CN113326594A - Electric automobile battery replacement station and power grid interaction method and system based on microscopic traffic simulation - Google Patents
Electric automobile battery replacement station and power grid interaction method and system based on microscopic traffic simulation Download PDFInfo
- Publication number
- CN113326594A CN113326594A CN202110593336.3A CN202110593336A CN113326594A CN 113326594 A CN113326594 A CN 113326594A CN 202110593336 A CN202110593336 A CN 202110593336A CN 113326594 A CN113326594 A CN 113326594A
- Authority
- CN
- China
- Prior art keywords
- simulation
- model
- power
- battery
- vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/02—CAD in a network environment, e.g. collaborative CAD or distributed simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention provides an electric automobile battery replacement station and power grid interaction method and system based on microscopic traffic simulation, wherein the system comprises the following steps: the system comprises a power distribution module, a microscopic traffic simulation module, an electric automobile power changing station operator simulation module and an electric automobile power changing strategy simulation module. By means of the interactive simulation software architecture of the electric vehicle battery changing station and the power grid based on microscopic traffic simulation, under the high-precision simulation capability of the interactive characteristics of the battery changing station and the power grid, simulation and verification environments can be provided for various researches such as battery changing station site selection, battery and battery changing station quantity optimization, a charging and discharging scheduling strategy of auxiliary services participated by the battery changing station, a battery changing service induction information issuing strategy, battery delivery vehicle scheduling, electric vehicle battery changing destination and path selection and the like. The invention can effectively utilize the existing mature professional traffic simulation software and reduce the overall construction difficulty of the simulation system.
Description
Technical Field
The invention relates to an electric automobile power changing station and power grid interaction method and system based on microscopic traffic simulation, in particular to the technical field of power system simulation.
Background
The shortage of energy and the continuous deterioration of the environment due to the large exploitation and consumption of fossil energy have become more and more of a concern worldwide. The new energy automobile technology is considered to be an effective means for solving the problem of shortage of fossil fuels in the future, and is rapidly developed.
However, compared with a convenient refueling mode and a mature fuel distribution and storage technology of a fuel automobile, an energy supplementing mode of an electric automobile is still to be researched and further promoted. The Betterplace company in Israel as early as 2007 puts forward the concept of electric automobile battery replacement and establishes the first electric automobile battery replacement station in the world, and then in 2009, the national grid company in China puts forward an operation mode of 'battery replacement is main, plug-in is auxiliary, centralized charging and unified distribution', but because the ownership of battery property is unclear, the interface standard is not unified, the multi-party benefit is unbalanced and the like, the national grid company in 2013 gives up the battery replacement mode of an electric automobile, and the battery replacement mode also leaves the field of view of the public once. In recent years, with the initial success of the car in the power conversion mode facing consumers and the new energy of the northern car facing taxi network appointment and the like in the past, the slow development of the charging technology continuously restricts the popularization pace of the new energy car, and the power conversion mode is paid attention again.
Compared with the charging mode of the electric automobile, the charging mode has the greatest advantage of speed. Taking tesla Model S75D as an example, it also takes 80 minutes to fully fill using the super charger post. And the full-automatic power switching station pushed by the leading car can complete all power switching operations of one car in only 3 minutes, and even if extra time such as queuing and the like is considered, the superiority of a power switching mode in speed relative to charging is also obvious.
The battery replacement mode has the advantages that the time-space coupling in the interaction process of the electric vehicle and the power grid is reduced, and compared with a charging station, the battery replacement station is easier to participate in ordered charging and power grid interaction, so that the auxiliary service functions of peak clipping, valley filling, frequency modulation, standby and the like are realized.
Of course, the battery replacement mode has its own problems. Different from charging piles built on parking spaces of residential districts and working units, the power change station must simultaneously consider the operating characteristics of a power network and a traffic network, and the planning scheme and the evaluation of the problems related to site selection, battery pack quantification, power change network design and the like are technical difficulties.
In order to better study the influence of the electric automobile power changing station on the electric power system under different conditions, the power grid interaction characteristic of the electric automobile power changing station needs to be simulated. The existing research on the electric automobile power changing station mainly focuses on the aspects of power load prediction of the power changing station, battery pack demand planning, power changing station scheduling strategies and the like, and the research on the interaction characteristic of the electric automobile power changing station and a power grid is rare. In addition, most of the existing researches adopt an analysis method for simulating the user behaviors of the electric automobile based on a probability statistical model, on one hand, because China lacks statistical data of the user behaviors of the electric automobile, foreign early statistical data (such as a US family tourism investigation report of 2009 of the US department of transportation) are often adopted in the existing researches, the development of the electric automobile industry from the year of the data used in the report to the present is ignored, and the national situation difference between China and foreign countries is ignored; on the other hand, the model based on the probability statistical distribution is too macroscopic, and the difference of the interaction characteristics of the transformer substation and the power grid under the conditions of different cities, different traffic conditions, different geographical layouts of the power conversion stations and the like is difficult to describe.
The microscopic traffic simulation with a single vehicle as a basic unit can truly reflect the microscopic behaviors of the vehicle such as following, overtaking, lane change and the like on a road, and is more suitable for researching the interaction behavior of the electric vehicle and a power grid. The existing electric automobile related research based on microscopic traffic simulation mainly focuses on a charging mode, and due to the fact that a charging station and a battery replacement station are different in operation mode and power grid interaction mode, research results cannot be directly applied to the battery replacement station. In addition, traffic simulation itself is a very professional field, and the related research of the existing electric vehicle based on traffic simulation is greatly simplified, which results in the accuracy of the analysis result being greatly reduced.
Disclosure of Invention
The purpose of the invention is as follows: an electric vehicle battery replacement station and power grid interaction method and system based on microscopic traffic simulation are provided to solve the problems in the prior art.
The technical scheme is as follows: on the first hand, an electric automobile power exchanging station and power grid interaction method based on microscopic traffic simulation is provided, and is characterized by specifically comprising the following steps:
preprocessing data to be subjected to simulation analysis;
constructing a simulation model and importing corresponding analysis software;
initializing the state of a simulation object in a model in the analysis software;
generating a random continuation column according to a preset simulation duration;
the simulation is carried out from the time starting point;
judging whether the simulation meets a preset expected value or not after the simulation is finished;
when the preset expected value is met, processing the simulation result; otherwise, the simulation model is modified and the process returns to the step of initializing the state of the simulation object in the model in the analysis software.
In some implementations of the first aspect, the preprocessing further includes type conversion, model clipping and splicing, and data parameter collection and checking.
The simulation model comprises: the system comprises a power distribution system model, a microscopic traffic model, a power change station operator model and an electric automobile power change strategy model.
In some implementations of the first aspect, there is no data that requires direct interaction between the power distribution system model and the micro traffic model, so when constructing the software for inverse-positive analysis, the specific steps are as follows:
the requirements of simulating and analyzing a power distribution system and microcosmic traffic are developed synchronously;
selecting development software according to the requirements;
formulating a data transmission interface and a transmission mode;
designing an interface program and debugging after packaging;
and after the functions are tested independently, the whole linkage of the system is carried out.
In some implementation manners of the first aspect, in the simulation process, for the simulation execution flow within a single simulation step size, further:
acquiring and updating the simulation time of the current step length;
updating data at the corresponding data interface according to specific operation;
after the updated data is read out from the data interface, the data of the current operation object is correspondingly updated;
and executing necessary follow-up work in the current simulation step length.
In a second aspect, an electric vehicle power exchanging station and power grid interaction system based on microscopic traffic simulation is provided, and the system specifically includes:
the power distribution module is arranged for carrying out power distribution operation on the vehicle;
the microscopic traffic simulation module is arranged for simulating actual road conditions and vehicle motion characteristics encountered in the vehicle running process;
the electric automobile battery replacement station operator simulation module is set to carry out scheduling simulation on battery delivery vehicles among battery replacement stations of a battery replacement network according to preset vehicle and battery scheduling regulations;
the electric vehicle battery replacement strategy simulation module is set to simulate the progress state of a vehicle in the battery replacement process.
In some realizations of the second aspect, the power distribution module includes an electrical model, a scheduling model, an electric vehicle charging station model, and a power distribution simulation model.
The electrical model comprises: the system comprises a power transmission network equivalent active network model, a distributed power supply model, a distribution line model, a distribution transformer element electrical model, various adjustable or non-adjustable electrical load, distributed energy storage and other various distribution system element electrical models and electrical connection relation models among the models.
The scheduling model includes: the dispatching model is respectively dispatched with a superior power grid dispatching system, a distributed power supply, an adjustable power load, distributed energy storage and a dispatching instruction and data interface according to the electric automobile battery replacement station; the system comprises a distributed power supply scheduling strategy model, an adjustable power load scheduling strategy model and a distributed energy storage scheduling strategy model.
The electric automobile power changing station model is provided with an external interface which interacts with an electric automobile power changing station operator simulation module and an electric automobile power changing strategy simulation module.
The power distribution simulation model can be constructed according to the model data of a real power system, can be a distribution network planning model to be verified, can also be various published standard power system test example models, or various combinations of several conditions and modified models thereof; the power distribution simulation model can be realized by adopting existing mature power system simulation software such as BPA, PSASP, PSS/E, OpenDSS and GridLAB-D, or can be realized by self programming according to requirements, or can be various different combinations of various existing software and self programming.
In some implementations of the second aspect, the microscopic traffic simulation module is configured to simulate actual road conditions and vehicle motion characteristics encountered during vehicle travel; the simulator for realizing the module can adopt existing mature software such as Vissim, Paramics, Tsis/Corsim, can be realized by self programming according to requirements, or can be various different combinations of various existing software and self programming. When the microscopic traffic simulation module is used for simulation analysis, the microscopic traffic simulation module can be constructed according to real microscopic traffic simulation data, can be a traffic planning model to be verified, can be published various standard electric power system test example models, or can be various combinations of several conditions and modified models thereof.
When the actual road condition met in the driving process of the vehicle is simulated, a microscopic traffic model is established according to the actual situation, wherein the microscopic traffic model comprises the following components: road model, city area model, vehicle motion characteristic model.
According to the energy supplementing mode of the vehicle, the vehicle is further divided into a vehicle with a power conversion mode and a vehicle without the power conversion mode in the vehicle motion characteristic model. The vehicle model with the battery replacement mode is provided with an external interface which interacts with an electric vehicle battery replacement station operator simulation module.
According to whether the vehicle motion characteristic model participates in the operation of the battery replacement network, the vehicle motion characteristic model is further divided into a battery distribution vehicle model and a non-battery distribution vehicle model; the battery distribution vehicle model can receive, decide, respond and execute a scheduling instruction according to a preset data interaction interface; the scheduling instruction originates from a charging station operator.
In some implementation manners of the second aspect, the electric vehicle battery replacement station operator simulation module includes a vehicle and battery scheduling simulation program in a battery replacement station within an operator jurisdiction and a scheduling simulation program for constructing a battery delivery vehicle between battery replacement stations of a battery replacement network.
The vehicle and battery scheduling simulation program in the battery replacement station in the operator jurisdiction can simulate the total number and the number of the battery replacement parking places corresponding to different vehicle types in all the battery replacement stations in the operator jurisdiction, the current battery replacement progress of the currently replaced vehicles and the current number of the vehicles waiting in line; the number of the batteries which are fully charged currently, the number and the state of charge of the batteries which are not charged after being replaced, the number and the respective charging power of the batteries which are being charged, and the current states of charge of all the batteries; and the complete battery replacement process of driving different types of batteries to be replaced in all battery replacement stations in the operator jurisdiction into the battery replacement station, participating in queuing for waiting, starting battery replacement, ending battery replacement and driving away from the battery replacement station can also be simulated.
The simulation module of the electric automobile power changing station operator is provided with an interface with the power distribution module, and can simulate the process of the operator for executing the ordered charging and even discharging strategies of the battery according to the power price information and the dispatching instruction issued by the power grid dispatching department and feeding back the strategies to the power grid dispatching department; through the interface with the electric automobile battery replacement strategy simulation module, the battery state change analysis before and after the battery replacement of the electric automobile in the battery replacement mode can be realized.
The scheduling simulation program for constructing the battery distribution vehicle between the battery swapping stations of the battery swapping network is provided with an interface for performing data interaction with the microscopic traffic simulation module; the battery transfer scheduling method can simulate the battery transfer scheduling scheme decision process of a battery transfer station operator according to the states of battery transfer vehicles and batteries in all battery transfer stations in the jurisdiction of the battery transfer station operator, the states of all battery distribution vehicles and traffic information obtained from a microscopic traffic simulation software interface.
In some implementations of the second aspect, the electric vehicle battery replacement strategy simulation module has a data interface for interacting with the microscopic traffic simulation module, and an interface for interacting with an electric vehicle battery replacement station operator simulation module.
Has the advantages that: the invention provides an electric vehicle battery replacement station and power grid interaction method and system based on microscopic traffic simulation, and due to the fact that a simulation software framework has strong openness, the method can include various existing research achievements of battery replacement station site selection, battery and battery replacement parking place quantity optimization, a charging and discharging scheduling strategy of battery replacement station participating in auxiliary service, a battery replacement service induction information issuing strategy, battery delivery vehicle scheduling, electric vehicle battery replacement destination and path selection and the like, and test and verification are carried out on the electric vehicle battery replacement station and power grid interaction system. In addition, the simulation software architecture has good compatibility, the existing power system simulation software such as BPA, PSASP, PSS/E and the like and the existing microscopic traffic simulation software such as Vissim, Paramics, Tsis/Corsim and the like can be utilized to a great extent, the overall construction difficulty of the simulation system is reduced, and the system construction efficiency is improved. The simulation software framework fully exerts the advantages brought by the technical intersection of multiple disciplines (particularly power engineering and traffic engineering), can accurately simulate the complex mutual influence among the electric automobile in the battery replacement mode, the battery replacement station and operators thereof, the regional power distribution system and the regional traffic system, and provides powerful simulation verification technical support for the development of the new energy automobile industry.
Drawings
FIG. 1 is a diagram of a complete simulation process based on the simulation software architecture of the present invention.
FIG. 2 is a flow chart of the construction of an emulation software system based on the emulation software architecture of the present invention.
Fig. 3 is a schematic diagram illustrating an execution flow of a power distribution system simulation program in a single simulation step size in a simulation process based on the simulation software architecture of the present invention.
Fig. 4 is a schematic diagram of an execution flow of a microscopic traffic simulation program within a single simulation step in a simulation process based on the simulation software architecture of the present invention.
Fig. 5 is a schematic diagram of an execution flow of a power station swapping operator simulation program within a single simulation step length in a simulation process based on the simulation software architecture of the present invention.
Fig. 6 is a schematic diagram of an execution flow of an electric vehicle swapping strategy simulation program within a single simulation step length in a simulation process based on the simulation software architecture of the present invention.
FIG. 7 is a diagram of a system architecture according to the present invention.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art, that the present invention may be practiced without one or more of these specific details. In other instances, well-known features have not been described in order to avoid obscuring the invention.
Example one
An electric vehicle power change station and power grid interaction simulation method based on microscopic traffic simulation is provided, and as shown in fig. 1, the method specifically comprises the following steps:
step one, preprocessing data;
secondly, building a model and importing corresponding software;
initializing the state of a simulation object in a model in software;
generating a random continuation row according to a preset simulation duration;
fifthly, simulating from the time starting point;
step six, judging whether the simulation meets a preset expected value or not after the simulation is finished;
step seven, processing the simulation result when the preset expected value is met; otherwise, the simulation model is modified and the process returns to the step of initializing the state of the simulation object in the model in the analysis software.
Specifically, the data is preprocessed, including but not limited to type conversion of model files, cutting and splicing of models, and collection of model parameters and kernel peer-to-peer.
The constructed model comprises the following steps: the system comprises a power distribution system model, a microscopic traffic model, a power change station operator model and an electric automobile power change strategy model.
And according to the preset simulation duration, the generated random continuation line accords with the probability distribution corresponding to the requirement.
The processing for the simulation result includes but is not limited to saving various required simulation results, drawing necessary result graphs, outputting prompt information and data, and the like.
Example two
For the fact that data needing direct interaction does not exist between the power distribution system model and the micro traffic model, when software for inverse-positive analysis is constructed, as shown in fig. 2, the specific implementation steps are as follows:
the method comprises the following steps of firstly, synchronously developing the requirements of simulating and analyzing a power distribution system and microcosmic traffic;
selecting development software according to requirements;
step three, formulating a data transmission interface and a transmission mode;
designing an interface program and debugging after packaging;
and step five, performing the integral linkage of the system after independently testing the functions.
Specifically, the software development is further selected as follows: firstly, according to whether all or part of simulation software is required to be developed by self, selecting or developing the power distribution system simulation software and the microscopic traffic simulation software synchronously; secondly, on the basis of selection or development work of power distribution system simulation software and microscopic traffic simulation software, simulation demand analysis of a power change station operator and simulation demand analysis of an electric vehicle power change strategy are developed simultaneously; and finally, according to whether all or part of simulation software is required to be developed by self, the selection or development of simulation software of a power exchange station operator and simulation software of an electric vehicle power exchange strategy is synchronously developed.
EXAMPLE III
Aiming at the single simulation step length in the simulation process, the method for executing the simulation power distribution program in the single simulation step length in the simulation process is provided. Specifically, as shown in fig. 3, the method includes the following steps:
step 1, acquiring current step size simulation time, and updating the corresponding current step size simulation time in simulation software;
step 2, updating the scheduling strategy, and updating the output or consumption corresponding to the scheduling strategy;
step 3, updating the electricity price and the scheduling instruction, and sending the electricity price and the scheduling instruction to an operator interface of the power change station;
step 4, after the data at the interface of the power swapping station is updated, reading the updated data of the interface of the power swapping station from the interface;
step 5, circularly judging whether the interface of the power exchanging station has data updating; updating the charging and discharging power information of the battery replacement station according to the data updated by the interface of the battery replacement station when the judgment result is that the data updating exists;
and 6, executing subsequent simulation work in the current simulation step length.
Specifically, the updated scheduling strategy comprises a power output scheduling strategy in the power transmission equivalent network, an unadjustable load power scheduling strategy, an execution distributed power scheduling strategy, an adjustable load scheduling strategy and a distributed energy storage scheduling strategy.
And updating the electricity price and the dispatching instruction issued by the superior power grid dispatching system at the current time, and sending the electricity price and the dispatching instruction to an operator interface of the power conversion station.
Example four
Aiming at the single simulation step length in the simulation process, the execution method of the microscopic traffic simulation program in the single simulation step length in the simulation process is provided. Specifically, as shown in fig. 4, the method includes the following steps:
step 1, acquiring current step size simulation time, and updating the corresponding current step size simulation time in simulation software;
step 2, updating traffic information of various types of vehicles in the traffic network according to the live simulation result; wherein the live simulation specifically comprises simulation of road and traffic control states; the traffic information includes driving state and position information;
step 3, sending the updated traffic information of each electric vehicle in the battery replacement mode to an interface for carrying out an electric vehicle battery replacement strategy simulation program;
step 4, circularly judging whether the data at the interface of the automobile battery replacement strategy is updated;
step 5, after the data at the power change strategy interface is updated, judging whether each battery delivery vehicle and each power change mode electric vehicle reach a target power change station; if yes, setting a reached state, sending the information of the delivery vehicle to a power exchange station interface, and simultaneously, transferring the control right of the vehicle model object to a simulation software program of a power exchange station operator;
step 6, updating the battery charge states of all the vehicles in the battery replacement mode;
and 7, executing subsequent simulation work in the current simulation step length.
EXAMPLE five
Aiming at the single simulation step length in the simulation process, the method for executing the simulation program of the power station changing operator in the single simulation step length in the simulation process is provided. Specifically, as shown in fig. 5, the method includes the following steps:
step 1, acquiring current step size simulation time, and updating the corresponding current step size simulation time in simulation software;
step 2, for each power changing station, adding the newly arrived power changing vehicle into a corresponding queue specific position or starting to change the power of the newly arrived power changing vehicle according to the reservation condition and the current queuing state of the newly arrived power changing vehicle;
step 3, when a newly arrived battery distribution vehicle is available, adding the newly arrived battery distribution vehicle into a vehicle queue waiting for distribution, and updating the state of an idle battery bank in the station;
step 4, updating the current battery replacement progress of the vehicle in battery replacement;
step 5, judging the situation of completing battery replacement of the vehicle, if the battery replacement of the vehicle is completed, updating the state of the battery replacement requirement of the vehicle, sending the information to the microscopic traffic simulation program, and simultaneously giving the control right to the microscopic traffic simulation program, and entering step 6; otherwise, go to step 7;
step 6, updating a battery swapping waiting queue, namely moving the vehicles which complete battery swapping out of the queue, and then setting the first vehicle in the queue to be in a battery swapping state;
step 7, continuously executing or adjusting the current power station scheduling strategy and then executing according to the power price and the scheduling instruction issued by the power grid scheduling system;
step 8, sending the charging and discharging power of the power exchanging station to a power distribution system simulation program interface;
and 9, executing subsequent simulation work in the current simulation step length.
EXAMPLE six
Aiming at the single simulation step length in the simulation process, the method for executing the simulation program of the electric vehicle battery replacement strategy in the single simulation step length in the simulation process is provided. Specifically, as shown in fig. 6, the method includes the following steps:
step 1, acquiring current step size simulation time, and updating the corresponding current step size simulation time in simulation software;
step 2, acquiring traffic information of each battery replacement vehicle from the battery replacement interface, and updating the battery state of each battery replacement vehicle;
step 3, switching the power conversion demand state according to the current electric quantity of the vehicle;
step 4, judging whether the current vehicle needs to be changed according to a preset rule; if yes, executing step 5; otherwise, executing step 7;
step 5, searching the power change service induction information issued by the power change station near the vehicle, selecting the power change station according to a set strategy after integrating the current electric quantity, the distance from the power change station, the road condition and the service preferential condition, and planning a driving path;
step 6, sending the information after the current vehicle decision to a microscopic traffic simulation program interface;
and 7, executing subsequent simulation work in the current simulation step length.
EXAMPLE seven
An electric vehicle power exchanging station and power grid interactive simulation system based on microscopic traffic simulation is provided, as shown in fig. 7, the system specifically includes:
the power distribution module is arranged for carrying out power distribution operation on the vehicle;
the microscopic traffic simulation module is arranged for simulating actual road conditions and vehicle motion characteristics encountered in the vehicle running process;
the electric automobile battery replacement station operator simulation module is set to carry out scheduling simulation on battery delivery vehicles among battery replacement stations of a battery replacement network according to preset vehicle and battery scheduling regulations;
the electric vehicle battery replacement strategy simulation module is set to simulate the progress state of a vehicle in the battery replacement process.
In a further embodiment, the power distribution module comprises an electrical model, a scheduling model, an electric automobile power exchange station model and a power distribution simulation model.
Wherein the electrical model includes, but is not limited to, the electrical model of the following power distribution system: the system comprises a power transmission network equivalent active network model, a distributed power supply model, a distribution line model, a distribution transformer element electrical model, various adjustable or non-adjustable electrical load, distributed energy storage and other various distribution system element electrical models and electrical connection relation models among the models.
The scheduling model includes, but is not limited to, the following scheduling models of the power distribution system: the dispatching model is respectively dispatched with a superior power grid dispatching system, a distributed power supply, an adjustable power load, distributed energy storage and a dispatching instruction and data interface according to the electric automobile battery replacement station; the system comprises a distributed power supply scheduling strategy model, an adjustable power load scheduling strategy model and a distributed energy storage scheduling strategy model.
The electric automobile power changing station model is provided with an external interface interacting with an electric automobile power changing station operator simulation module and an electric automobile power changing strategy simulation module, and does not need to be provided with a detailed vehicle and battery scheduling model inside the power changing station.
The power distribution simulation model can be constructed according to the real power system model data, can be a distribution network planning model to be verified, can be various published standard power system test example models, or various combinations of the above and modified models. The power distribution simulation model can be realized by adopting existing mature power system simulation software such as BPA, PSASP, PSS/E, OpenDSS, GridLAB-D and the like, or can be realized by self programming according to requirements, or various different combinations of a plurality of existing software and self programming.
In a further embodiment, the microscopic traffic simulation module is configured to simulate actual road conditions and vehicle motion characteristics encountered during vehicle travel. Besides existing mature software such as Vissim, Paramics, Tsis/Corsim and the like, the simulator for realizing the module can be realized by self programming according to requirements, or various different combinations of various existing software and self programming.
Specifically, when the actual road conditions encountered in the driving process of the vehicle are simulated, a microscopic traffic model is established according to the actual conditions, and the microscopic traffic model includes but is not limited to: road model, city area model, vehicle motion characteristic model.
Wherein the elements in the road model include, but are not limited to: roads such as highways, urban roads, factories and mines roads, forest roads, country roads and the like. Elements in the urban area model include, but are not limited to: traffic elements such as communities, commercial districts, hospitals, large-scale meeting places, road intersections, toll points, public traffic priority rules and the like. Elements in the vehicle motion characteristics model include, but are not limited to: the model of the four types of vehicles including mini-cars, passenger cars, large and medium-sized vehicles and unshaped vehicles.
According to the energy supplementing mode of the vehicle, the vehicle is further divided into a vehicle with a power conversion mode and a vehicle without the power conversion mode in the vehicle motion characteristic model. The vehicle model with the battery replacement mode is provided with an external interface which interacts with an electric vehicle battery replacement station operator simulation module.
The vehicle motion characteristic models are further divided into a battery distribution vehicle model and a non-battery distribution vehicle model according to whether the vehicle participates in the operation of the battery replacement network. The battery distribution vehicle model can receive, decide, respond and execute a scheduling instruction according to a preset data interaction interface. The scheduling instruction originates from a charging station operator.
In a further embodiment, the electric vehicle battery replacement station operator simulation module comprises a vehicle and battery scheduling simulation program in a battery replacement station in an operator jurisdiction and a scheduling simulation program for a battery delivery vehicle between battery replacement stations for constructing a battery replacement network.
The system comprises a power conversion station, a power conversion system and a battery scheduling simulation program, wherein the vehicle and battery scheduling simulation program in the power conversion station in an operator jurisdiction can simulate the total number and the number of power conversion parking places which correspond to different vehicle types in all power conversion stations in the operator jurisdiction, the current power conversion progress of the currently-converting vehicles, and the current number of vehicles waiting in line; the number of batteries currently fully charged, the number and state of charge of batteries that have not been charged after being replaced, the number and respective charging powers of batteries being charged, and the current state of charge of all batteries. The method can also simulate the complete battery replacement process of different types of vehicles to be replaced in all battery replacement stations in the operator jurisdiction, such as entering the battery replacement station, participating in queuing for waiting, starting battery replacement, ending battery replacement and leaving the battery replacement station.
In addition, the program has an interface with the power distribution module, and can simulate the process of an operator for executing the battery ordered charging and even discharging strategies according to power generation price information, scheduling instructions and the like generated by a power grid scheduling department and feeding back the strategies to the power grid scheduling department. Through the interface with the electric automobile battery replacement strategy simulation module, the battery state change analysis before and after the battery replacement of the electric automobile in the battery replacement mode can be realized.
The scheduling simulation program for constructing the battery distribution vehicle between the battery replacement stations of the battery replacement network is provided with an interface for data interaction with the microscopic traffic simulation module, and can simulate the process of making a battery distribution scheduling scheme decision by a battery replacement station operator according to the battery replacement vehicles and the battery states in all the battery replacement stations in the jurisdiction of the operator, the states of all the battery distribution vehicles and traffic information obtained from the microscopic traffic simulation software interface. Meanwhile, the program can also simulate the process of the change of the number and the state of the batteries in the battery changing station before and after the battery distribution vehicle drives in or out of the battery changing station.
In a further embodiment, the electric vehicle battery replacement strategy simulation module is provided with a data interface for interacting with the microscopic traffic simulation module and an interface for interacting data with the electric vehicle battery replacement station operator simulation module. The traffic information of all the electric vehicles in the power conversion mode in the simulation area can be obtained through the data interface interacting with the microscopic traffic simulation module, and the process that the battery charge state changes along with the traffic condition is simulated. Through an interface for data interaction with an electric vehicle power change station operator simulation module, power change service induction information issued by all power change station operators in a nearby area can be obtained, and processes of power change station selection, route optimization of driving to the power change station and power change service reservation with the power change station are simulated according to the information. Besides, the electric vehicle power exchange strategy simulation module can simulate the process of switching the power exchange requirements according to the current electric quantity information of the electric vehicle.
As noted above, while the present invention has been shown and described with reference to certain preferred embodiments, it is not to be construed as limited thereto. Various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. An electric automobile power changing station and power grid interaction method based on microscopic traffic simulation is characterized by comprising the following steps:
preprocessing data to be subjected to simulation analysis;
constructing a simulation model and importing corresponding analysis software;
initializing the state of a simulation object in a model in the analysis software;
generating a random continuation column according to a preset simulation duration;
the simulation is carried out from the time starting point;
judging whether the simulation meets a preset expected value or not after the simulation is finished;
when the preset expected value is met, processing the simulation result; otherwise, the simulation model is modified and the process returns to the step of initializing the state of the simulation object in the model in the analysis software.
2. The electric vehicle power exchanging station and power grid interaction method based on micro traffic simulation as claimed in claim 1,
the preprocessing further comprises the steps of carrying out type conversion on the data file, cutting and splicing the model, and collecting and checking data parameters;
the simulation model comprises: the system comprises a power distribution system model, a microscopic traffic model, a power change station operator model and an electric automobile power change strategy model.
3. The interaction method of the electric automobile power exchanging station and the power grid based on the micro traffic simulation as claimed in claim 2, wherein data needing direct interaction does not exist between the power distribution system model and the micro traffic model, so when software for inverse analysis is constructed, the specific steps are as follows:
the requirements of simulating and analyzing a power distribution system and microcosmic traffic are developed synchronously;
selecting development software according to the requirements;
formulating a data transmission interface and a transmission mode;
designing an interface program and debugging after packaging;
and after the functions are tested independently, the whole linkage of the system is carried out.
4. The electric vehicle power exchanging station and power grid interaction method based on micro traffic simulation as claimed in claim 1,
in the simulation process, the simulation execution flow in the single simulation step length further comprises the following steps:
acquiring and updating the simulation time of the current step length;
updating data at the corresponding data interface according to specific operation;
after the updated data is read out from the data interface, the data of the current operation object is correspondingly updated;
and executing necessary follow-up work in the current simulation step length.
5. An electric automobile power changing station and power grid interaction system based on microscopic traffic simulation is used for realizing the method of any one of claims 1-4, and is characterized by specifically comprising the following steps:
the power distribution module is arranged for carrying out power distribution operation on the vehicle;
the microscopic traffic simulation module is arranged for simulating actual road conditions and vehicle motion characteristics encountered in the vehicle running process;
the electric automobile battery replacement station operator simulation module is set to carry out scheduling simulation on battery delivery vehicles among battery replacement stations of a battery replacement network according to preset vehicle and battery scheduling regulations;
the electric vehicle battery replacement strategy simulation module is set to simulate the progress state of a vehicle in the battery replacement process.
6. The electric vehicle power changing station and power grid interaction system based on micro traffic simulation as claimed in claim 5,
the power distribution module comprises an electrical model, a scheduling model, an electric automobile power change station model and a power distribution simulation model;
the electrical model comprises: the method comprises the following steps that a power transmission network equivalent active network model, a distributed power supply model, a distribution line model, a distribution transformer element electrical model, various adjustable or non-adjustable power load, distributed energy storage and other various distribution system element electrical models and electrical connection relation models among the models are adopted;
the scheduling model includes: the dispatching model is respectively dispatched with a superior power grid dispatching system, a distributed power supply, an adjustable power load, distributed energy storage and a dispatching instruction and data interface according to the electric automobile battery replacement station; the distributed energy storage system comprises a distributed power supply scheduling strategy model, an adjustable power load scheduling strategy model and a distributed energy storage scheduling strategy model;
the electric automobile power changing station model is provided with an external interface which interacts with an electric automobile power changing station operator simulation module and an electric automobile power changing strategy simulation module;
the power distribution simulation model can be constructed according to the model data of a real power system, can be a distribution network planning model to be verified, can also be various published standard power system test example models, or various combinations of several conditions and modified models thereof; the power distribution simulation model can be realized by adopting existing mature power system simulation software such as BPA, PSASP, PSS/E, OpenDSS and GridLAB-D, or can be realized by self programming according to requirements, or can be various different combinations of various existing software and self programming.
7. The electric vehicle power changing station and power grid interaction system based on micro traffic simulation as claimed in claim 5,
the microscopic traffic simulation module is arranged to simulate actual road conditions and vehicle motion characteristics encountered in the vehicle driving process; the simulator for realizing the module can adopt existing mature software such as Vissim, Paramics and Tsis/Corsim, can be realized by self programming according to requirements, or can be various different combinations of various existing software and self programming; when the microscopic traffic simulation module is used for simulation analysis, the microscopic traffic simulation module can be constructed according to real microscopic traffic simulation data, can be a traffic planning model to be verified, can also be various published standard electric power system test example models, or various combinations of several conditions and modified models thereof;
when the actual road condition met in the driving process of the vehicle is simulated, a microscopic traffic model is established according to the actual situation, wherein the microscopic traffic model comprises the following components: a road model, an urban area model and a vehicle motion characteristic model;
according to the energy supplementing mode of the vehicle, the vehicle is further divided into a vehicle with a power conversion mode and a vehicle without the power conversion mode in the vehicle motion characteristic model; the vehicle model with the battery replacement mode is provided with an external interface which interacts with an electric vehicle battery replacement station operator simulation module;
according to whether the vehicle motion characteristic model participates in the operation of the battery replacement network, the vehicle motion characteristic model is further divided into a battery distribution vehicle model and a non-battery distribution vehicle model; the battery distribution vehicle model can receive, decide, respond and execute a scheduling instruction according to a preset data interaction interface; the scheduling instruction originates from a charging station operator.
8. The electric vehicle power changing station and power grid interaction system based on micro traffic simulation as claimed in claim 5,
the electric automobile battery replacement station operator simulation module comprises a vehicle and battery scheduling simulation program in a battery replacement station in an operator jurisdiction and a scheduling simulation program of a battery delivery vehicle between battery replacement stations for constructing a battery replacement network;
the vehicle and battery scheduling simulation program in the battery replacement station in the operator jurisdiction can simulate the total number and the number of the battery replacement parking places corresponding to different vehicle types in all the battery replacement stations in the operator jurisdiction, the current battery replacement progress of the currently replaced vehicles and the current number of the vehicles waiting in line; the number of the batteries which are fully charged currently, the number and the state of charge of the batteries which are not charged after being replaced, the number and the respective charging power of the batteries which are being charged, and the current states of charge of all the batteries; the complete battery replacement process of driving different types of batteries to be replaced in all battery replacement stations in an operator jurisdiction into the battery replacement stations, participating in queuing for waiting, starting battery replacement, ending battery replacement and driving away from the battery replacement stations can also be simulated;
the simulation module of the electric automobile power changing station operator is provided with an interface with the power distribution module, and can simulate the process of the operator for executing the ordered charging and even discharging strategies of the battery according to the power price information and the dispatching instruction issued by the power grid dispatching department and feeding back the strategies to the power grid dispatching department; through the interface with the electric automobile battery replacement strategy simulation module, the battery state change analysis before and after the battery replacement of the electric automobile in the battery replacement mode can be realized.
9. The electric vehicle power changing station and power grid interaction system based on micro traffic simulation as claimed in claim 8,
the scheduling simulation program for constructing the battery distribution vehicle between the battery swapping stations of the battery swapping network is provided with an interface for performing data interaction with the microscopic traffic simulation module; the battery transfer scheduling method can simulate the battery transfer scheduling scheme decision process of a battery transfer station operator according to the states of battery transfer vehicles and batteries in all battery transfer stations in the jurisdiction of the battery transfer station operator, the states of all battery distribution vehicles and traffic information obtained from a microscopic traffic simulation software interface.
10. The electric vehicle power changing station and power grid interaction system based on micro traffic simulation as claimed in claim 5,
the electric automobile battery replacement strategy simulation module is provided with a data interface for interacting with the microscopic traffic simulation module and an interface for interacting data with the electric automobile battery replacement station operator simulation module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110593336.3A CN113326594B (en) | 2021-05-28 | 2021-05-28 | Electric vehicle battery replacement station and power grid interaction method and system based on microscopic traffic simulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110593336.3A CN113326594B (en) | 2021-05-28 | 2021-05-28 | Electric vehicle battery replacement station and power grid interaction method and system based on microscopic traffic simulation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113326594A true CN113326594A (en) | 2021-08-31 |
| CN113326594B CN113326594B (en) | 2023-08-01 |
Family
ID=77422243
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110593336.3A Active CN113326594B (en) | 2021-05-28 | 2021-05-28 | Electric vehicle battery replacement station and power grid interaction method and system based on microscopic traffic simulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113326594B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114006390A (en) * | 2021-10-29 | 2022-02-01 | 国网江苏省电力有限公司苏州供电分公司 | Electric vehicle charging load participation power grid interaction simulation method and system |
| CN117408463A (en) * | 2023-10-20 | 2024-01-16 | 重庆大学 | Intelligent electric animal skip power station replacement site selection and scheduling method and system |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20110037523A (en) * | 2009-10-07 | 2011-04-13 | 한국에너지기술연구원 | Electric vehicle charging and discharging system and method using the contactless power transmission method |
| CN103631642A (en) * | 2013-12-13 | 2014-03-12 | 国家电网公司 | Ecological simulation-based electric car battery charging and replacing service network simulation system and method |
| CN103646295A (en) * | 2013-11-28 | 2014-03-19 | 东南大学 | Service station general model-based electric vehicle battery charging/swapping network integrated scheduling method |
| CN103810539A (en) * | 2014-02-25 | 2014-05-21 | 华北电力大学 | Optimal capacity configuration method considering availability of power conversion service for electric automobile converter station |
| CN106599390A (en) * | 2016-11-23 | 2017-04-26 | 国网浙江省电力公司电动汽车服务分公司 | Method for calculating charging load considering time-space stochastic characteristics of electric taxi |
| CN107844925A (en) * | 2017-12-19 | 2018-03-27 | 天津大学 | Consider that electric automobile changes the active distribution network space truss project method of power mode |
| CN109146201A (en) * | 2018-09-13 | 2019-01-04 | 三峡大学 | Filling based on cooperative game changes the integrated power station micro-capacitance sensor Optimization Scheduling of storage |
| CN109256800A (en) * | 2018-09-18 | 2019-01-22 | 三峡大学 | A kind of region, which is filled, changes the integrated power station micro-capacitance sensor group's coordination optimization dispatching method of storage |
| CN109523051A (en) * | 2018-09-18 | 2019-03-26 | 国网浙江省电力有限公司经济技术研究院 | A kind of electric car charging Real time optimal dispatch method |
| CN109583708A (en) * | 2018-11-08 | 2019-04-05 | 国网浙江省电力有限公司经济技术研究院 | The method for building up of multiple agent microcosmic traffic Assignment Model |
| CN109583136A (en) * | 2018-12-28 | 2019-04-05 | 上海电力学院 | Electric car based on schedulable potentiality, which fills, changes storage one station method for establishing model |
| CN110084443A (en) * | 2019-05-23 | 2019-08-02 | 哈尔滨工业大学 | A kind of electrical changing station optimal operation model analysis method based on QPSO optimization algorithm |
| CN112418742A (en) * | 2021-01-20 | 2021-02-26 | 南方电网数字电网研究院有限公司 | Network double-layer control method for electric automobile battery replacement station with information and physical fusion |
-
2021
- 2021-05-28 CN CN202110593336.3A patent/CN113326594B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20110037523A (en) * | 2009-10-07 | 2011-04-13 | 한국에너지기술연구원 | Electric vehicle charging and discharging system and method using the contactless power transmission method |
| CN103646295A (en) * | 2013-11-28 | 2014-03-19 | 东南大学 | Service station general model-based electric vehicle battery charging/swapping network integrated scheduling method |
| CN103631642A (en) * | 2013-12-13 | 2014-03-12 | 国家电网公司 | Ecological simulation-based electric car battery charging and replacing service network simulation system and method |
| CN103810539A (en) * | 2014-02-25 | 2014-05-21 | 华北电力大学 | Optimal capacity configuration method considering availability of power conversion service for electric automobile converter station |
| CN106599390A (en) * | 2016-11-23 | 2017-04-26 | 国网浙江省电力公司电动汽车服务分公司 | Method for calculating charging load considering time-space stochastic characteristics of electric taxi |
| CN107844925A (en) * | 2017-12-19 | 2018-03-27 | 天津大学 | Consider that electric automobile changes the active distribution network space truss project method of power mode |
| CN109146201A (en) * | 2018-09-13 | 2019-01-04 | 三峡大学 | Filling based on cooperative game changes the integrated power station micro-capacitance sensor Optimization Scheduling of storage |
| CN109256800A (en) * | 2018-09-18 | 2019-01-22 | 三峡大学 | A kind of region, which is filled, changes the integrated power station micro-capacitance sensor group's coordination optimization dispatching method of storage |
| CN109523051A (en) * | 2018-09-18 | 2019-03-26 | 国网浙江省电力有限公司经济技术研究院 | A kind of electric car charging Real time optimal dispatch method |
| CN109583708A (en) * | 2018-11-08 | 2019-04-05 | 国网浙江省电力有限公司经济技术研究院 | The method for building up of multiple agent microcosmic traffic Assignment Model |
| CN109583136A (en) * | 2018-12-28 | 2019-04-05 | 上海电力学院 | Electric car based on schedulable potentiality, which fills, changes storage one station method for establishing model |
| CN110084443A (en) * | 2019-05-23 | 2019-08-02 | 哈尔滨工业大学 | A kind of electrical changing station optimal operation model analysis method based on QPSO optimization algorithm |
| CN112418742A (en) * | 2021-01-20 | 2021-02-26 | 南方电网数字电网研究院有限公司 | Network double-layer control method for electric automobile battery replacement station with information and physical fusion |
Non-Patent Citations (1)
| Title |
|---|
| 谢平平 等: "计及电动汽车换电站储能的负荷频率控制", 《电工技术学报》, vol. 31, no. 12, pages 193 - 203 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114006390A (en) * | 2021-10-29 | 2022-02-01 | 国网江苏省电力有限公司苏州供电分公司 | Electric vehicle charging load participation power grid interaction simulation method and system |
| CN114006390B (en) * | 2021-10-29 | 2023-11-07 | 国网江苏省电力有限公司苏州供电分公司 | Electric vehicle charging load participation power grid interaction simulation method and system |
| CN117408463A (en) * | 2023-10-20 | 2024-01-16 | 重庆大学 | Intelligent electric animal skip power station replacement site selection and scheduling method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113326594B (en) | 2023-08-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wu et al. | A novel fast-charging stations locational planning model for electric bus transit system | |
| Shen et al. | Optimization models for electric vehicle service operations: A literature review | |
| Chaudhari et al. | Agent-based aggregated behavior modeling for electric vehicle charging load | |
| CN109398149B (en) | Intelligent electric vehicle charging and discharging system based on distributed energy application and operation control method thereof | |
| CN110880054B (en) | Planning method for electric network car-booking charging and battery-swapping path | |
| Hossain et al. | A comprehensive review on the integration of electric vehicles for sustainable development | |
| CN102722767B (en) | Electromobile charging and exchanging power station stationing and planning system and method | |
| Khan et al. | Technical investigation on V2G, S2V, and V2I for next generation smart city planning | |
| CN109711630A (en) | A kind of electric car fast charge station addressing constant volume method based on trip probability matrix | |
| Tulpule et al. | Energy economic analysis of PV based charging station at workplace parking garage | |
| Ji et al. | Optimizing the locations and sizes of solar assisted electric vehicle charging stations in an urban area | |
| CN108269008B (en) | Charging facility optimization planning method considering user satisfaction and distribution network reliability | |
| CN108334991A (en) | A kind of electric automobile charging station method and system for planning | |
| Yao et al. | Service operations of electric vehicle carsharing systems from the perspectives of supply and demand: A literature review | |
| Rigas et al. | EVLibSim: A tool for the simulation of electric vehicles’ charging stations using the EVLib library | |
| CN113326594B (en) | Electric vehicle battery replacement station and power grid interaction method and system based on microscopic traffic simulation | |
| CN110084520A (en) | Charging station site selecting method and device based on public bus network Yu gridding AP algorithm | |
| CN113442780A (en) | Portable universal battery replacement system for electric vehicle and use method of portable universal battery replacement system | |
| CN103439931B (en) | A kind of electric automobile and real time information interactive system | |
| CN117078046A (en) | Electric bus wired and wireless combined charging optimization method, system and equipment | |
| Abbasi et al. | Assessing feasibility of overnight-charging electric bus in a real-world BRT system in the context of a developing country | |
| Shen et al. | Integrated optimization of electric vehicles charging location and allocation for valet charging service | |
| Zhang et al. | Multi-period planning of locations and capacities of public charging stations | |
| CN114725967A (en) | Electric vehicle charging and discharging benefit optimization method based on vehicle network interaction V2G | |
| CN209683471U (en) | A kind of on-board charging system and movable charging vehicle of miniature gas turbine power generation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |