JP2013196500A - Control device and control method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a control device and a control method which are capable of enhancing calculation accuracy of an optimum solution while preventing the optimum solution from becoming a local solution.SOLUTION: A HEMS 200 includes a calculation unit 230 that utilizes, as an element, an operation of a PV unit 130, a storage battery unit 140, a fuel cell unit 150, or a hot water storage unit 160, and calculates, every unit time, an optimum solution including at least one of a purchase charge of electric power supplied from a system and a sales charge of electric power provided to the system. The calculation unit 230 calculates the optimum solution on the basis of a weighting value determined from a parameter in a certain period longer than a unit time.

Description

  The present invention relates to a control device and a control method for controlling a distributed power source, a power storage device, or a heat storage device.

  In recent years, methods for optimizing the operation of a distributed power source, a power storage device, and a heat storage device have been proposed. A distributed power source is a device that generates electric power using natural energy such as sunlight, wind power, and geothermal heat, such as a solar battery. Or a distributed power supply is an apparatus which produces | generates electric power using fuel gas like a fuel cell, for example. The power storage device is a device that stores electric power, such as a secondary battery. The heat storage device is a device that stores electric power by converting electric power into heat, such as a water heater.

  For example, a technique for optimizing the amount of power (amount of power purchased) supplied from the grid by controlling charging and discharging of the power storage device and minimizing the purchase price of power has been proposed (for example, Patent Document 1). .

  By the way, in order to obtain a solution such as minimization of a power purchase fee, a method for calculating an optimum solution for each unit time by searching for a combination of a plurality of elements that affect the solution is known. Such methods are called greedy methods, greedy methods, greedy methods, and the like.

  For example, the following objective function can be used in a method (hereinafter, greedy method) for calculating an optimal solution such as a purchase price of power supplied from the grid and a sale price of power provided to the grid.

  Here, cell_power (t) indicates the trading power in unit time t. When cell_power (t) is a positive value, a reverse power flow is performed on the system, and cell_power (t) When is a negative value, power is supplied from the grid. cell_unit_price (t) indicates the unit price of the sold power in unit time t, and buy_unit_price (t) indicates the unit price of purchased power in unit time t. Here, the unit time t is, for example, the minimum time interval at which charging / discharging of the power storage device can be switched.

Japanese Patent Laid-Open No. 2002-247761

  As described above, in the method for calculating the optimal solution such as the purchase price of the power supplied from the grid and the sale price of the power provided to the grid (hereinafter, greedy method), the optimal solution is calculated for each unit time. Is possible. However, since the optimal solution is calculated every unit time, the optimal solution tends to fall into a local solution.

  Therefore, the present invention has been made to solve the above-described problems, and provides a control device and a control method that can improve the calculation accuracy of an optimal solution without the optimal solution falling into a local solution. For the purpose.

  The control device according to the first feature is a device for controlling the distributed power source, the power storage device, or the heat storage device. The control device has the operation of the distributed power supply, the power storage device or the heat storage device as an element, and at least one of the purchase fee of power supplied from the grid and the sale fee of power provided to the grid is a unit. A calculation unit that calculates an optimal solution every time is provided. The calculation unit calculates the optimum solution based on a weight value determined from a parameter in a certain period longer than the unit time.

  In the first feature, the parameter is a unit price of power supplied from the grid.

  In the first feature, the parameter is a sales unit price of electric power provided to the grid.

  In the first feature, the parameter is a unit price of power supplied from the grid. The element includes an operation of the power storage device. The weight value is determined so that a solution including an operation of discharging the power storage device is easily calculated as the optimal solution when the purchase unit price is relatively high. The weight value is determined such that when the purchase unit price is relatively low, a solution including an operation of storing power in the power storage device is easily calculated as the optimal solution.

  In the first feature, the parameters are a purchase unit price of power supplied from the grid and a sale unit price of power provided to the grid. The element includes an operation of the power storage device. The certain period includes a first unit time and a second unit time that is later in time than the first unit time. In the case where the selling unit price of the second unit time is higher than a predetermined unit price by the purchase unit price of the first unit time, the weight value of the first unit time includes an operation in which the power storage device stores power. Is determined so as to be easily calculated as the optimum solution. In the case where the selling unit price of the second unit time is lower than a predetermined unit price by the purchase unit price of the first unit time, the weight value of the first unit time includes an operation that discharges the power storage device. Is determined so as to be easily calculated as the optimum solution.

  In the first feature, the weight value of the first unit time is determined based on a switching loss between an operation of storing the power storage device and an operation of discharging the power storage device.

  In the first feature, the weight value of the first unit time is determined based on the power consumption consumed by a load or the amount of heat stored in the heat storage device during the certain period.

  In the first feature, the weight value of the first unit time is determined based on the number of times of switching between the operation of storing the power storage device and the operation of discharging the power storage device in the certain period.

  The control method according to the second feature is a method for controlling the distributed power source, the power storage device, or the heat storage device. The control method includes the operation of the distributed power source, the power storage device or the heat storage device as an element, and at least one of a purchase fee of power supplied from the grid and a sale fee of power provided to the grid as a solution. Step A for calculating an optimal solution every time is provided. In the step A, the optimum solution is calculated based on a weight value determined from parameters in a fixed period longer than the unit time.

  According to the present invention, it is possible to provide a control device and a control method that can improve the calculation accuracy of an optimal solution without the optimal solution falling into a local solution.

FIG. 1 is a diagram illustrating an energy management system 100 according to the first embodiment. FIG. 2 is a diagram illustrating the customer 10 according to the first embodiment. FIG. 3 is a diagram illustrating the HEMS 200 according to the first embodiment. FIG. 4 is a diagram for explaining an objective function according to the first embodiment. FIG. 5 is a diagram for explaining a weight value determination method (1) according to the first embodiment. FIG. 6 is a diagram for explaining a weight value determination method (2) according to the first embodiment. FIG. 7 is a diagram for explaining a weight value determination method (2) according to the first embodiment. FIG. 8 is a flowchart showing the control method according to the first embodiment.

  Hereinafter, a control device according to an embodiment of the present invention will be described with reference to the drawings. In the following description of the drawings, the same or similar parts are denoted by the same or similar reference numerals.

  However, it should be noted that the drawings are schematic and ratios of dimensions and the like are different from actual ones. Therefore, specific dimensions and the like should be determined in consideration of the following description. Moreover, it is a matter of course that portions having different dimensional relationships and ratios are included between the drawings.

[Outline of Embodiment]
The control device according to the embodiment is a device for controlling the distributed power source, the power storage device, or the heat storage device. The control device has the operation of the distributed power supply, the power storage device or the heat storage device as an element, and at least one of the purchase fee of power supplied from the grid and the sale fee of power provided to the grid is a unit. A calculation unit that calculates an optimal solution every time is provided. The calculation unit calculates the optimum solution based on a weight value determined from a parameter in a certain period longer than the unit time.

  In the embodiment, the calculation unit calculates an optimal solution based on a weight value determined from a parameter in a certain period longer than a unit time. Even if the optimal solution is calculated every unit time, the optimal solution does not fall into a local solution, and the calculation accuracy of the optimal solution can be improved.

[First Embodiment]
(Energy management system)
Hereinafter, the energy management system according to the first embodiment will be described. FIG. 1 is a diagram illustrating an energy management system 100 according to the first embodiment.

  As shown in FIG. 1, the energy management system 100 includes a customer 10, a CEMS 20, a substation 30, a smart server 40, and a power plant 50. The customer 10, the CEMS 20, the substation 30 and the smart server 40 are connected by a network 60.

  The customer 10 has at least one of a distributed power source, a power storage device, and a heat storage device. A distributed power source is a device that generates electric power using natural energy such as sunlight, wind power, and geothermal heat, such as a solar battery. Or a distributed power supply is an apparatus which produces | generates electric power using fuel gas like a fuel cell, for example. The power storage device is a device that stores electric power, such as a secondary battery. The heat storage device is a device that stores electric power by converting electric power into heat, such as a water heater.

  For example, the customer 10 may be a single-family house, an apartment house such as a condominium, a commercial facility such as a building, or a factory.

  In the first embodiment, a customer group 10 </ b> A and a customer group 10 </ b> B are configured by a plurality of consumers 10. The consumer group 10A and the consumer group 10B are classified by, for example, a geographical area.

  The CEMS 20 controls interconnection between the plurality of consumers 10 and the power system. The CEMS 20 may be referred to as a CEMS (Cluster / Community Energy Management System) in order to manage a plurality of consumers 10. Specifically, the CEMS 20 disconnects between the plurality of consumers 10 and the power system at the time of a power failure or the like. On the other hand, the CEMS 20 interconnects the plurality of consumers 10 and the power system when power is restored.

  In the first embodiment, a CEMS 20A and a CEMS 20B are provided. For example, the CEMS 20A controls interconnection between the customer 10 included in the customer group 10A and the power system. For example, the CEMS 20B controls interconnection between the customer 10 included in the customer group 10B and the power system.

  The substation 30 supplies electric power to the plurality of consumers 10 via the distribution line 31. Specifically, the substation 30 steps down the voltage supplied from the power plant 50.

  In the first embodiment, a substation 30A and a substation 30B are provided. For example, the substation 30A supplies power to the consumers 10 included in the consumer group 10A via the distribution line 31A. For example, the substation 30B supplies power to the consumers 10 included in the consumer group 10B via the distribution line 31B.

  The smart server 40 manages a plurality of CEMSs 20 (here, CEMS 20A and CEMS 20B). The smart server 40 also manages a plurality of substations 30 (here, the substation 30A and the substation 30B). In other words, the smart server 40 comprehensively manages the customers 10 included in the customer group 10A and the customer group 10B. For example, the smart server 40 has a function of balancing the power to be supplied to the consumer group 10A and the power to be supplied to the consumer group 10B.

  The power plant 50 generates power using thermal power, wind power, hydraulic power, nuclear power, and the like. The power plant 50 supplies power to the plurality of substations 30 (here, the substation 30A and the substation 30B) via the power transmission line 51.

  The network 60 is connected to each device via a signal line. The network 60 is, for example, the Internet, a wide area network, a narrow area network, a mobile phone network, or the like.

(Customer)
Below, the consumer which concerns on 1st Embodiment is demonstrated. FIG. 2 is a diagram illustrating details of the customer 10 according to the first embodiment.

  As shown in FIG. 2, the customer 10 includes a distribution board 110, a load 120, a PV unit 130, a storage battery unit 140, a fuel cell unit 150, a hot water storage unit 160, and a HEMS 200.

  Distribution board 110 is connected to distribution line 31 (system). Distribution board 110 is connected to load 120, PV unit 130, storage battery unit 140, and fuel cell unit 150 via a power line.

  The distribution board 110 may have a measurement unit that measures electric power supplied from the distribution line 31 (system). The measurement unit may measure the power consumption of the load 120.

  The load 120 is a device that consumes power supplied via the power line. For example, the load 120 includes devices such as a refrigerator, lighting, an air conditioner, and a television. The load 120 may be a single device or may include a plurality of devices.

  The PV unit 130 includes a PV 131 and a PCS 132. The PV 131 is an example of a distributed power source, and is a device that generates power in response to reception of sunlight. The PV 131 outputs the generated DC power. The amount of power generated by the PV 131 changes according to the amount of solar radiation applied to the PV 131. The PCS 132 is a device (Power Conditioning System) that converts DC power output from the PV 131 into AC power. The PCS 132 outputs AC power to the distribution board 110 via the power line.

  In the first embodiment, the PV unit 130 may have a pyranometer that measures the amount of solar radiation irradiated on the PV 131.

  The PV unit 130 is controlled by an MPPT (Maximum Power Point Tracking) method. Specifically, the PV unit 130 optimizes the operating point (a point determined by the operating point voltage value and the power value, or a point determined by the operating point voltage value and the current value) of the PV 131.

  The storage battery unit 140 includes a storage battery 141 and a PCS 142. The storage battery 141 is a device that stores electric power. The PCS 142 is a power conditioning system that converts AC power supplied from the distribution line 31 (system) into DC power. Further, the PCS 142 converts DC power output from the storage battery 141 into AC power.

  The fuel cell unit 150 includes a fuel cell 151 and a PCS 152. The fuel cell 151 is an example of a distributed power source, and is a device that generates electric power using fuel gas. The PCS 152 is a device (Power Conditioning System) that converts DC power output from the fuel cell 151 into AC power.

  The fuel cell unit 150 operates by load following control. Specifically, the fuel cell unit 150 controls the fuel cell 151 so that the power output from the fuel cell 151 follows the power consumption of the load 120.

  The hot water storage unit 160 is an example of a heat storage device that converts electric power into heat, accumulates heat, and stores heat generated by a cogeneration device such as the fuel cell unit 150 as hot water. Specifically, the hot water storage unit 160 has a hot water storage tank, and warms water supplied from the hot water storage tank by exhaust heat generated by the operation (power generation) of the fuel cell 151. Specifically, the hot water storage unit 160 warms the water supplied from the hot water storage tank and returns the warmed hot water to the hot water storage tank.

  The HEMS 200 is a control device for controlling a distributed power source, a power storage device, or a heat storage device.

  In the first embodiment, the HEMS 200 is connected to the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160 via signal lines, and the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage. The unit 160 is controlled. Further, the HEMS 200 may control the power consumption of the load 120 by controlling the operation mode of the load 120.

  The HEMS 200 is connected to various servers via the network 60. Various servers store, for example, information (hereinafter, energy fee information) such as a unit price of power supplied from the grid, a unit price of power sold from the grid, and a unit price of fuel gas.

  Or various servers store the information (henceforth energy consumption prediction information) for predicting the power consumption of the load 120, for example. The energy consumption prediction information may be generated based on, for example, the past power consumption actual value of the load 120. Alternatively, the energy consumption prediction information may be a model of power consumption of the load 120.

  Or various servers store the information (henceforth PV power generation amount prediction information) for predicting the power generation amount of PV131, for example. The PV power generation prediction information may be a predicted value of the amount of solar radiation irradiated on the PV 131. Alternatively, the PV power generation prediction information may be weather forecast, season, sunshine time, and the like.

  Specifically, as illustrated in FIG. 3, the HEMS 200 includes a reception unit 210, a transmission unit 220, a calculation unit 230, and a control unit 240.

  The receiving unit 210 receives various signals from a device connected via a signal line. For example, the receiving unit 210 receives information indicating the power generation amount of the PV 131 from the PV unit 130. The receiving unit 210 receives information indicating the storage amount of the storage battery 141 from the storage battery unit 140. The receiving unit 210 receives information indicating the power generation amount of the fuel cell 151 from the fuel cell unit 150. The receiving unit 210 receives information indicating the amount of hot water stored in the hot water storage unit 160 from the hot water storage unit 160.

  In the first embodiment, the reception unit 210 may receive energy charge information, energy consumption prediction information, and PV power generation amount prediction information from various servers via the network 60. However, the energy fee information, the energy consumption prediction information, and the PV power generation amount prediction information may be stored in the HEMS 200 in advance.

  The transmission unit 220 transmits various signals to a device connected via a signal line. For example, the transmission part 220 transmits the signal for controlling the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160 to each apparatus.

  The calculation unit 230 is based on the operations of the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160, and is at least one of a purchase price for power supplied from the grid and a sale price for power supplied to the grid. And the optimal solution is calculated every unit time. Here, the calculation unit 230 calculates an optimal solution based on the weight value determined from the parameters in a certain period longer than the unit time.

  Specifically, the calculation unit 230 calculates an optimal solution for each unit time using an objective function shown below.

  Here, cell_power (t) indicates the trading power in unit time t. When cell_power (t) is a positive value, a reverse power flow is performed on the system, and cell_power (t) When is a negative value, power is supplied from the grid. sell_unit_price (t) indicates the unit price (purchased unit price) of the electric power sold per unit time t, and buy_unit_price (t) indicates the unit price of the electric power purchased per unit time t (unit price for sale). Here, the unit time t is, for example, the minimum time interval at which the operation of the PV unit 130, the storage battery unit 140, the fuel cell unit 150, or the hot water storage unit 160 can be switched.

  In the first embodiment, weight (t) is a weight value applied to the unit time t. As described above, weight (t) is determined from parameters in a certain period longer than the unit time t.

  Here, the parameter is, for example, the unit price of power supplied from the grid. Alternatively, the parameter is, for example, the sales unit price of power provided to the grid. Alternatively, the parameter is the unit price of fuel gas purchase.

  Here, as shown in FIG. 4, the elements applied to the objective function are the operation of the PV unit 130 (PV operation), the operation of the storage battery unit 140 (operation of the storage battery), and the operation of the fuel cell unit 150 (operation of the fuel cell). Operation) and operation of the hot water storage unit 160 (operation of the hot water storage unit).

  The operation of the PV unit 130 is an operation predicted based on the PV power generation amount prediction information. For example, the PV unit 130 is controlled by the MPPT method. FIG. 4 illustrates a case where the operation of the PV unit 130 is three types of “AA”, “AB (not shown in FIG. 4)”, and “AC”.

  The operation of the storage battery unit 140 is, for example, power storage, discharge, and maintenance. FIG. 4 illustrates a case where the operation of the storage battery unit 140 has three types of “BA”, “BB (not shown in FIG. 4)”, and “BC”.

  The operation of the fuel cell unit 150 is an operation predicted based on the energy consumption prediction information. For example, the fuel cell unit 150 is controlled by load following control. FIG. 4 illustrates a case where the operation of the fuel cell unit 150 is of three types “CA”, “CB”, and “CC”.

  The operation of the hot water storage unit 160 is, for example, an increase in the amount of hot water storage, maintenance of the hot water storage amount, and no warming. FIG. 4 illustrates a case where the operation of the hot water storage unit 160 is three types of “DA”, “DB”, and “DC”.

In the case shown in FIG. 4, there are 81 types (3 ⁴ ) of combinations of elements. A weight value (weight (t)) is defined for each combination of elements. The calculation unit 230 applies all combinations to the objective function in a brute force manner and identifies combinations of elements (operations) that constitute the maximum value (optimum solution) of “Sell_price (t) + weight (t)”.

  Here, Sell_price (t) may be considered as a purchase fee for power supplied from the grid, or may be considered as a charge for selling power provided to the grid.

  The control unit 240 controls the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160. The control unit 240 controls the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160 based on the elements (operations) that constitute the optimal solution calculated by the calculation unit 230.

(Determination method of weight value (1))
Hereinafter, the determination method (1) of the weight value will be described. FIG. 5 is a diagram for explaining a weight value determination method (1) according to the first embodiment.

  The weight value is determined so that a solution including an operation of discharging the storage battery 141 is easily calculated as an optimal solution when the purchase unit price is relatively high.

  Specifically, in the example shown in FIG. 5, the solution including the operation of discharging the storage battery 141 is easily calculated as the optimal solution in the unit time a where the purchase price is higher than the average value of the purchase price in a certain period. Determined.

  As a result, the electric power supplied from the grid is reduced by the discharge of the storage battery 141, and the power purchase fee can be reduced. In addition, by determining such weighted values when the purchase unit price is relatively high, it is possible to efficiently reduce the purchase fee throughout the fixed period without the optimal solution falling into the local solution. it can.

  On the other hand, the weight value is determined so that the solution including the operation of storing the storage battery 141 is easily calculated as the optimum solution when the purchase unit price is relatively low.

  Specifically, in the example shown in FIG. 5, the solution including the operation of storing the storage battery 141 is easily calculated as the optimal solution in the unit time b where the purchase price is lower than the average value of the purchase price in a certain period. Determined.

  Thereby, the purchase price of the electric power accompanying the electrical storage of the storage battery 141 can be reduced. In addition, by determining the weight value when the purchase unit price is relatively low, the shortage of the amount of power stored in the storage battery 141 is suppressed throughout the predetermined period without causing the optimal solution to fall into the local solution. be able to.

  Here, the case where the unit time a is simply a unit time higher than the average value of the purchase price and the unit time b is simply a unit time lower than the average value of the purchase price is illustrated. However, the unit time may be selected in descending order from the average value of the purchase price, and the weight value may be determined for the selected unit time so as to be proportional to the difference from the average value of the purchase price. In addition, by calculating optimal solutions in descending order from the average value of the purchase price, it is possible to grasp the total amount of power storage / discharge in the order of efficiency, and excessive power storage is suppressed. For example, it is possible to control the amount of power storage so that power storage exceeding expected power consumption is not performed in unit time when the purchase unit price is higher than the average value of purchase prices.

(Determination of weighted value (2))
Hereinafter, the determination method (2) of the weight value will be described. 6 and 7 are diagrams for explaining the weight value determination method (2) according to the first embodiment.

  In the case where the selling unit price of the second unit time is higher than the predetermined unit price by the purchase unit price of the first unit time, the weight value of the first unit time is easily calculated as an optimum solution including the operation of storing the storage battery 141. It is determined to do.

  Specifically, in the example shown in FIG. 6, when the unit price of unit time a is greater than the unit price of unit time b by a predetermined unit price, that is, the unit price of unit time a and the unit price of unit time b ( > Purchased unit price of unit time a) is equal to or greater than a predetermined unit price, the weight value of unit time a is determined so that the solution including the operation of storing the battery 141 is easily calculated as the optimal solution. .

  Thereby, insufficiency of the storage amount of the storage battery 141 can be suppressed in the second unit time (unit time b), and the appropriate solution can be obtained by discharging the storage battery 141 in the second unit time (unit time b). Without falling into a local solution, the difference between the power sales fee and the power purchase fee can be earned throughout the entire period.

  On the other hand, when the selling unit price of the second unit time is lower than the predetermined unit price by the purchase unit price of the first unit time, the solution including the operation of discharging the storage battery 141 is the optimal solution for the weighted value of the first unit time. It is determined so that it can be easily calculated.

  Specifically, in the example shown in FIG. 7, when the unit sales price of unit time b is lower than the unit price of unit time a by a predetermined unit price or more, that is, the unit price of unit time a and the unit price of unit time b ( In the case where the difference from <purchasing unit price of unit time a) is equal to or greater than a predetermined unit price, the weight value of unit time a is determined so that the solution including the operation of discharging the storage battery 141 is easily calculated as the optimal solution. .

  As a result, the power purchase fee can be suppressed in the first unit time (unit time a), and the optimal solution can be changed to the local solution by storing the storage battery 141 in the second unit time (unit time b). Without falling, the shortage of the amount of power stored in the storage battery 141 can be suppressed throughout the fixed period.

(Method for determining weighted value (3))
Hereinafter, the determination method (3) of the weight value will be described. The weight value determination method (3) is a determination method further applied to the weight value determination method (2).

  Specifically, the weight value of the first unit time (unit time a) is determined based on a switching loss between the operation of storing the storage battery 141 and the operation of discharging the storage battery 141.

  For example, as the switching loss increases, a larger unit price is set as a predetermined unit price to be compared with the difference between the purchase unit price for the first unit time (unit time a) and the sale unit price for the second unit time (unit time b). Alternatively, the weighting value of the first unit time (unit time a) is set so that the solution including the operation of storing the storage battery 141 (or the operation of discharging the storage battery 141) is less likely to be selected as the optimal solution as the switching loss increases. Is determined.

  As described above, since the switching loss is taken into consideration, it is possible to appropriately calculate the optimum solution.

(Determination method of weight value (4))
Hereinafter, the determination method (4) of the weight value will be described. The weight value determination method (4) is a determination method further applied to the weight value determination method (2).

  Specifically, the weighting value of the first unit time (unit time a) is the power consumption consumed by the load 120 or the amount of heat stored in the heat storage device (here, the amount of hot water stored in the hot water storage unit 160) during a certain period. Determined based on.

  For example, as power consumption consumed by the load 120 increases during a certain period, a solution including an operation of discharging the storage battery 141 is less likely to be selected as an optimal solution, and a solution including an operation of storing the storage battery 141 is more easily selected as an optimal solution. As described above, the weight value of the first unit time (unit time a) is determined. On the other hand, the smaller the power consumed by the load 120 in a certain period, the easier the solution including the operation of discharging the storage battery 141 is selected as the optimal solution, and the solution including the operation of storing the storage battery 141 is selected as the optimal solution. A weight value of the first unit time (unit time a) is determined so as to be difficult.

  Similarly, as the amount of heat stored in the heat storage device is larger, the solution including the operation of discharging the storage battery 141 is less likely to be selected as the optimal solution, and the solution including the operation of storing the storage battery 141 is more easily selected as the optimal solution. A weight value of one unit time (unit time a) is determined. On the other hand, as the amount of heat stored in the heat storage device is smaller, the solution including the operation of discharging the storage battery 141 is more easily selected as the optimal solution, and the solution including the operation of storing the storage battery 141 is less likely to be selected as the optimal solution. A weight value of one unit time (unit time a) is determined.

  As a result, the amount of power stored in the storage battery 141 can be maintained at an appropriate level throughout the predetermined period without causing the optimal solution to fall into the local solution.

(Determination of weighted value (5))
Hereinafter, the determination method (5) of the weight value will be described. The weight value determination method (5) is a determination method further applied to the weight value determination method (2).

  Specifically, the weight value of the first unit time (unit time a) is determined based on the number of times of switching between the operation of storing the storage battery 141 and the operation of discharging the storage battery 141 in a certain period.

  For example, the first unit time so that a solution including an operation in which the storage battery 141 stores electricity (or an operation in which the storage battery 141 discharges) is less likely to be selected as an optimal solution as the number of times of switching between storage and discharge is increased in a certain period. A weight value of (unit time a) is determined. On the other hand, the first unit is set so that the solution including the operation in which the storage battery 141 stores electricity (or the operation in which the storage battery 141 discharges) is more easily selected as the optimal solution as the number of times of switching between storage and discharge is smaller in a certain period. A weight value for time (unit time a) is determined.

  Thereby, the switching loss of the operation of the storage battery 141 can be efficiently suppressed throughout the certain period without the optimum solution falling into the local solution.

(Other methods for determining weight values)
In the weight value determination methods (1) to (5) described above, the weight value may be determined for each unit time or may be determined for a plurality of unit times. That is, when a period in which a common weight value is used is defined as a weighting period, the weighting period may be composed of one unit time or a plurality of unit times.

  In the weight value determination methods (1) to (5) described above, the operation of the storage battery 141 has been mainly described. However, the embodiment is not limited to this. An appropriate weight value may be determined in consideration of the operations of the PV unit 130, the fuel cell unit 150, and the hot water storage unit 160.

  For example, in the hot water storage unit 160, in consideration of a loss of heat amount due to the passage of time such as heat dissipation, the heat storage unit 160 is more likely to store heat as the difference between the unit time in which heat is stored and the unit time in which hot water is actually used is shorter. A bid price may be determined.

  Alternatively, the fuel cell 151 has the property that it is most efficient to output electric power at the rated output, and the efficiency becomes so high that heat can be radiated to the hot water storage unit 160. Therefore, an appropriate weight value may be determined in consideration of the output power (generated power) of the fuel cell 151 and the remaining hot water amount of the hot water storage unit 160.

(Control method)
Hereinafter, a control method according to the first embodiment will be described. FIG. 8 is a flowchart showing the control method according to the first embodiment. Specifically, FIG. 8 is a flowchart showing the operation of the HEMS 200.

  As shown in FIG. 8, in step 10, the HEMS 200 acquires energy rate information. Here, the HEMS 200 may acquire energy charge information via the network 60. Alternatively, the energy fee information may be stored in advance in the HEMS 200.

  In Step 20, the HEMS 200 acquires energy consumption prediction information. Here, the HEMS 200 may acquire energy consumption prediction information via the network 60. Alternatively, the energy consumption prediction information may be stored in advance in the HEMS 200.

  In step 30, the HEMS 200 acquires PV power generation amount prediction information. The HEMS 200 may acquire PV power generation amount prediction information via the network 60. Alternatively, the PV power generation amount prediction information may be stored in advance in the HEMS 200.

  In step 40A, the HEMS 200 sets a certain period. As described above, the certain period is a period to be referred to when determining the weight value. Between step 40A and step 40B, optimal solutions for every unit time included in the fixed period are calculated.

  In step 50, the HEMS 200 determines the weighting period. The weighting period may be constituted by one unit time or may be constituted by a plurality of unit times.

  In Step 60A, the HEMS 200 sets a unit time and sets a combination of each operation (element) of the set unit time. Between step 60A and step 60B, all combinations are applied brute force to the objective function.

  In step 70, the HEMS 200 determines whether or not the combination of the operations (elements) set in step 60A satisfies the constraint condition. For example, the power generation amount of the PV 131 does not violate the PV power generation amount prediction information, the power storage amount of the storage battery 141 is not smaller than the threshold, the power generation amount of the fuel cell 151 does not exceed the threshold, The condition is that the amount of stored hot water is not smaller than the threshold value. The HEMS 200 performs the process of step 80 when the determination result is “YES”. On the other hand, when the determination result is “NO”, the HEMS 200 returns to the process of Step 60A without performing the process of Step 80.

  In Step 80, the HEMS 200 determines a weight value corresponding to the combination of the actions (elements) set in Step 60A. Subsequently, the HEMS 200 calculates the solution of the objective function by applying the combination of actions (elements) and the weight value to the objective function.

  In step 90, the HEMS 200 calculates the optimal solution for the unit time set in step 60A based on the result obtained by applying all the combinations to the objective function in a brute force manner. In other words, the HEMS 200 determines an optimal solution from the solution group calculated in step 80.

(Function and effect)
In the first embodiment, the HEMS 200 calculates an optimal solution based on a weight value determined from parameters in a certain period longer than a unit time. Even if the optimal solution is calculated every unit time, the optimal solution does not fall into a local solution, and the calculation accuracy of the optimal solution can be improved.

[Other Embodiments]
Although the present invention has been described with reference to the above-described embodiments, it should not be understood that the descriptions and drawings constituting a part of this disclosure limit the present invention. From this disclosure, various alternative embodiments, examples and operational techniques will be apparent to those skilled in the art.

  In the embodiment, the HEMS 200 is exemplified as the control device. However, the embodiment is not limited to this. The control device may be the CEMS 20 or the smart server 40. Alternatively, the control device may be a BEMS (Building Energy Management System) or a FEMS (Factor Energy Management System).

  In the embodiment, the customer 10 includes a PV unit 130, a storage battery unit 140, a fuel cell unit 150, and a hot water storage unit 160. However, the consumer 10 may have any one of the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160.

  DESCRIPTION OF SYMBOLS 10 ... Consumer, 20 ... CEMS, 30 ... Substation, 31 ... Distribution line, 40 ... Smart server, 50 ... Power plant, 51 ... Transmission line, 60 ... Network, 100 ... Energy management system, 110 ... Distribution board, DESCRIPTION OF SYMBOLS 120 ... Load, 130 ... PV unit, 131 ... PV, 132 ... PCS, 140 ... Storage battery unit, 141 ... Storage battery, 142 ... PCS, 150 ... Fuel cell unit, 151 ... Fuel cell, 152 ... PCS, 160 ... Hot water storage unit, 200 ... HEMS, 210 ... reception unit, 220 ... transmission unit, 230 ... calculation unit, 240 ... control unit

Claims (9)

A control device for controlling the distributed power source, the power storage device or the heat storage device,
Optimal for each unit time with the operation of the distributed power supply, the power storage device or the heat storage device as an element, and at least one of the purchase price of power supplied from the grid and the sale price of power provided to the grid as a solution It has a calculation unit that calculates the solution,
The said calculating part calculates the said optimal solution based on the weighting value determined from the parameter in the fixed period longer than the said unit time.   The control device according to claim 1, wherein the parameter is a unit price of power supplied from the system.   The control device according to claim 1, wherein the parameter is a sales unit price of electric power provided to the system. The parameter is the unit price of power supplied from the grid,
The element includes an operation of the power storage device,
The weight value is determined so that a solution including an operation of discharging the power storage device is easily calculated as the optimal solution when the purchase unit price is relatively high,
2. The weight value is determined so that a solution including an operation of storing power in the power storage device is easily calculated as the optimal solution when the purchase unit price is relatively low. Control device. The parameters are the unit price of power supplied from the grid and the unit price of power supplied to the grid,
The element includes an operation of the power storage device,
The certain period includes a first unit time and a second unit time which is later in time than the first unit time,
In the case where the selling unit price of the second unit time is higher than a predetermined unit price by the purchase unit price of the first unit time, the weight value of the first unit time includes an operation in which the power storage device stores power. Is determined to be easily calculated as the optimal solution,
In the case where the selling unit price of the second unit time is lower than a predetermined unit price by the purchase unit price of the first unit time, the weight value of the first unit time includes an operation that discharges the power storage device. The control device according to claim 1, wherein the control device is determined so as to be easily calculated as the optimum solution.   The control device according to claim 5, wherein the weighted value of the first unit time is determined based on a switching loss between an operation of storing the power storage device and an operation of discharging the power storage device.   6. The control device according to claim 5, wherein the weight value of the first unit time is determined based on power consumption consumed by a load or a heat amount stored in the heat storage device during the certain period.   The weighted value of the first unit time is determined based on the number of times of switching between the operation of storing the power storage device and the operation of discharging the power storage device in the fixed period. The control device described. A control method for controlling the distributed power source, the power storage device or the heat storage device,
Optimal for each unit time with the operation of the distributed power supply, the power storage device or the heat storage device as an element, and at least one of the purchase price of power supplied from the grid and the sale price of power provided to the grid as a solution Step A for computing the solution,
In the step A, the optimal solution is calculated based on a weight value determined from a parameter in a fixed period longer than the unit time.

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