according to the ninth embodiment. As shown in FIG. 49, the operation plan planning unit 10 according to the present embodiment further includes an operation diagram selection unit 105 and an operation plan evaluation unit 106. Other configurations are the same as those of the first embodiment.

  The operation diagram selection means 105 selects a candidate departure point that satisfies a predetermined condition from a predetermined number of candidate departure points evaluated as being chargeable. The predetermined condition is set according to the purpose of the planned operation plan. As predetermined conditions, the distance of the operation diagram is the maximum, the distance of the operation diagram is the minimum, the distance of the traffic jam occurring in the operation diagram is the minimum, and the time of the traffic jam occurring in the operation diagram Is minimal.

For example, when planning an operation plan for the purpose of reducing fuel costs and CO ₂ emissions, the operation diagram selection means 105 is included in an operation diagram having the maximum travel distance from a predetermined number of candidate departure points. Select a candidate starting point. The vehicle assignment means 101 preferentially assigns the EV bus to the operation schedule including the selected candidate departure point, thereby minimizing the travel distance of the non-electric vehicle and reducing the fuel cost and the CO ₂ emission amount. Can do.

  Further, when planning an operation plan for the purpose of extending the life of the storage battery of the EV bus, the operation diagram selecting means 105 selects candidate departures included in the operation diagram having the minimum travel distance from a predetermined number of candidate departure points. Select a point. The vehicle assignment means 101 preferentially assigns EV buses whose storage battery deterioration has progressed to the operation schedule including the selected candidate departure point, so that the deterioration degree of the storage battery of each EV bus becomes uniform, and the entire bus system The life of the storage battery in can be extended.

  Furthermore, when planning an operation plan for the purpose of preventing electric shortage of the EV bus, the operation diagram selection means 105 is included in an operation diagram that minimizes the distance and time of traffic jams from a predetermined number of candidate departure points. Select a candidate starting point. The vehicle allocation means 101 preferentially allocates EV buses with a small amount of remaining power and effective capacity of the storage battery to the operation schedule including the selected candidate departure point, thereby preventing shortage of electric power.

  The predetermined conditions are not limited to those described above, and can be arbitrarily set according to the purpose of the planned operation plan. Moreover, in this embodiment, according to the objective of the operation plan to plan, the vehicle allocation means 101 sets a priority to the vehicle registered into the operation management apparatus, and allocates a vehicle in order of a priority.

  The operation plan evaluation unit 106 calculates an evaluation value of the generated operation plan, and selects an operation plan to be actually used according to the evaluation value. As the evaluation value, the size of the EV bus travel distance, the number of assigned vehicles, and the like can be used. The evaluation value can be arbitrarily set according to the purpose of the planned operation plan.

Next, the operation plan planning process of this embodiment will be described with reference to FIG. FIG. 50 is a flowchart showing the operation plan planning process of the present embodiment. Hereinafter will be described the processing in the case of formulating a trip plan for the purpose of reducing fuel costs and CO ₂ emissions.

  As shown in FIG. 50, first, the operation planning means 10 sets a parameter k to 1 (step S9001). The parameter k is the number of candidate departure points to be extracted. Here, k is set to 1 as an initial value, but the initial value of k can be arbitrarily set.

  Next, the operation planning means 10 creates an arrival point list, a candidate departure point list, and an assignable EV list (step S9002), and in the order of the created arrival point list, that is, the arrival time of the arrival point. An arrival point is acquired based on the ascending order (step S9003). An EV bus is assigned to the service schedule of the acquired arrival point and the service schedule whose departure time is earlier than the arrival time of the acquired arrival point (step S9004).

When planning an operation plan for the purpose of reducing fuel costs and CO ₂ emissions, it is preferable to allocate an EV bus to the operation schedule as much as possible and not to allocate a non-electric vehicle. For this reason, the priority of the EV bus is set higher than the priority of the non-electric vehicle. The vehicle assigning means 101 assigns an EV bus to an operation schedule according to such priority, and does not assign a vehicle when there is no assignable EV bus.

  Next, the charge feasibility evaluation unit 104 refers to the candidate departure point list, and extracts k candidate departure points that can be charged from the candidate departure points of the acquired arrival points (step S9005). Here, FIG. 51 is a diagram for explaining a method of extracting candidate departure points. In FIG. 51, the arrival point acquired in step S9003 is arrival point 1, the candidate departure points for arrival point 1 are departure points 2 to 7, and k = 3.

  The charge feasibility evaluation means 104 sequentially evaluates the charge feasibility of each candidate departure point at arrival point 1 until three candidate departure points that can be charged are found. In FIG. 51, starting points 2 and 3 cannot be charged, and starting points 4 to 6 can be charged. Therefore, the charging feasibility evaluation means 104 sequentially evaluates the charging feasibility from the starting point 2 to the starting point 6, evaluates the starting point 6, and finds three starting points 4 to 6 that can be charged. At the time point, the evaluation is terminated and starting points 4 to 6 are extracted.

  In FIG. 51, k starting points are extracted from the candidate starting points. However, if there are no k candidate starting points that can be charged, the charging feasibility evaluation unit 104 determines all the candidate starting points. When the charging feasibility of the starting point is evaluated, the evaluation is finished, and all the found starting points that can be charged are extracted. In this case, there are fewer than k candidate starting points to be extracted.

  In step S9005, when one or more candidate departure points are extracted (YES in step S9006), the operation diagram selection unit 105 selects an operation diagram having the maximum travel distance from the extracted candidate departure points. The vehicle assignment unit 101 assigns an EV bus to the selected schedule (step S9007). In the case of FIG. 51, the operation schedule 5 from the starting point 5 having the longest travel distance (15 km) is selected from the extracted starting points 4 to 6.

  In step S9007, the vehicle assignment unit 101 assigns an EV bus according to the priority set for each EV bus. As a method for assigning EV buses, for example, a method for preferentially assigning EV buses having a low degree of deterioration of the storage battery can be considered. Thereby, the deterioration degree of the storage battery of each EV bus | bath can be equalize | homogenized, and the lifetime of the storage battery of the whole EV bus | bath can be extended.

After the completion of step S9007 or when there is no candidate starting point that can be charged (NO in step S9006), the operation planning means 10 determines the EV bus storage battery information, stationary storage battery information, vehicle allocation list, and charging list. Then, various parameters such as system supply power P _{i, 1} (t), P _{i, 2} (t) are updated (step S9008).

  If there is a next arrival point in the arrival point list (YES in step S9009), the process returns to step S9003, and the operation planning means 10 acquires the next arrival point (step S9003) and repeats steps S9004 to S9008. .

  On the other hand, when there is no next arrival point in the arrival point list (NO in step S9009), that is, when processing for all arrival points in the arrival point list is completed, the vehicle assignment unit 101 operates without assigning the EV bus. A non-electric vehicle is assigned to the diamond (step S9010). Thereby, the operation plan in the case of k = 1 is created.

In step S9010, the operation schedule to which no EV bus is assigned is an operation diagram without an assignable EV bus. The vehicle allocation means 101 connects such operation schedules and allocates non-electric vehicles according to the priority of each vehicle. As a non-electric vehicle allocation method, for example, a method of preferentially allocating a diesel vehicle over a gasoline vehicle, or a method of preferentially allocating a non-electric vehicle with lower fuel consumption can be considered. Thereby, the fuel cost and the CO ₂ emission amount can be further reduced.

  Moreover, the connection method of the operation schedule which allocates a non-electric vehicle is arbitrary. As a connection method, for example, a method of connecting candidate departures closest to the arrival point is cited.

  Next, the operation planning means 10 increments the parameter k by 1 (step S9011), and sets the parameter k to k = 2. The increase width of the parameter k is not limited to 1 and can be arbitrarily set. Alternatively, the initial value of k may be set to 2 or more and decreased by one.

  If the parameter k set in step S9011 is less than or equal to the predetermined maximum value kmax of the parameter k (YES in step S9012), the process returns to step S9002, and the processes in steps S9002 to S9011 are repeated. Thereby, the operation plan in the case of k = 2 is created.

The maximum value kmax of the parameter k can be determined by the following equation according to the number of candidate departure points for each arrival point included in the basic diagram.
kmax = max (NCDP (ap1), NCDP (ap2), ..., NCDP (apn))
In the above equation, NCDP (apn) is the number of candidate departure points for arrival point n.

  On the other hand, when the parameter k set in step S9011 is larger than the predetermined maximum value kmax of the parameter k (NO in step S9012), an operation plan evaluation is performed from among a plurality of operation plans created for each value of k. The means 106 selects an operation plan according to the evaluation value (step S9013). The operation plan selected by the operation plan evaluation unit 106 is stored in the plan storage unit 15 as an operation plan that is actually used (step S9014).

  In step S9013, the operation plan evaluation unit 106 may use, for example, the EV bus travel distance as the evaluation value, and may select the operation plan with the maximum evaluation value, or the travel distance of the non-electric vehicle as the evaluation value. The operation plan having the smallest evaluation value may be selected. Moreover, you may use together the number of allocated vehicles as an evaluation value with these evaluation values.

  As described above, according to the present embodiment, a plurality of operation plans can be created by changing the number of candidate departure points to be extracted, and the operation plan with the best evaluation value can be selected. Further, the evaluation value can be maximized by assigning the vehicle to the operation schedule according to the priority of each vehicle.

For example, if priority is not set for each vehicle and EV buses and non-electric vehicles are assigned to operation schedules at the same time, the number of operation schedules (candidate departure points) to which EV buses can be allocated is reduced, and the EV bus travel distance is reduced. It may not be possible to maximize. However, according to the present embodiment, by preferentially assigning the EV bus, the travel distance of the EV bus can be maximized, and the fuel cost and the CO ₂ emission amount can be effectively reduced.

  In FIG. 50, the operation plan evaluation means 106 selects an operation plan with a good evaluation value after all k value operation plans have been created, but each k value operation plan is created. You may select an operation plan. That is, after the k-value operation plan in step S9010 is created, the operation plan and the evaluation value are compared with the evaluation value of the operation plan created with the previous k value, and an operation plan with a good evaluation value is obtained. select. This is repeated for each k value, and the operation plan finally selected is stored in the plan storage unit 15 as the operation plan to be actually used.

  In addition, the operation plan may be created not only for the k value but also for each power level of the charging base. That is, for each k value, an operation plan for charging at power level 1 and an operation plan for charging at power level 2 may be created.

  Furthermore, in the above description, the priority of the vehicle assigned to the operation schedule is set to two types, that is, the priority for each vehicle type and the priority in the vehicle type, but the method for setting the priority is not limited to this. For example, only the priority for each vehicle may be set. In this case, in step S9004 and step S9007, an EV bus or a non-electric vehicle is assigned to the bus schedule including the candidate departure point according to the priority of the vehicle, and step S9010 is omitted.

In step S9004, when a non-electric vehicle is assigned to the bus schedule including the arrival point acquired in step S9003, k nearest candidate departure points are extracted (step S9005), and candidate departure points that satisfy a predetermined condition are extracted. The non-electric vehicle may be assigned to the operation schedule including the selected candidate departure point (step S9007). When creating an operation plan for the purpose of reducing fuel costs and CO ₂ emissions, for example, a predetermined condition may be that the travel distance of the operation diagram is the minimum.

  In other words, when an EV bus is assigned to a bus schedule that includes an arrival point, the bus schedule is connected to a bus schedule that has the longest travel distance among the bus schedules that include the candidate departure point, and the bus schedule is not electrically powered. When the vehicle is allocated, the operation schedule is connected to an operation schedule having the shortest travel distance among the operation schedules including the candidate departure points. Thereby, the travel distance of the EV bus can be increased, and the travel distance of the non-electric vehicle can be decreased.

  Note that the present invention is not limited to the above-described embodiments as they are, and can be embodied by modifying the components without departing from the scope of the invention in the implementation stage. Various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the above embodiments. Further, for example, a configuration in which some components are deleted from all the components shown in each embodiment is also conceivable. Furthermore, you may combine suitably the component described in different embodiment.

10: Operation plan creation means 101: Vehicle allocation means 102: Operation schedule connection means 103: Charge amount calculation means 104: Charge feasibility evaluation means 105: Operation schedule selection means 106: Operation plan evaluation means 11: Basic schedule means 12: Vehicle information means 13: Route information means 14: Charging equipment information means 141: Stationary storage battery information means 142: System power information means 15: Plan storage means 16: Replan determination means 17: Replan request means

Claims (18)

Vehicle information on a plurality of vehicles including an electric vehicle and a non-electric vehicle, charging facility information on the charging capability of a charging facility arranged at a plurality of charging bases, a path connecting a plurality of stop positions, and each of the above paths Based on the schedule information that defines a plurality of schedules including at least one of the departure time and arrival time of the stop position, an operation plan is created by allocating the vehicle to the schedules determined by the schedule information and planning an operation plan. Means,
The operation planning means is
An electric vehicle capable of assigning and assigning the electric vehicle among the electric vehicle and the non-electric vehicle to the plurality of operation schedules based on an amount of power consumed when the electric vehicle operates the route. An operation management device for allocating the non-electric vehicle to the operation schedule that does not exist. The operation planning means obtains an arrival point in the schedule information, and a candidate departure that can be charged with the amount of power charged based on the amount of power consumed within a chargeable period from the arrival time of the arrival point to the departure time. From the points, select the candidate departure point where the distance of the operation diagram is the maximum, and assign the same electric vehicle as the operation diagram including the acquired arrival point to the operation diagram including the selected candidate departure point,
The operation management device according to claim 1. The operation management device according to claim 2, wherein the operation plan planning unit acquires the arrival points according to an ascending order of the arrival times.   The operation planning means calculates a power consumption amount consumed when the electric vehicle travels the route, and calculates a charging power amount to charge the electric vehicle at each charging base based on the power consumption amount. The operation management device according to claim 1, wherein the electric vehicle is assigned to the operation diagram based on the charging power amount.   The operation plan drafting unit is configured to connect the electric vehicle to the operation diagram so that the remaining electric energy of the storage battery after charging when the storage battery of the electric vehicle is charged with the charged electric energy does not exceed the effective capacity of the storage battery. The operation management device according to claim 4 to be assigned.   The operation planning means has a minimum charging rate necessary for charging the electric vehicle with the amount of charging electric power within a chargeable period from the arrival time to the departure time of the charging base in the storage battery of the electric vehicle. The operation management device according to claim 4 or 5, wherein the electric vehicle is allocated to the operation schedule so that the electric charging vehicle is equal to or lower than a preset maximum charging rate.   The said operation plan creation means allocates the electric vehicle with larger effective capacity of the storage battery of the said electric vehicle to the said operation diagram with the sum total of the power consumption amount required for operation of the said route being larger. The operation management device according to any one of the above.   The said operation plan drafting means adds the predetermined surplus electric energy to the electric energy which integrated | accumulated the distance of the said path | route included in the said operation schedule, and the electric power consumption of the said electric vehicle, and calculates the said electric power consumption. The operation management device according to claim 6.   The operation plan drafting means is preset in the storage battery so that the remaining power amount of the electric vehicle in operation is equal to or more than a lower limit value of the remaining power amount predetermined in the storage battery of the electric vehicle. The operation management device according to claim 5, wherein the charge power amount is calculated so as to be less than or equal to a remaining power amount upper limit value, or to be greater than or equal to the remaining power amount lower limit value and less than or equal to the remaining power amount upper limit value.   The operation plan drafting unit has an evaluation unit that evaluates whether or not the electric vehicle can be charged with the amount of charging electric power within the chargeable period of the charging base, and the electric driving plan is based on the evaluation by the evaluation unit. The operation management device according to claim 6, wherein a vehicle is assigned to the operation diagram. Re-planning judgment means for judging whether or not to re-plan the operation plan planned by the operation plan planning means;
The replanning determination means replans the operation plan based on information that changes during operation of the electric vehicle among information included in at least one of the vehicle information, the charging facility information, and the route information related to the route. Determine
The operation management apparatus according to any one of claims 4 to 10, wherein when the re-planning determination unit determines to re-plan the operation plan, the operation plan planning unit re-plans the operation plan.   The replan determination means calculates a delay time of the electric vehicle in operation according to the operation plan, compares the delay time with a predetermined threshold value, and determines whether to replan the operation plan. The operation management device according to claim 11.   The re-planning determination means acquires the remaining power amount of the electric vehicle in operation according to the operation plan, compares the remaining power amount with a predetermined threshold value, and determines whether to re-plan the operation plan. The operation management device according to claim 11 or 12. The operation planning means selects one operation diagram from the operation diagrams in ascending order of arrival time of arrival points when the evaluation unit evaluates that charging is possible, and the arrival point of the selected operation diagram The same electric vehicle as the selected operation diagram is assigned to an operation diagram having a departure time closest to the arrival time at a time later than the arrival time of the arrival point. Operation management device. At least some operation schedules are non-charging bases where at least one of a starting point and an arriving point does not include the charging facility,
If the arrival point of the operation schedule is the non-charging base, the operation planning means calculates power consumption when operating from the non-charging base to each charging base, and the calculated power consumption The charge power amount is calculated on the basis of the maximum power consumption amount and the power consumption amount consumed when the electric vehicle is operated until the arrival point. The operation management device described.   5. The at least one of a remaining power lower limit value, a remaining power upper limit value, a maximum charge rate, or a maximum discharge rate predetermined for the storage battery of the electric vehicle is calculated according to a deterioration state of the storage battery. The operation management device according to any one of claims 15 to 15. A wireless power feeding facility that wirelessly feeds the electric vehicle while the electric vehicle is stopped is disposed at least at a stop position where the electric vehicle stops.
The operation planning means calculates the amount of power charged to the electric vehicle by wireless power feeding at the stop position based on the information on the power feeding capability of the wireless power feeding equipment, and the charging base at the charging base based on the power amount. The operation management device according to claim 6, wherein the amount of electric power charged in the electric vehicle is calculated. Vehicle information relating to a plurality of vehicles including electric vehicles and non-electric vehicles;
Charging facility information on the charging capacity of charging facilities located at multiple charging bases,
A schedule information that defines a plurality of operation schedules including a route connecting a plurality of stop positions and at least one of a departure time and an arrival time of each stop position on the route;
On the basis of the operation plan planning method for planning an operation plan by allocating the vehicle to the operation schedule determined by the diagram information,
Computer equipment
An electric vehicle capable of assigning and assigning the electric vehicle among the electric vehicle and the non-electric vehicle to the plurality of operation schedules based on an amount of power consumed when the electric vehicle operates the route. An operation planning method for allocating the non-electric vehicle to the operation schedule that does not exist.

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