An electric vehicle charging and discharging aggregated scheduling method and system

Abstract

The application relates to an electric vehicle charging and discharging aggregation scheduling method and system, which comprises the following steps: performing static aggregation on the power supply area of a charging and discharging facility agent in a scheduling area according to a wholesale power purchase proportion curve of the power supply area; determining a scheduling strategy of an electric vehicle scheduling system according to a scheduling participation rate index of the area corresponding to the static aggregation result; and performing real-time scheduling on the electric vehicle scheduling system according to the scheduling strategy of the electric vehicle scheduling system. The application adjusts the load curve of the electric vehicle scheduling system, reduces the peak-valley load difference rate of the power supply area of the electric vehicle agent, improves the wholesale power purchase proportion index, reduces the power purchase cost of the electric vehicle scheduling system, improves the income, formulates the scheduling strategy, and makes the reliability of the electric vehicle scheduling system higher; the transaction between the charging and discharging facility agent, the vehicle owner and the electric vehicle scheduling system is more simple; and the user is more free to accept the scheduling of the electric vehicle scheduling system.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle charging and discharging technology, and specifically to a method and system for aggregated scheduling of electric vehicle charging and discharging. Background Technology

[0002] With the increasing participation rate of electric vehicles (EVs) in power grid dispatching, the charging load of EVs will have a more significant impact on the actual operation of the power grid. Aggregating and dispatching EVs can have a beneficial effect on the economic and safe operation of the EV dispatching system. Traditional EV dealerships select EVs on demand, which has the following drawbacks: the dispatched objects cannot always meet dispatching needs; the dispatched objects cannot be accurately determined; and the reliability of participation in dispatching is low. EVs are dispersed across different areas for charging and discharging, leading to complex settlement issues due to the large number of parties involved (especially different charging and discharging facilities); and the system struggles to predict changes in distribution network flow caused by dispatching, potentially leading to unforeseen problems.

[0003] Overall, in existing research on electric vehicle dealerships, the aggregation process involves complex and non-fixed objects, which is not conducive to the refinement of scheduling strategies. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the purpose of this invention is to propose a control method and system for aggregating and scheduling the power supply areas of charging and discharging facility agents under different electric vehicle dispatch participation rates. This invention reduces the peak-valley load difference rate of the electric vehicle dispatch system's power supply area by adjusting the load curve of the electric vehicle dispatch system, thereby increasing its wholesale electricity purchase ratio and lowering the electricity purchase cost and revenue of the electric vehicle dispatch system. Furthermore, by formulating dispatch strategies, the reliability and operational efficiency of the electric vehicle dispatch system are improved; transactions between charging and discharging facility agents, vehicle owners, and the electric vehicle dispatch system are simplified; and users have greater freedom to accept the dispatching of the electric vehicle dispatch system.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] This invention provides a method for aggregated scheduling of charging and discharging of electric vehicles, the improvement of which is that the method includes:

[0007] Static aggregation of the power supply areas of charging and discharging facility agents is performed based on the wholesale power purchase ratio curve of the power supply areas of the dispatching area.

[0008] The scheduling strategy of the electric vehicle scheduling system is determined based on the scheduling participation rate index of the region corresponding to the static aggregation results.

[0009] The electric vehicle scheduling system is scheduled in real time according to the scheduling strategy of the electric vehicle scheduling system.

[0010] Preferably, the step of statically aggregating the power supply areas of charging and discharging facility agents based on the wholesale electricity purchase ratio curve of the power supply areas in the scheduling area includes:

[0011] Step a. Obtain the wholesale electricity purchase ratio curve for the power supply areas of unmerged charging and discharging facility agents in the dispatch area;

[0012] Step b. Aggregate the wholesale electricity purchase ratio curves of the power supply areas of each unmerged charging and discharging facility agent in pairs to obtain the aggregated curve;

[0013] Step c. Select the aggregation curve with the largest average wholesale electricity purchase ratio. If the average wholesale electricity purchase ratio of the aggregation curve with the largest average wholesale electricity purchase ratio is greater than the average wholesale electricity purchase ratio of the power supply area curves of the two corresponding charging and discharging facility agents, then merge the power supply areas of the two charging and discharging facility agents, output the merged area, and return to step a. Otherwise, output the unmerged area.

[0014] Furthermore, the wholesale electricity purchase ratio of the power supply area for charging and discharging facility agents is calculated using the following formula:

[0015]

[0016] Among them, P emin This is the minimum load in the power supply area of ​​the charging and discharging facility agent during time period t. ξ is the average load of the power supply area of ​​the charging and discharging facility agent in time period t, and ξ is the conservative coefficient for wholesale electricity purchase.

[0017] Preferably, determining the scheduling strategy of the electric vehicle scheduling system based on the scheduling participation rate index of the region corresponding to the static aggregation result includes:

[0018] If the scheduling participation rate index of the region corresponding to the static aggregation result is less than 1, then the region corresponding to the static aggregation result is subject to charging and discharging regulation according to the first regulation strategy of the electric vehicle scheduling system.

[0019] If the scheduling participation rate index of the region corresponding to the static aggregation result is equal to 1, then the region corresponding to the static aggregation result is subject to charging and discharging regulation according to the second regulation strategy of the electric vehicle scheduling system.

[0020] Furthermore, the step of regulating the charging and discharging of the region corresponding to the static aggregation result according to the first regulation strategy of the electric vehicle scheduling system includes:

[0021] With the goal of minimizing the peak-valley load difference, the optimal scheduling period for the region corresponding to the static aggregation result is obtained;

[0022] Based on the optimal scheduling time period of the region corresponding to the static aggregation result, obtain the schedulable potential of each time period in the optimal scheduling time period of the region corresponding to the static aggregation result;

[0023] If the time period corresponding to the maximum schedulable potential of the region corresponding to the static aggregation result is the same as the time period corresponding to the maximum schedulable potential of the region corresponding to other static aggregation results in the scheduling region, then the electric vehicle scheduling system will perform charging and discharging regulation on the region corresponding to the static aggregation result and the region corresponding to other static aggregation results in the scheduling region during the same time period.

[0024] Furthermore, the step of regulating the charging and discharging of the region corresponding to the static aggregation result according to the second regulation strategy of the electric vehicle scheduling system includes:

[0025] If the average selling price of electric vehicles charging the electric vehicle dispatch system in the region corresponding to the static aggregation result is less than the preset selling price, then the electric vehicle dispatch system will schedule electric vehicles in the region corresponding to the static aggregation result to charge the electric vehicle dispatch system; otherwise, the task will end.

[0026] Furthermore, the scheduling participation rate index of the region corresponding to the static aggregation result is calculated using the following formula:

[0027]

[0028] Where ε is the scheduling correction coefficient, and P(t) is the electric vehicle charging and discharging power of the region corresponding to the static aggregation result in time period t. This represents the average charging and discharging power of electric vehicles within the region corresponding to the static aggregation results.

[0029] Furthermore, the step of obtaining the optimal scheduling period for the region corresponding to the static aggregation result with the objective of minimizing the peak-valley load difference includes:

[0030] Simulate the charging and discharging scenarios of electric vehicles in the region corresponding to the static aggregation results, and obtain the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results.

[0031] Select the charging and discharging scenario of the electric vehicle corresponding to the load curve that minimizes the peak-valley load difference, and take the charging period of the electric vehicle to the electric vehicle scheduling system in the charging and discharging scenario of the electric vehicle as the optimal control period of the region corresponding to the static aggregation result.

[0032] Furthermore, the peak-valley load difference rate is calculated using the following formula:

[0033] minδ=(P smax -P smin ) / P smax

[0034] Among them, P smax P represents the peak and valley load values ​​of the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results. smin This represents the minimum peak and valley load values ​​of the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results.

[0035] Furthermore, the schedulable potential of each time period in the optimal scheduling period of the region corresponding to the static aggregation result is the difference between the charging and discharging power and the maximum charging and discharging power of each time period in the optimal scheduling period of the region corresponding to the static aggregation result.

[0036] The present invention provides an electric vehicle charging and discharging aggregation scheduling system, the improvement of which is that the system includes:

[0037] The static aggregation module is used to statically aggregate the power supply areas of charging and discharging facility agents based on the wholesale electricity purchase ratio curve of the power supply areas of the charging and discharging facility agents in the dispatch area.

[0038] The determination module is used to determine the scheduling strategy of the electric vehicle scheduling system based on the scheduling participation rate index of the region corresponding to the static aggregation results.

[0039] The scheduling module is used to perform real-time scheduling of the electric vehicle scheduling system according to the scheduling strategy of the electric vehicle scheduling system.

[0040] Preferably, the static aggregation module includes:

[0041] The first acquisition unit is used to acquire the wholesale electricity purchase ratio curve of the power supply area of ​​the unmerged charging and discharging facility agents in the dispatch area;

[0042] The second acquisition unit is used to aggregate the wholesale electricity purchase ratio curves of the power supply areas of each unmerged charging and discharging facility agent in pairs to obtain the aggregated curve;

[0043] The selection unit is used to select the aggregation curve with the largest average wholesale electricity purchase ratio. If the average wholesale electricity purchase ratio of the aggregation curve with the largest average wholesale electricity purchase ratio is greater than the average wholesale electricity purchase ratio of the power supply area curves of the two corresponding charging and discharging facility agents, then the power supply areas of the two charging and discharging facility agents are merged, the merged area is output, and the process returns to step a. Otherwise, the unmerged area is output.

[0044] Furthermore, the wholesale electricity purchase ratio of the power supply area for charging and discharging facility agents is calculated using the following formula:

[0045]

[0046] Among them, P emin This is the minimum load in the power supply area of ​​the charging and discharging facility agent during time period t. ξ is the average load of the power supply area of ​​the charging and discharging facility agent in time period t, and ξ is the conservative coefficient for wholesale electricity purchase.

[0047] Preferably, the determining module includes:

[0048] The first control unit is used to control the charging and discharging of the region corresponding to the static aggregation result according to the first control strategy of the electric vehicle scheduling system if the scheduling participation rate index of the region corresponding to the static aggregation result is less than 1.

[0049] The second control unit is used to control the charging and discharging of the region corresponding to the static aggregation result according to the second control strategy of the electric vehicle scheduling system if the scheduling participation rate index of the region corresponding to the static aggregation result is equal to 1.

[0050] Furthermore, the first control unit includes:

[0051] The first acquisition subunit is used to acquire the optimal scheduling period for the region corresponding to the static aggregation result with the goal of minimizing the peak-valley load difference rate;

[0052] The second acquisition subunit is used to acquire the schedulable potential of each time period in the optimal scheduling time period of the region corresponding to the static aggregation result based on the optimal scheduling time period of the region corresponding to the static aggregation result.

[0053] The first control subunit is used to control the charging and discharging of the region corresponding to the static aggregation result and the region corresponding to the other static aggregation results in the scheduling area during the same time period if the time period corresponding to the maximum schedulable potential of the region corresponding to the static aggregation result is the same as the time period corresponding to the maximum schedulable potential of the region corresponding to the static aggregation result in the scheduling area.

[0054] Furthermore, the second control unit is configured to, if the average selling price of electric vehicles charging the electric vehicle dispatching system in the region corresponding to the static aggregation result is less than a preset selling price, then the electric vehicle dispatching system will schedule electric vehicles in the region corresponding to the static aggregation result to charge the electric vehicle dispatching system; otherwise, the task will be terminated.

[0055] Furthermore, the scheduling participation rate index of the region corresponding to the static aggregation result is calculated using the following formula:

[0056]

[0057] Where ε is the scheduling correction coefficient, and P(t) is the electric vehicle charging and discharging power of the region corresponding to the static aggregation result in time period t. This represents the average charging and discharging power of electric vehicles within the region corresponding to the static aggregation results.

[0058] Furthermore, the first acquisition subunit includes:

[0059] The acquisition submodule is used to simulate the charging and discharging scenarios of electric vehicles in the region corresponding to the static aggregation results, and to acquire the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results.

[0060] The selection submodule is used to select the charging and discharging scenario of the electric vehicle corresponding to the load curve when the peak-valley load difference is minimized, and to take the charging period of the electric vehicle to the electric vehicle scheduling system in the charging and discharging scenario of the electric vehicle as the optimal control period of the region corresponding to the static aggregation result.

[0061] Furthermore, the peak-valley load difference rate is calculated using the following formula:

[0062] minδ=(P smax -P smin ) / P smax

[0063] Among them, P smax P represents the peak and valley load values ​​of the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results. smin This represents the minimum peak and valley load values ​​of the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results.

[0064] Furthermore, the schedulable potential of each time period in the optimal scheduling period of the region corresponding to the static aggregation result is the difference between the charging and discharging power and the maximum charging and discharging power of each time period in the optimal scheduling period of the region corresponding to the static aggregation result.

[0065] Compared with the closest existing technology, the present invention has the following advantages:

[0066] Based on the wholesale electricity purchase ratio curve of the power supply area of ​​the charging and discharging facility agents in the dispatch area, the power supply areas of the charging and discharging facility agents are statically aggregated. By increasing the wholesale electricity purchase ratio index of the power supply area corresponding to the static aggregation, the electricity purchase cost is reduced, thereby increasing the revenue of the charging and discharging facility agents. The dispatch strategy of the electric vehicle dispatch system is determined based on the dispatch participation rate index of the area corresponding to the static aggregation result. The electric vehicle dispatch system is dispatched in real time according to the dispatch strategy of the electric vehicle dispatch system. By reducing the load peak-valley difference rate of the power supply area of ​​the charging and discharging facility agents, the dispatch error of the electric vehicle dispatch system is reduced, thereby increasing the revenue of the charging and discharging facility agents. Furthermore, the impact of charging and discharging dispatch on the distribution network in the power supply area of ​​the charging and discharging facility agents is predictable. The uncertainty of user charging behavior in the power supply area of ​​the charging and discharging facility agents has a lower impact on the power supply load and dispatchable potential of the power supply area. The reliability of the electric vehicle dispatch system is higher. Transactions between charging and discharging facility agents, car owners and the electric vehicle dispatch system are simpler. Users have more freedom to accept the dispatch of the electric vehicle dispatch system. Attached Figure Description

[0067] Figure 1 This is a flowchart of a method for aggregated scheduling of electric vehicle charging and discharging.

[0068] Figure 2 This is a schematic diagram of the structure of an electric vehicle charging and discharging aggregation scheduling system. Detailed Implementation

[0069] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0070] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0071] This invention provides a method for aggregated scheduling of charging and discharging of electric vehicles, such as... Figure 1 As shown,

[0072] The method includes:

[0073] Static aggregation of the power supply areas of charging and discharging facility agents is performed based on the wholesale power purchase ratio curve of the power supply areas of the dispatching area.

[0074] For example, based on the location of electric vehicle charging and discharging facilities, the dispatch area is divided into different power supply areas for different charging and discharging facility agents. Electric vehicle agent types include: residential area agents, enterprise area agents, commercial area agents, centralized charging station agents, centralized battery charging station agents, and other types of agents.

[0075] The scheduling strategy of the electric vehicle scheduling system is determined based on the scheduling participation rate index of the region corresponding to the static aggregation results.

[0076] The electric vehicle scheduling system is scheduled in real time according to the scheduling strategy of the electric vehicle scheduling system.

[0077] The daily revenue model for electric vehicles participating in the charging and discharging scheduling of the electric vehicle scheduling system in the power supply area of ​​the charging and discharging facility agent in the scheduling area is as follows:

[0078]

[0079] Among them, P ev C(t) represents the total charging power of electric vehicles within the power supply area of ​​the charging and discharging facility agent in the dispatch area, and C(t) represents the electricity fee paid by the user to the electric vehicle charging and discharging facility agent for each unit of electricity used. wholesale The cost per unit of electricity for wholesale distributors of electric vehicle charging and discharging facilities; C realtime (t) represents the electricity price paid by the electric vehicle charging and discharging facility agent for each unit of electricity purchased in the real-time market, Q. 1day P represents the daily wholesale electricity volume for electric vehicle charging and discharging facility distributors. wholesale Q represents the power output corresponding to the daily wholesale electricity volume for electric vehicle charging and discharging facility distributors. dispatch C is the electricity volume that electric vehicle charging and discharging facility agents receive from the electric vehicle dispatching system. dispatch C is the compensation price for electric vehicle charging and discharging facility agents who accept dispatch from the electric vehicle dispatching system per unit of electricity. discharge Q is the compensation electricity price paid by the electric vehicle charging and discharging facility agent to user i who accepts dispatch control for each unit of electricity. discharge_i Let ΔQ be the amount of electricity received by user i under dispatch, n be the number of users participating in dispatch that day, and ΔQ be the total amount of electricity received by user i under dispatch. dispatch Dispatch error power to electric vehicle charging and discharging facility agents. The penalty electricity price corresponding to the dispatch error of electric vehicle charging and discharging facility agents, △Q realtime For electric vehicle dealers, the real-time market purchase error in electricity volume, C realtime_error Settle the electricity price for electric vehicle dealers based on the error in real-time market electricity purchase volume.

[0080] To maximize the profits of electric vehicle charging and discharging facility dealers, they can adjust load curves to reduce the peak-valley load difference in the dealers' power supply areas and increase their wholesale electricity purchase ratio to lower electricity purchase costs and increase revenue.

[0081] Meanwhile, electric vehicle charging and discharging facility agents should adjust the charging and discharging status of electric vehicles in a timely manner based on dispatch information, so as to reduce the difference between the agent's daily load (including actual dispatch volume) and the previous day's predicted load (including previous day's dispatch batch), thereby reducing error costs in the real-time market and penalties for inadequate dispatch.

[0082] Specifically, the static aggregation of the power supply areas of charging and discharging facility agents based on the wholesale electricity purchase ratio curve of the power supply areas in the dispatch area includes:

[0083] Step a. Obtain the wholesale electricity purchase ratio curve for the power supply areas of unmerged charging and discharging facility agents in the dispatch area;

[0084] Step b. Aggregate the wholesale electricity purchase ratio curves of the power supply areas of each unmerged charging and discharging facility agent in pairs to obtain the aggregated curve;

[0085] Step c. Select the aggregation curve with the largest average wholesale electricity purchase ratio. If the average wholesale electricity purchase ratio of the aggregation curve with the largest average wholesale electricity purchase ratio is greater than the average wholesale electricity purchase ratio of the power supply area curves of the two corresponding charging and discharging facility agents, then merge the power supply areas of the two charging and discharging facility agents, output the merged area, and return to step a. Otherwise, output the unmerged area.

[0086] Specifically, the wholesale electricity purchase ratio of the power supply area for charging and discharging facility agents is calculated using the following formula:

[0087]

[0088] Among them, P emin This is the minimum load in the power supply area of ​​the charging and discharging facility agent during time period t. ξ is the average load of the power supply area of ​​the charging and discharging facility agent in time period t, and ξ is the conservative coefficient for wholesale electricity purchase, which is generally selected from (0-1).

[0089] Specifically, determining the scheduling strategy of the electric vehicle scheduling system based on the scheduling participation rate index of the region corresponding to the static aggregation result includes:

[0090] If the scheduling participation rate index of the region corresponding to the static aggregation result is less than 1, then the region corresponding to the static aggregation result is subject to charging and discharging regulation according to the first regulation strategy of the electric vehicle scheduling system.

[0091] If the scheduling participation rate index of the region corresponding to the static aggregation result is equal to 1, then the region corresponding to the static aggregation result is subject to charging and discharging regulation according to the second regulation strategy of the electric vehicle scheduling system.

[0092] Specifically, the step of regulating the charging and discharging of the region corresponding to the static aggregation result according to the first regulation strategy of the electric vehicle scheduling system includes:

[0093] With the goal of minimizing the peak-valley load difference, the optimal scheduling period for the region corresponding to the static aggregation result is obtained;

[0094] Based on the optimal scheduling time period of the region corresponding to the static aggregation result, obtain the schedulable potential of each time period in the optimal scheduling time period of the region corresponding to the static aggregation result;

[0095] If the time period corresponding to the maximum schedulable potential of the region corresponding to the static aggregation result is the same as the time period corresponding to the maximum schedulable potential of the region corresponding to other static aggregation results in the scheduling region, then the electric vehicle scheduling system will perform charging and discharging regulation on the region corresponding to the static aggregation result and the region corresponding to other static aggregation results in the scheduling region during the same time period.

[0096] Specifically, the step of regulating the charging and discharging of the region corresponding to the static aggregation result according to the second regulation strategy of the electric vehicle scheduling system includes:

[0097] If the average selling price of electric vehicles charging the electric vehicle dispatch system in the region corresponding to the static aggregation result is less than the preset selling price, then the electric vehicle dispatch system will schedule electric vehicles in the region corresponding to the static aggregation result to charge the electric vehicle dispatch system; otherwise, the task will end.

[0098] Specifically, the scheduling participation rate index of the region corresponding to the static aggregation result is calculated using the following formula:

[0099]

[0100] Where ε is the scheduling correction coefficient, and P(t) is the electric vehicle charging and discharging power of the region corresponding to the static aggregation result in time period t. This represents the average charging and discharging power of electric vehicles within the region corresponding to the static aggregation results.

[0101] Specifically, obtaining the optimal scheduling period for the region corresponding to the static aggregation result with the objective of minimizing the peak-valley load difference includes:

[0102] Simulate the charging and discharging scenarios of electric vehicles in the region corresponding to the static aggregation results, and obtain the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results.

[0103] The charging and discharging scenario of the electric vehicle corresponding to the load curve that minimizes the peak-valley load difference is selected, and the charging period of the electric vehicle to the electric vehicle scheduling system in this charging and discharging scenario is taken as the optimal control period for the region corresponding to the static aggregation result. The charging and discharging scenario of the electric vehicle corresponding to the load curve that minimizes the peak-valley load difference can be selected using a genetic algorithm.

[0104] Specifically, the peak-valley load difference rate is calculated using the following formula:

[0105] minδ=(P smax -P smin ) / P smax

[0106] Among them, P smax P represents the peak and valley load values ​​of the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results. smin This represents the minimum peak and valley load values ​​of the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results.

[0107] Specifically, the schedulable potential of each time period in the optimal scheduling period of the region corresponding to the static aggregation result is the difference between the charging and discharging power of each time period in the optimal scheduling period of the region corresponding to the static aggregation result and the maximum charging and discharging power.

[0108] This invention provides an electric vehicle charging and discharging aggregation scheduling system, such as... Figure 2 As shown,

[0109] The system includes:

[0110] The static aggregation module is used to statically aggregate the power supply areas of charging and discharging facility agents based on the wholesale electricity purchase ratio curve of the power supply areas of the charging and discharging facility agents in the dispatch area.

[0111] The determination module is used to determine the scheduling strategy of the electric vehicle scheduling system based on the scheduling participation rate index of the region corresponding to the static aggregation results.

[0112] The scheduling module is used to perform real-time scheduling of the electric vehicle scheduling system according to the scheduling strategy of the electric vehicle scheduling system.

[0113] Specifically, the static aggregation module includes:

[0114] The first acquisition unit is used to acquire the wholesale electricity purchase ratio curve of the power supply area of ​​the unmerged charging and discharging facility agents in the dispatch area;

[0115] The second acquisition unit is used to aggregate the wholesale electricity purchase ratio curves of the power supply areas of each unmerged charging and discharging facility agent in pairs to obtain the aggregated curve;

[0116] The selection unit is used to select the aggregation curve with the largest average wholesale electricity purchase ratio. If the average wholesale electricity purchase ratio of the aggregation curve with the largest average wholesale electricity purchase ratio is greater than the average wholesale electricity purchase ratio of the power supply area curves of the two corresponding charging and discharging facility agents, then the power supply areas of the two charging and discharging facility agents are merged, the merged area is output, and the process returns to step a. Otherwise, the unmerged area is output.

[0117] Specifically, the wholesale electricity purchase ratio of the power supply area for charging and discharging facility agents is calculated using the following formula:

[0118]

[0119] Among them, P emin This is the minimum load in the power supply area of ​​the charging and discharging facility agent during time period t. ξ is the average load of the power supply area of ​​the charging and discharging facility agent in time period t, and ξ is the conservative coefficient for wholesale electricity purchase.

[0120] Specifically, the determining module includes:

[0121] The first control unit is used to control the charging and discharging of the region corresponding to the static aggregation result according to the first control strategy of the electric vehicle scheduling system if the scheduling participation rate index of the region corresponding to the static aggregation result is less than 1.

[0122] The second control unit is used to control the charging and discharging of the region corresponding to the static aggregation result according to the second control strategy of the electric vehicle scheduling system if the scheduling participation rate index of the region corresponding to the static aggregation result is equal to 1.

[0123] Specifically, the first control unit includes:

[0124] The first acquisition subunit is used to acquire the optimal scheduling period for the region corresponding to the static aggregation result with the goal of minimizing the peak-valley load difference rate;

[0125] The second acquisition subunit is used to acquire the schedulable potential of each time period in the optimal scheduling time period of the region corresponding to the static aggregation result based on the optimal scheduling time period of the region corresponding to the static aggregation result.

[0126] The first control subunit is used to control the charging and discharging of the region corresponding to the static aggregation result and the region corresponding to the other static aggregation results in the scheduling area during the same time period if the time period corresponding to the maximum schedulable potential of the region corresponding to the static aggregation result is the same as the time period corresponding to the maximum schedulable potential of the region corresponding to the static aggregation result in the scheduling area.

[0127] Specifically, the second control unit is used to schedule electric vehicles in the region corresponding to the static aggregation result to charge the electric vehicle dispatching system if the average selling price of electric vehicles charging the electric vehicle dispatching system in the region corresponding to the static aggregation result is less than the preset selling price; otherwise, the task is terminated.

[0128] Specifically, the scheduling participation rate index of the region corresponding to the static aggregation result is calculated using the following formula:

[0129]

[0130] Where ε is the scheduling correction coefficient, and P(t) is the electric vehicle charging and discharging power of the region corresponding to the static aggregation result in time period t. This represents the average charging and discharging power of electric vehicles within the region corresponding to the static aggregation results.

[0131] Specifically, the first acquisition subunit includes:

[0132] The acquisition submodule is used to simulate the charging and discharging scenarios of electric vehicles in the region corresponding to the static aggregation results, and to acquire the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results.

[0133] The selection submodule is used to select the charging and discharging scenario of the electric vehicle corresponding to the load curve when the peak-valley load difference is minimized, and to take the charging period of the electric vehicle to the electric vehicle scheduling system in the charging and discharging scenario of the electric vehicle as the optimal control period of the region corresponding to the static aggregation result.

[0134] Specifically, the peak-valley load difference rate is calculated using the following formula:

[0135] minδ=(P smax -P smin ) / P smax

[0136] Among them, P smax P represents the peak and valley load values ​​of the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results. smin This represents the minimum peak and valley load values ​​of the load curves corresponding to the charging and discharging scenarios of each electric vehicle in the region corresponding to the static aggregation results.

[0137] Specifically, the schedulable potential of each time period in the optimal scheduling period of the region corresponding to the static aggregation result is the difference between the charging and discharging power of each time period in the optimal scheduling period of the region corresponding to the static aggregation result and the maximum charging and discharging power.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for aggregated scheduling of charging and discharging of electric vehicles, characterized in that, The method comprises: According to the wholesale electricity purchase proportion curve of the power supply area of the charging and discharging facility agent in the scheduling area, the power supply area of the charging and discharging facility agent is statically aggregated; According to the scheduling participation rate index of the region corresponding to the static aggregation result, the scheduling strategy of the electric vehicle scheduling system is determined; According to the scheduling strategy of the electric vehicle scheduling system, the electric vehicle scheduling system is scheduled in real time; According to the wholesale electricity purchase proportion curve of the power supply area of the charging and discharging facility agent in the scheduling area, the power supply area of the charging and discharging facility agent is statically aggregated, comprising: Step a. Obtain the wholesale electricity purchase proportion curve of the power supply area of the uncombined charging and discharging facility agent in the scheduling area; Step b. Aggregate the wholesale electricity purchase proportion curves of each uncombined charging and discharging facility agent's power supply area two by two to obtain an aggregated curve; Step c. Select the aggregated curve with the maximum average wholesale electricity purchase proportion value, if the average wholesale electricity purchase proportion value of the aggregated curve with the maximum average wholesale electricity purchase proportion value is greater than the average wholesale electricity purchase proportion value of the two charging and discharging facility agents' power supply area corresponding to the aggregated curve, then the two charging and discharging facility agents' power supply area is merged, the merged region is output, and step a is returned, otherwise, the unmerged region is output; According to the scheduling participation rate index of the region corresponding to the static aggregation result, the scheduling strategy of the electric vehicle scheduling system is determined, comprising: If the scheduling participation rate index of the region corresponding to the static aggregation result is less than 1, then the first regulation and control strategy of the electric vehicle scheduling system is used to regulate and control the charging and discharging of the region corresponding to the static aggregation result; If the scheduling participation rate index of the region corresponding to the static aggregation result is equal to 1, then the second regulation and control strategy of the electric vehicle scheduling system is used to regulate and control the charging and discharging of the region corresponding to the static aggregation result; According to the first regulation and control strategy of the electric vehicle scheduling system, the charging and discharging of the region corresponding to the static aggregation result is regulated and controlled, comprising: The optimal scheduling period of the region corresponding to the static aggregation result is obtained by taking the minimization of the peak-valley load difference rate as the target; The schedulable potential of each period in the optimal scheduling period of the region corresponding to the static aggregation result is obtained according to the optimal scheduling period of the region corresponding to the static aggregation result; If the period corresponding to the maximum schedulable potential of the region corresponding to the static aggregation result is the same as the period corresponding to the maximum schedulable potential of other regions corresponding to the static aggregation result in the scheduling area, then the electric vehicle scheduling system regulates and controls the charging and discharging of the region corresponding to the static aggregation result and the other regions corresponding to the static aggregation result in the scheduling area in the same period; The schedulable potential of each period in the optimal scheduling period of the region corresponding to the static aggregation result is the difference between the charging and discharging power of each period in the optimal scheduling period of the region corresponding to the static aggregation result and the maximum charging and discharging power.

2. The method of claim 1, wherein, The wholesale electricity purchase proportion index of the power supply area of the charging and discharging facility agent is calculated as follows: wherein, is a minimum value of the load of the power supply area of the charging and discharging facility agent for the tth period, is an average value of the load of the power supply area of the charging and discharging facility agent for the tth period, is a wholesale power purchase conservative coefficient.

3. The method of claim 1, wherein, According to the second regulation and control strategy of the electric vehicle scheduling system, the charging and discharging of the region corresponding to the static aggregation result is regulated and controlled, comprising: If an average selling price of the electric vehicles charging the electric vehicle scheduling system in the region corresponding to the static aggregation result is less than a preset selling price, the electric vehicle scheduling system schedules the electric vehicles in the region corresponding to the static aggregation result to charge the electric vehicle scheduling system; otherwise, the task is ended.

4. The method of claim 1, wherein, The scheduling participation rate index of the region corresponding to the static aggregation result is calculated according to the following formula: wherein, is a dispatch correction coefficient, is the electric vehicle charging and discharging power of the region corresponding to the static aggregation result of the t period, is the average value of the electric vehicle charging and discharging power of the region corresponding to the static aggregation result.

5. The method of claim 1, wherein, The system comprises: The static aggregation module is configured to aggregate the power supply regions of the charging and discharging facility agents in the scheduling region according to the wholesale power purchase proportion curves of the power supply regions of the charging and discharging facility agents. The determination module is configured to determine a scheduling strategy of the electric vehicle scheduling system according to the scheduling participation rate index of the region corresponding to the static aggregation result.

6. The method of claim 1, wherein, The scheduling module is configured to schedule the electric vehicle scheduling system in real time according to the scheduling strategy of the electric vehicle scheduling system. wherein, is the maximum peak-valley load value of the load curve corresponding to the charging and discharging scenario of each electric vehicle in the region corresponding to the static aggregation result, is the minimum peak-valley load value of the load curve corresponding to the charging and discharging scenario of each electric vehicle in the region corresponding to the static aggregation result.

7. An electric vehicle charging and discharging aggregated scheduling system, characterized in that, The static aggregation module comprises: The first obtaining unit is configured to obtain the wholesale power purchase proportion curves of the power supply regions of the unmerged charging and discharging facility agents in the scheduling region. The second obtaining unit is configured to aggregate the wholesale power purchase proportion curves of the power supply regions of the unmerged charging and discharging facility agents two by two to obtain aggregation curves. The selection unit is configured to select the aggregation curve with the maximum average wholesale power purchase proportion value, and if the average wholesale power purchase proportion values of the aggregation curve with the maximum average wholesale power purchase proportion value are greater than the average wholesale power purchase proportion values of the wholesale power purchase proportion curves of the power supply regions of the two charging and discharging facility agents corresponding to the aggregation curve with the maximum average wholesale power purchase value, respectively, the power supply regions of the two charging and discharging facility agents are merged, a merged region is output, and the step a is returned; otherwise, an unmerged region is output. The determination module comprises: The first regulation unit is configured to perform charging and discharging regulation on the region corresponding to the static aggregation result according to a first regulation strategy of the electric vehicle scheduling system if the scheduling participation rate index of the region corresponding to the static aggregation result is less than 1. The second regulation unit is configured to perform charging and discharging regulation on the region corresponding to the static aggregation result according to a second regulation strategy of the electric vehicle scheduling system if the scheduling participation rate index of the region corresponding to the static aggregation result is equal to 1. The first regulation unit comprises: The first obtaining subunit is configured to obtain an optimal scheduling time period of the region corresponding to the static aggregation result with the minimum peak-valley load difference rate as a target. The second obtaining subunit is configured to obtain the schedulable potential of each time period in the optimal scheduling time period of the region corresponding to the static aggregation result according to the optimal scheduling time period of the region corresponding to the static aggregation result. ​ ​ ​ ​ The first regulation subunit is configured to, if the time period corresponding to the maximum schedulable potential of the region corresponding to the static aggregation result is the same as the time period corresponding to the maximum schedulable potential of the region corresponding to other static aggregation results in the scheduling region, regulate the charging and discharging of the region corresponding to the static aggregation result and the region corresponding to other static aggregation results in the scheduling region at the same time period. The schedulable potential of each time period in the optimal scheduling time period of the region corresponding to the static aggregation result is the difference between the charging and discharging power of each time period in the optimal scheduling time period of the region corresponding to the static aggregation result and the maximum charging and discharging power.

8. The system of claim 7, wherein, The wholesale electricity purchase proportion index of the power supply region of the charging and discharging facility agent is calculated according to the following formula: wherein, is a minimum value of the load of the power supply area of the charging and discharging facility agent for the tth period, is an average value of the load of the power supply area of the charging and discharging facility agent for the tth period, is a wholesale power purchase conservative coefficient.

9. The system of claim 7, wherein, The second regulation unit is configured to, if the average selling price of the electric vehicles in the region corresponding to the static aggregation result to the electric vehicle scheduling system is less than the preset selling price, schedule the electric vehicles in the region corresponding to the static aggregation result to the electric vehicle scheduling system; otherwise, end the task.

10. The system of claim 7, wherein, The scheduling participation rate index of the region corresponding to the static aggregation result is calculated according to the following formula: wherein, is a dispatch correction coefficient, is the electric vehicle charging and discharging power of the region corresponding to the static aggregation result at time t, is the average of the electric vehicle charging and discharging power of the region corresponding to the static aggregation result.

11. The system of claim 7, wherein, The first acquisition subunit comprises: The acquisition submodule is configured to simulate the charging and discharging scenarios of the electric vehicles in the region corresponding to the static aggregation result, and acquire the load curve corresponding to the charging and discharging scenario of each electric vehicle in the region corresponding to the static aggregation result. The selection submodule is configured to select the charging and discharging scenario of the electric vehicle corresponding to the load curve with the minimum peak-valley load difference rate, and take the charging time period of the electric vehicle to the electric vehicle scheduling system in the charging and discharging scenario of the electric vehicle as the optimal regulation time period of the region corresponding to the static aggregation result.

12. The system of claim 7, wherein, The peak-valley load difference rate is calculated according to the following formula: wherein, is the peak-valley load maximum value of the load curve corresponding to the charging and discharging scenario of each electric vehicle in the region corresponding to the static aggregation result, is the peak-valley load minimum value of the load curve corresponding to the charging and discharging scenario of each electric vehicle in the region corresponding to the static aggregation result.

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