Adjustment capability evaluation calculation and regulation method under charging station resources in virtual power plant

Abstract

The invention relates to the technical field of virtual power plant resource estimation, and provides a virtual power plant charging station resource regulation capability evaluation calculation and regulation method comprising the following steps: building a charging station resource baseline load calculation model in a virtual power plant; establishing an adjustment capability evaluation calculation model under charging station resources in the virtual power plant; a regulation response regulation profit boundary analysis model under the charging station resources in the virtual power plant is established, the regulation response regulation profit boundary analysis model under the charging station resources in the virtual power plant is calculated and solved, and the lower limit value of the charging station resource response period willingness degree in the virtual power plant is solved; establishing a regulation and control model for regulating capability release under charging station resources in the virtual power plant; and establishing an adjustment response regulation and control profit effect calculation model under the charging station resources in the virtual power plant, and performing evaluation calculation on the adjustment response regulation and control profit effect under the charging station resources in the virtual power plant. According to the invention, accurate calculation and accurate operation regulation and control of the adjustment capability of the charging station resources can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual power plant resource estimation, and in particular to a method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant. Background Art

[0002] With the energy transition and the widespread adoption of electric vehicles, virtual power plants (VPPs), as an emerging resource management and scheduling method, are gradually gaining a significant position in the power system. By integrating and optimizing distributed resources such as charging stations, distributed generation, energy storage, and controllable loads, VPPs enable flexible energy scheduling and optimized allocation. In VPP operations, charging stations, as a key flexibility resource, offer enormous regulatory potential and promising prospects for grid-load interactive response and regulation.

[0003] However, in the actual operation of virtual power plants, the evaluation, calculation and control of the down-regulation capacity of charging station resources face many challenges. (1) Traditional charging station operation management focuses mainly on the provision of charging services, and lacks systematic evaluation and optimization of the regulation capacity of charging station resources. This results in the inability to fully utilize the regulation capacity of charging station resources during the operation of virtual power plants, affecting the overall operation efficiency and economic benefits of virtual power plants. (2) Traditional charging station resource management and scheduling methods are often based on fixed charging strategies, ignoring the flexibility and adjustability of charging station resources. Existing methods cannot fully utilize the regulation capacity of charging station resources, give full play to profit space, and lead to waste of flexible resources. (3) The evaluation and control of the regulation capacity of charging station resources requires comprehensive consideration of multiple factors including baseline load, pre-evaluation calculation of regulation capacity, profit boundary analysis and generation of control instructions. In the existing technology, there is a lack of a method that can comprehensively and systematically evaluate, calculate and control the down-regulation capacity of charging station resources. Existing evaluation methods cannot reflect the dynamic regulation capacity of charging station resources in real time, and there are also significant limitations in profit boundary analysis and control instruction generation. Overall, existing technical approaches mostly focus on single charging strategies and models, lacking systematic down-regulation capacity assessment and control solutions. In particular, when considering the participation of charging station resources in the electricity market, accurately assessing their down-regulation capacity, determining their profit margins, and developing corresponding control strategies have become urgent technical challenges. Summary of the Invention

[0004] The purpose of the present invention is to solve at least one technical problem in the background technology and to provide a method and system for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant.

[0005] To achieve the above objectives, the present invention provides a method for evaluating, calculating, and controlling the regulation capacity of charging station resources in a virtual power plant, comprising:

[0006] Establish a baseline load calculation model for charging station resources in a virtual power plant, including: a baseline load calculation model for charging station resources on weekdays, a baseline load calculation model for charging station resources on weekends, and a baseline load calculation model for charging station resources on statutory holidays;

[0007] Based on the baseline load calculation model of charging station resources in the virtual power plant, a calculation model for evaluating the down-regulation capability of charging station resources in the virtual power plant is established, including: a calculation model for evaluating the predicted real-time maximum down-regulation capability, a calculation model for evaluating the real-time maximum down-regulation capability during the response period, and a calculation model for evaluating the willingness down-regulation capability during the response period;

[0008] Based on the calculation model for evaluating the regulation capability of charging station resources in the virtual power plant, a profit boundary analysis model for regulating the response of charging station resources in the virtual power plant is established, and the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant is calculated and solved to obtain the lower limit of the willingness of the charging station resources in the virtual power plant to respond during the period.

[0009] Based on the profit boundary analysis model of the regulation response of the charging station resources in the virtual power plant, a regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant is established, and regulation instructions are generated and issued according to the output of the regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant;

[0010] Based on the regulation model for releasing the regulation capacity of charging station resources in the virtual power plant, a profit-making effect calculation model for regulating the response of charging station resources in the virtual power plant is established to evaluate and calculate the profit-making effect of regulating the response of charging station resources in the virtual power plant;

[0011] Collect initialization startup data information of regulation capacity evaluation calculation and control under the virtual power plant's charging station resources, input the collected initialization startup data information into the baseline load calculation model of the charging station resources in the virtual power plant, the regulation capacity evaluation calculation model under the virtual power plant's charging station resources, the regulation response control profit boundary analysis model under the virtual power plant's charging station resources, the regulation model of regulation capacity release under the virtual power plant's charging station resources and the regulation response control profit effect calculation model under the virtual power plant's charging station resources, and output the regulation capacity evaluation calculation and control result data information under the virtual power plant's charging station resources.

[0012] According to one aspect of the present invention, the working day baseline load calculation model of the charging station resources in the virtual power plant is expressed as follows:

[0013]

[0014] Where: For charging station resources working day at time t Baseline load value; The first of five consecutive normal working days before the charging station resource response invitation date d working days at time t Historical electricity load values; For charging station resources, please work for 5 consecutive normal working days before the invitation date. t The maximum value of historical power load; For charging station resources, please work for 5 consecutive normal working days before the invitation date. t The minimum value of the historical power load value; Ξmax{*} is the maximum value function among multiple data; Ξmin{*} is the minimum value function among multiple data;

[0015] The expression of the baseline load calculation model for charging station resources on weekends in the virtual power plant is as follows:

[0016]

[0017] Where: For charging station resources on weekends at time t Baseline load value; The first of five consecutive normal weekends before the day of the charging station resource response invitation q Weekdays off at time t Historical electricity load values; For charging station resources, respond to the invitation for 5 consecutive normal weekends before the date of the invitation. t The maximum value of historical power load; For charging station resources, respond to the invitation for 5 consecutive normal weekends before the date of the invitation. t The minimum value of the historical power load value; Ξmax{*} is the maximum value function among multiple data; Ξmin{*} is the minimum value function among multiple data;

[0018] The expression of the statutory holiday baseline load calculation model for charging station resources in the virtual power plant is as follows:

[0019]

[0020] Where: is the baseline load value of the charging station resource on statutory holidays at time t; It is the historical daily electricity load value of charging station resources during statutory holidays.

[0021] According to one aspect of the present invention, the expression of the predicted real-time maximum down-regulation capability evaluation calculation model is as follows:

[0022]

[0023] Where: Predicting the real-time maximum down-regulation capacity for charging station resources in virtual power plants; The power load value of a sampling point of the charging station resource in the virtual power plant; The power load value of the latest sampling point of the charging station resources in the virtual power plant; Predict the power load value of the first sampling point in the future for the charging station resources in the virtual power plant; Predict the power load value of the second sampling point in the future for the charging station resources in the virtual power plant; The minimum safety load requirement for the operation and maintenance of charging station resources in the virtual power plant; Δt The interval between power sampling points for the power load of charging station resources in the virtual power plant;

[0024] The expression of the response period real-time maximum down-regulation capability evaluation calculation model is as follows:

[0025]

[0026] Where: It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the baseline load value of the charging station resource at time t on a working day; is the baseline load value of the charging station resource at time t on weekends; is the baseline load value of the charging station resource on statutory holidays at time t; The minimum safety load requirement for operation and maintenance of charging station resources in the virtual power plant; Ω response is a set of time periods for charging station resource response periods; A function that operates on one of multiple data values;

[0027] The expression of the calculation model for evaluating the regulatory ability under the response period willingness is as follows:

[0028]

[0029] Where: The adjustment capability of charging station resources in the virtual power plant under the willingness response period; The willingness of charging station resources to respond in the virtual power plant is 0, indicating no response to regulation, and 1 indicates the maximum degree of participation in response regulation. is the real-time maximum down-regulation capability of the charging station resource response period in the virtual power plant; Ξmin{*} is the minimum value function among multiple data; It is the minimum security load requirement for the operation and maintenance of charging station resources in the virtual power plant.

[0030] According to one aspect of the present invention, the expression of the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant is as follows:

[0031]

[0032] Where: Ω response is a set of time periods for charging station resource response periods; is the time-of-use electricity price of the charging service of the charging station in the virtual power plant at time t; is the time-sharing price of the charging service of the charging station in the virtual power plant at time t; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the adjustment capacity of the charging station resource response period willingness in the virtual power plant; Δt is the interval time between the power sampling points of the charging station resource power load in the virtual power plant; ε loss cost ΣΩ is the unit comprehensive loss cost of the charging load demand caused by the interruption of charging station resources in the virtual power plant, which includes the cost of compensating charging users, regulation costs, operation and maintenance costs, labor costs, etc. response is the total length of the charging station resource response period; β response price is the unit compensation income of the charging station resource response period in the virtual power plant; is the willingness of charging station resources to respond in the virtual power plant. A value of 0 indicates no response to regulation, and a value of 1 indicates maximum participation in response regulation. start The starting time of the charging station resource response period;

[0033] The profit boundary analysis model of the regulation response control of charging station resources in the virtual power plant is calculated and solved. The lower limit of If the lower limit value of is 0, it means that there is no profit space for response regulation and no response regulation should be made; if If the lower limit value is greater than 0, it means that there is profit space when participating in response regulation at least at this lower limit value.

[0034] According to one aspect of the present invention, the expression for establishing a control model for regulating the release of charging station resources in a virtual power plant is as follows:

[0035]

[0036] Where: is the control instruction received by the charging station resources in the virtual power plant at time t; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; The adjustment capability of charging station resources in the virtual power plant under the willingness response period; is the control instruction received by each charging pile within the charging station resources in the virtual power plant at time t; The smallest positive integer operation function whose upward value is greater than the operation result, and the minimum result of this operation function is 1; The rated charging power of the charging piles within the charging station resources in the virtual power plant; The minimum power for charging the charging piles within the charging station resources in the virtual power plant; Ω response is a set of time periods for charging station resource response periods; The intermediate process quantity related to the evaluation and calculation of the control instructions received by each charging pile within the charging station resources in the virtual power plant at time t;

[0037] The control instructions are produced and issued according to the output of the control model of the regulation capacity released by the charging station resources in the virtual power plant. The output of the station control system at the charging station resource level is Tracking execution instructions for charging stations; output Down to each charging pile within the charging station resources, the output Execute instructions for tracking charging piles.

[0038] According to one aspect of the present invention, the expression of the profit effect calculation model of the regulation response control of charging station resources in the virtual power plant is as follows:

[0039]

[0040] Where: Ω is the profit value of the charging station resource adjustment in the virtual power plant; response is a set of time periods for charging station resource response periods; is the time-of-use electricity price of the charging service of the charging station in the virtual power plant at time t; is the time-sharing price of the charging service of the charging station in the virtual power plant at time t; is the control instruction received by each charging pile within the charging station resources in the virtual power plant at time t; The smallest positive integer operation function whose upward value is greater than the operation result, and the minimum result of this operation function is 1; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the rated charging power of the charging pile within the charging station resources in the virtual power plant; Δt is the interval between the power sampling points of the power load of the charging station resources in the virtual power plant; is the adjustment capacity of charging station resources in the virtual power plant under the willingness response period; βresponse price is the unit compensation income of the charging station resource response period in the virtual power plant; ΣΩ response is the total length of the charging station resource response period; ε loss cost The unit comprehensive loss cost of the charging load demand caused by the interruption of charging station resources in the virtual power plant includes the cost of compensating charging users, regulation cost, operation and maintenance cost, labor cost, etc.; start The starting time of the charging station resource response period.

[0041] According to one aspect of the present invention, the collection of initialization startup data information for evaluating, calculating, and regulating the regulation capacity of charging station resources in a virtual power plant includes:

[0042] The historical electricity load values on the invitation day and the five consecutive normal working days before the invitation day, the historical electricity load values on the five consecutive normal weekends before the invitation day, the historical electricity load values on the same days of statutory holidays, the historical electricity load power values at the two sampling points before the current moment, the predicted electricity load power values at the two sampling points before the current moment, the interval between the sampling points of the electricity load power of the charging station resources, the minimum security load requirement for the operation and maintenance of the charging station resources, the set of time periods of the charging station resource response period, the charging time-of-use electricity price of the charging service of the charging station in the virtual power plant at each time, the service fee time-of-use price of the charging service of the charging station in the virtual power plant at each time, the unit comprehensive loss cost of the charging load demand of the charging station resources in the virtual power plant due to interruption, the total length of the charging station resource response period, the unit compensation income of the charging station resource response period in the virtual power plant, the rated charging power of the charging piles within the charging station resources in the virtual power plant, and the minimum charging operation power of the charging piles within the charging station resources in the virtual power plant;

[0043] The output of the virtual power plant charging station resource regulation capacity evaluation calculation and regulation result data information includes:

[0044] The baseline load values of charging station resources at various times on weekdays, the baseline load values of charging station resources at various times on weekends, the baseline load values of charging station resources at various times on statutory holidays, the predicted real-time maximum down-regulation capacity of charging station resources in the virtual power plant, the real-time maximum down-regulation capacity of charging station resources in the virtual power plant during the response period, the willingness value of charging station resources in the virtual power plant during the response period, the control instructions received by charging station resources in the virtual power plant at various times, the control instructions received by each charging pile within the charging station resources in the virtual power plant at various times, and the control profit value of the down-regulation response of charging station resources in the virtual power plant.

[0045] To achieve the above objectives, the present invention further provides a system for evaluating, calculating, and controlling the regulation capacity of charging station resources in a virtual power plant, comprising:

[0046] The first model building module establishes a baseline load calculation model for charging station resources in the virtual power plant, including: a baseline load calculation model for charging station resources on weekdays, a baseline load calculation model for charging station resources on weekends, and a baseline load calculation model for charging station resources on statutory holidays in the virtual power plant;

[0047] The second model building module establishes a calculation model for evaluating the down-regulation capability of charging station resources in the virtual power plant based on the baseline load calculation model of charging station resources in the virtual power plant, including: a calculation model for evaluating the predicted real-time maximum down-regulation capability, a calculation model for evaluating the real-time maximum down-regulation capability during the response period, and a calculation model for evaluating the willingness down-regulation capability during the response period;

[0048] The third model building module establishes a profit boundary analysis model for regulating the response of charging station resources in the virtual power plant based on the calculation model for evaluating the regulation capability of charging station resources in the virtual power plant, calculates and solves the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant, and solves the lower limit of the willingness of the charging station resources in the virtual power plant to respond during the period;

[0049] a fourth model building module, which establishes a control model for releasing the regulation capacity of charging station resources in the virtual power plant based on the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant, and generates and issues control instructions according to the output of the control model for releasing the regulation capacity of charging station resources in the virtual power plant;

[0050] a fifth model building module, based on the regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant, establishing a profit-making effect calculation model for regulating the response of the charging station resources in the virtual power plant, and evaluating and calculating the profit-making effect of regulating the response of the charging station resources in the virtual power plant;

[0051] The data information input and output module collects the initialization startup data information of the regulation capacity evaluation calculation and regulation under the virtual power plant's charging station resources, and inputs the collected initialization startup data information into the baseline load calculation model of the charging station resources in the virtual power plant, the regulation capacity evaluation calculation model under the virtual power plant's charging station resources, the regulation response regulation profit boundary analysis model under the virtual power plant's charging station resources, the regulation model of the regulation capacity release under the virtual power plant's charging station resources, and the regulation response regulation profit effect calculation model under the virtual power plant's charging station resources, and outputs the regulation capacity evaluation calculation and regulation result data information under the virtual power plant's charging station resources.

[0052] To achieve the above-mentioned objectives, the present invention also provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and runnable on the processor. When the computer program is executed by the processor, the method for evaluating, calculating, and controlling the regulation capacity of charging station resources in a virtual power plant as described above is implemented.

[0053] To achieve the above-mentioned objectives, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the above-mentioned method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant.

[0054] The present invention comprehensively considers multiple aspects of charging station resources, including baseline load calculation, downsizing capacity assessment, profit margin analysis, and control strategy formulation, to achieve the calculation of the regulating capacity and precise operational control of charging station resources. This invention effectively addresses the difficulties in assessing the regulating capacity of charging station resources, calculating the profit margin for market participation, and regulating the release of regulating capacity by charging piles. It provides strong technical support for energy management, efficient operation, and precise control of regulating capacity release of charging station resources in virtual power plants.

[0055] According to the solution of the present invention, the present invention fully considers the whole process elements such as baseline load calculation, down-regulation capacity evaluation calculation, regulation, profit boundary analysis, and profit calculation of charging station resources in virtual power plants, establishes a mathematical model for down-regulation capacity evaluation calculation and energy release regulation of charging station resources, which is helpful for accurate operation and regulation of charging station resources in virtual power plants, and is beneficial for charging station operation and maintenance personnel to grasp the down-regulation capacity of power station resources in real time; the present invention proposes a down-regulation capacity evaluation calculation and regulation method for charging station resources in virtual power plants based on the actual application needs of flexible charging station resources of virtual power plants to participate in the power market, effectively solving the technical problems of difficulty in evaluating the regulation capacity of charging station resources, difficulty in calculating the profit boundary of market participation, and difficulty in regulating the release of regulation capacity of charging piles; the present invention constructs a detailed overall full-process scheme for down-regulation capacity evaluation, profit boundary analysis, regulation and release of regulation capacity, and response regulation profit effect calculation of charging station resources in virtual power plants, thereby providing reference and guidance for operation and regulation management of charging station resources and charging pile resources in virtual power plants, market profit effect analysis, pre-assessment of grid-load interactive regulation capacity, and regulation instruction generation method. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 The flowchart schematically shows a method for evaluating, calculating and controlling the regulation capability of charging station resources in a virtual power plant according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only intended to enable those skilled in the art to better understand and implement the present invention, rather than to imply any limitation on the scope of the present invention.

[0058] As used herein, the term "including" and variations thereof are to be interpreted as open-ended terms meaning "including, but not limited to." The term "based on" is to be interpreted as "based, at least in part, on." The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment."

[0059] Figure 1 Schematically shows a flow chart of a method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant according to an embodiment of the present invention. Figure 1 As shown, in this embodiment, the method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant is characterized by including:

[0060] Establish a baseline load calculation model for charging station resources in a virtual power plant, including: a baseline load calculation model for charging station resources on weekdays, a baseline load calculation model for charging station resources on weekends, and a baseline load calculation model for charging station resources on statutory holidays;

[0061] Based on the baseline load calculation model of charging station resources in the virtual power plant, a calculation model for evaluating the down-regulation capability of charging station resources in the virtual power plant is established, including: a calculation model for evaluating the predicted real-time maximum down-regulation capability, a calculation model for evaluating the real-time maximum down-regulation capability during the response period, and a calculation model for evaluating the willingness down-regulation capability during the response period;

[0062] Based on the calculation model for evaluating the regulation capability of charging station resources in the virtual power plant, a profit boundary analysis model for regulating the response of charging station resources in the virtual power plant is established, and the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant is calculated and solved to obtain the lower limit of the willingness of the charging station resources in the virtual power plant to respond during the period.

[0063] Based on the profit boundary analysis model of the regulation response of the charging station resources in the virtual power plant, a regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant is established, and regulation instructions are generated and issued according to the output of the regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant;

[0064] Based on the regulation model for releasing the regulation capacity of charging station resources in the virtual power plant, a profit-making effect calculation model for regulating the response of charging station resources in the virtual power plant is established to evaluate and calculate the profit-making effect of regulating the response of charging station resources in the virtual power plant;

[0065] Collect initialization startup data information of regulation capacity evaluation calculation and control under the virtual power plant's charging station resources, input the collected initialization startup data information into the baseline load calculation model of the charging station resources in the virtual power plant, the regulation capacity evaluation calculation model under the virtual power plant's charging station resources, the regulation response control profit boundary analysis model under the virtual power plant's charging station resources, the regulation model of regulation capacity release under the virtual power plant's charging station resources and the regulation response control profit effect calculation model under the virtual power plant's charging station resources, and output the regulation capacity evaluation calculation and control result data information under the virtual power plant's charging station resources.

[0066] Further, according to one embodiment of the present invention,

[0067] The working day baseline load calculation model for charging station resources in the virtual power plant selects five consecutive normal working days before the response invitation day as typical days. The selected five normal working days have excluded the response day and the orderly power consumption execution day. In this embodiment, the response invitation day is the invitation date for inviting the charging station in the virtual power plant to participate in the adjustment response; the response day is the date on which the charging station in the virtual power plant participates in the adjustment; the orderly power consumption execution day is the date on which the power grid company has implemented orderly power consumption; the normal working day is the normal working day from Monday to Friday, and the normal working day.

[0068] The expression of the working day baseline load calculation model of charging station resources in the virtual power plant is as follows:

[0069]

[0070] Where: For charging station resources working day at time t Baseline load value; The first of five consecutive normal working days before the charging station resource response invitation date d working days at time t Historical electricity load values; For charging station resources, please work for 5 consecutive normal working days before the invitation date. t The maximum value of historical power load; For charging station resources, please work for 5 consecutive normal working days before the invitation date. t The minimum value of the historical power load value; Ξmax{*} is the maximum value function among multiple data; Ξmin{*} is the minimum value function among multiple data;

[0071] The baseline load calculation model for charging station resources on weekends in the virtual power plant selects five consecutive normal weekends before the response invitation day as typical days. The five normal working days selected have already excluded the response day and the orderly power consumption execution day. The expression of the baseline load calculation model for charging station resources on weekends in the virtual power plant is as follows:

[0072]

[0073] Where: For charging station resources on weekends at time t Baseline load value; The first of five consecutive normal weekends before the day of the charging station resource response invitation q Weekdays off at time t Historical electricity load values; The maximum value of the historical power load value at time t for five consecutive normal weekends before the charging station resource response invitation; is the minimum historical power load value of the five consecutive normal weekends at time t before the charging station resource response invitation; Ξmax{*} is the maximum value function among multiple data; Ξmin{*} is the minimum value function among multiple data;

[0074] The statutory holiday baseline load calculation model for charging station resources in the virtual power plant directly selects historical days that did not participate in the response (excluding the days that participated in the down-regulation) as typical days. The selected typical days have excluded the response days and the orderly power consumption execution days. The expression of the statutory holiday baseline load calculation model for charging station resources in the virtual power plant is as follows:

[0075]

[0076] Where: is the baseline load value of the charging station resource on statutory holidays at time t; It is the historical daily electricity load value of charging station resources during statutory holidays.

[0077] Furthermore, according to one embodiment of the present invention, the expression of the real-time maximum down-regulation capability evaluation calculation model is as follows:

[0078]

[0079] Where: Predicting the real-time maximum down-regulation capacity for charging station resources in virtual power plants; The power load value of a sampling point of the charging station resource in the virtual power plant; The power load value of the latest sampling point of the charging station resources in the virtual power plant; Predict the power load value of the first sampling point in the future for the charging station resources in the virtual power plant; Predict the power load value of the second sampling point in the future for the charging station resources in the virtual power plant; is the minimum safety load requirement for the operation and maintenance of charging station resources in the virtual power plant; Δt is the interval between power sampling points for the power load of charging station resources in the virtual power plant;

[0080] The expression of the calculation model for evaluating the real-time maximum down-regulation capability during the response period is as follows:

[0081]

[0082] Where: It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the baseline load value of the charging station resource at time t on a working day; is the baseline load value of the charging station resource at time t on weekends; is the baseline load value of the charging station resource on statutory holidays at time t; The minimum safety load requirement for operation and maintenance of charging station resources in the virtual power plant; Ω response is a set of time periods for charging station resource response periods; A function that operates on one of multiple data values;

[0083] The expression of the calculation model for regulatory ability evaluation under the response period willingness is as follows:

[0084]

[0085] Where: The adjustment capability of charging station resources in the virtual power plant under the willingness response period; The willingness of charging station resources to respond in the virtual power plant is 0, indicating no response to regulation, and 1 indicates the maximum degree of participation in response regulation. is the real-time maximum down-regulation capability of the charging station resource response period in the virtual power plant; Ξmin{*} is the minimum value function among multiple data; It is the minimum security load requirement for the operation and maintenance of charging station resources in the virtual power plant.

[0086] Furthermore, according to one embodiment of the present invention, the profit boundary analysis model for regulating the response of charging station resources in a virtual power plant is expressed as follows:

[0087]

[0088] Where: Ω response is a set of time periods for charging station resource response periods; is the time-of-use electricity price of the charging service of the charging station in the virtual power plant at time t; is the time-sharing price of the charging service of the charging station in the virtual power plant at time t; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the adjustment capacity of the charging station resource response period willingness in the virtual power plant; Δt is the interval time between the power sampling points of the charging station resource power load in the virtual power plant; ε loss cost ΣΩ is the unit comprehensive loss cost of the charging load demand caused by the interruption of charging station resources in the virtual power plant, which includes the cost of compensating charging users, regulation costs, operation and maintenance costs, labor costs, etc. response is the total length of the charging station resource response period; β response price is the unit compensation income of the charging station resource response period in the virtual power plant; is the willingness of charging station resources to respond in the virtual power plant. A value of 0 indicates no response to regulation, and a value of 1 indicates maximum participation in response regulation. start The starting time of the charging station resource response period;

[0089] In this embodiment, the profit boundary analysis model of the regulation response control of charging station resources in the virtual power plant is calculated and solved. The lower limit of If the lower limit value of is 0, it means that there is no profit space for response regulation and no response regulation should be made; if If the lower limit value is greater than 0, it means that there is profit space when participating in response regulation at least at this lower limit value.

[0090] Furthermore, according to an embodiment of the present invention, responsive regulation is performed based on profit margins to release the regulation capacity. The regulation model for releasing the regulation capacity under the charging station resources in the virtual power plant is expressed as follows:

[0091]

[0092] Where: is the control instruction received by the charging station resources in the virtual power plant at time t; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; The adjustment capability of charging station resources in the virtual power plant under the willingness response period; is the control instruction received by each charging pile within the charging station resources in the virtual power plant at time t; The smallest positive integer operation function whose upward value is greater than the operation result, and the minimum result of this operation function is 1; The rated charging power of the charging piles within the charging station resources in the virtual power plant; The minimum power for charging the charging piles within the charging station resources in the virtual power plant; Ωresponse is a set of time periods for charging station resource response periods; The intermediate process quantity related to the evaluation and calculation of the control instructions received by each charging pile within the charging station resources in the virtual power plant at time t;

[0093] In this embodiment, the control instructions are produced and issued according to the output of the control model of the charging station resource regulation capacity release in the virtual power plant. The output of the station control system at the charging station resource level is Tracking execution instructions for charging stations; output Down to each charging pile within the charging station resources, the output Execute instructions for tracking charging piles.

[0094] Further, according to an embodiment of the present invention, according to the above steps, There is profit space when the lower limit value of participates in response regulation, and the regulation model for releasing the regulation capacity of charging station resources in the virtual power plant is used to release the regulation capacity. Based on this, the profit effect of the regulation response regulation of charging station resources in the virtual power plant can be evaluated and calculated according to the actual regulation situation. The expression of the profit effect calculation model of the regulation response regulation of charging station resources in the virtual power plant is as follows:

[0095]

[0096] Where: Ω is the profit value of the charging station resource adjustment in the virtual power plant; response is a set of time periods for charging station resource response periods; is the time-of-use electricity price of the charging service of the charging station in the virtual power plant at time t; is the time-sharing price of the charging service of the charging station in the virtual power plant at time t; is the control instruction received by each charging pile within the charging station resources in the virtual power plant at time t; The smallest positive integer operation function whose upward value is greater than the operation result, and the minimum result of this operation function is 1; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the rated charging power of the charging pile within the charging station resources in the virtual power plant; Δt is the interval between the power sampling points of the power load of the charging station resources in the virtual power plant; is the adjustment capacity of charging station resources in the virtual power plant under the willingness response period; β response price is the unit compensation income of the charging station resource response period in the virtual power plant; ΣΩ responseis the total length of the charging station resource response period; ε loss cost The unit comprehensive loss cost of the charging load demand caused by the interruption of charging station resources in the virtual power plant includes the cost of compensating charging users, regulation cost, operation and maintenance cost, labor cost, etc.; start The starting time of the charging station resource response period.

[0097] Furthermore, according to an embodiment of the present invention, collecting initialization startup data information for evaluating, calculating, and regulating the regulation capacity of charging station resources in a virtual power plant includes:

[0098] The historical electricity load values on the invitation day and the five consecutive normal working days before the invitation day, the historical electricity load values on the five consecutive normal weekends before the invitation day, the historical electricity load values on the same days of statutory holidays, the historical electricity load power values at the two sampling points before the current moment, the predicted electricity load power values at the two sampling points before the current moment, the interval between the sampling points of the electricity load power of the charging station resources, the minimum security load requirement for the operation and maintenance of the charging station resources, the set of time periods of the charging station resource response period, the charging time-of-use electricity price of the charging service of the charging station in the virtual power plant at each time, the service fee time-of-use price of the charging service of the charging station in the virtual power plant at each time, the unit comprehensive loss cost of the charging load demand of the charging station resources in the virtual power plant due to interruption, the total length of the charging station resource response period, the unit compensation income of the charging station resource response period in the virtual power plant, the rated charging power of the charging piles within the charging station resources in the virtual power plant, and the minimum charging operation power of the charging piles within the charging station resources in the virtual power plant;

[0099] Outputs the calculation and control result data of the regulation capacity evaluation of charging station resources in the virtual power plant, including:

[0100] The baseline load values of charging station resources at various times on weekdays, the baseline load values of charging station resources at various times on weekends, the baseline load values of charging station resources at various times on statutory holidays, the predicted real-time maximum down-regulation capacity of charging station resources in the virtual power plant, the real-time maximum down-regulation capacity of charging station resources in the virtual power plant during the response period, the willingness value of charging station resources in the virtual power plant during the response period, the control instructions received by charging station resources in the virtual power plant at various times, the control instructions received by each charging pile within the charging station resources in the virtual power plant at various times, and the control profit value of the down-regulation response of charging station resources in the virtual power plant.

[0101] According to the above-mentioned solution of the present invention, the present invention comprehensively considers multiple aspects of charging station resources, including baseline load calculation, downsizing capacity assessment, profit margin analysis, and control strategy formulation, to achieve the calculation of the regulating capacity and precise operational control of charging station resources. This invention can effectively solve the problems of difficult assessment of charging station resource regulating capacity, difficulty in calculating profit margins for market participation, and difficulty in regulating the release of regulating capacity of charging piles. It provides strong technical support for energy management, efficient operation, and precise control of regulating capacity release of charging station resources in virtual power plants.

[0102] According to the above scheme of the present invention, the present invention fully considers the whole process elements such as baseline load calculation, down-regulation capacity evaluation calculation, regulation, profit boundary analysis, and profit calculation of charging station resources in virtual power plants, and establishes a mathematical model for down-regulation capacity evaluation calculation and energy release regulation of charging station resources, which is helpful for accurate operation and regulation of charging station resources in virtual power plants, and is beneficial for charging station operation and maintenance personnel to grasp the down-regulation capacity of power station resources in real time; the present invention proposes a down-regulation capacity evaluation calculation and regulation method for charging station resources in virtual power plants based on the actual application needs of flexible charging station resources of virtual power plants to participate in the power market, which effectively solves the technical problems of difficulty in evaluating the regulation capacity of charging station resources, difficulty in calculating the profit boundary of market participation, and difficulty in regulating the release of regulation capacity of charging piles; the present invention constructs a detailed overall full-process scheme for down-regulation capacity evaluation, profit boundary analysis, regulation and release of regulation capacity, and response regulation profit effect calculation of charging station resources in virtual power plants, which can provide reference and guidance for operation and regulation management of charging station resources and charging pile resources in virtual power plants, market profit effect analysis, pre-assessment of grid-load interactive regulation capacity, and regulation instruction generation method.

[0103] Furthermore, to achieve the above-mentioned objectives, the present invention also provides a system for evaluating, calculating, and controlling the regulation capacity of charging station resources in a virtual power plant, comprising:

[0104] The first model building module establishes a baseline load calculation model for charging station resources in the virtual power plant, including: a baseline load calculation model for charging station resources on weekdays, a baseline load calculation model for charging station resources on weekends, and a baseline load calculation model for charging station resources on statutory holidays in the virtual power plant;

[0105] The second model building module establishes a calculation model for evaluating the down-regulation capability of charging station resources in the virtual power plant based on the baseline load calculation model of charging station resources in the virtual power plant, including: a calculation model for evaluating the predicted real-time maximum down-regulation capability, a calculation model for evaluating the real-time maximum down-regulation capability during the response period, and a calculation model for evaluating the willingness down-regulation capability during the response period;

[0106] The third model building module establishes a profit boundary analysis model for regulating the response of charging station resources in the virtual power plant based on the calculation model for evaluating the regulation capability of charging station resources in the virtual power plant, calculates and solves the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant, and solves the lower limit of the willingness of the charging station resources in the virtual power plant to respond during the period;

[0107] a fourth model building module, which establishes a control model for releasing the regulation capacity of charging station resources in the virtual power plant based on the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant, and generates and issues control instructions according to the output of the control model for releasing the regulation capacity of charging station resources in the virtual power plant;

[0108] a fifth model building module, based on the regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant, establishing a profit-making effect calculation model for regulating the response of the charging station resources in the virtual power plant, and evaluating and calculating the profit-making effect of regulating the response of the charging station resources in the virtual power plant;

[0109] The data information input and output module collects the initialization startup data information of the regulation capacity evaluation calculation and regulation under the virtual power plant's charging station resources, and inputs the collected initialization startup data information into the baseline load calculation model of the charging station resources in the virtual power plant, the regulation capacity evaluation calculation model under the virtual power plant's charging station resources, the regulation response regulation profit boundary analysis model under the virtual power plant's charging station resources, the regulation model of the regulation capacity release under the virtual power plant's charging station resources, and the regulation response regulation profit effect calculation model under the virtual power plant's charging station resources, and outputs the regulation capacity evaluation calculation and regulation result data information under the virtual power plant's charging station resources.

[0110] According to the above-mentioned virtual power plant charging station resource regulation capacity evaluation calculation and control system of the present invention, the above-mentioned virtual power plant charging station resource regulation capacity evaluation calculation and control method can be implemented. The specific process steps are as described above and will not be repeated here.

[0111] Furthermore, to achieve the above-mentioned purpose, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, it implements the above-mentioned method for evaluating, calculating and controlling the regulation capacity of charging station resources in the virtual power plant.

[0112] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the calculation and control method for evaluating the adjustment capacity of charging station resources in a virtual power plant as described above is implemented.

[0113] Those skilled in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented using electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0114] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method implementation methods and will not be repeated here.

[0115] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0116] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the embodiments of the present invention.

[0117] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0118] If the functions are implemented as software modules and sold or used as standalone products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the energy-saving signal transmission / reception method according to various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, ROM, RAM, a magnetic disk, or an optical disk.

[0119] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

[0120] It should be understood that the size of the serial numbers of each step in the content of the invention and the implementation methods of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation methods of the present invention.

Claims

1. A method for evaluating, calculating, and controlling the regulation capacity of charging station resources in a virtual power plant, characterized in that: include: Establish a baseline load calculation model for charging station resources in a virtual power plant, including: a baseline load calculation model for charging station resources on weekdays, a baseline load calculation model for charging station resources on weekends, and a baseline load calculation model for charging station resources on statutory holidays; Based on the baseline load calculation model of charging station resources in the virtual power plant, a calculation model for evaluating the down-regulation capability of charging station resources in the virtual power plant is established, including: a calculation model for evaluating the predicted real-time maximum down-regulation capability, a calculation model for evaluating the real-time maximum down-regulation capability during the response period, and a calculation model for evaluating the willingness down-regulation capability during the response period; Based on the calculation model for evaluating the regulation capability of charging station resources in the virtual power plant, a profit boundary analysis model for regulating the response of charging station resources in the virtual power plant is established, and the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant is calculated and solved to obtain the lower limit of the willingness of the charging station resources in the virtual power plant to respond during the period. Based on the profit boundary analysis model of the regulation response of the charging station resources in the virtual power plant, a regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant is established, and regulation instructions are generated and issued according to the output of the regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant; Based on the regulation model for releasing the regulation capacity of charging station resources in the virtual power plant, a profit-making effect calculation model for regulating the response of charging station resources in the virtual power plant is established to evaluate and calculate the profit-making effect of regulating the response of charging station resources in the virtual power plant; Collect initialization startup data information of regulation capacity evaluation calculation and control under the virtual power plant's charging station resources, input the collected initialization startup data information into the baseline load calculation model of the charging station resources in the virtual power plant, the regulation capacity evaluation calculation model under the virtual power plant's charging station resources, the regulation response control profit boundary analysis model under the virtual power plant's charging station resources, the regulation model of regulation capacity release under the virtual power plant's charging station resources and the regulation response control profit effect calculation model under the virtual power plant's charging station resources, and output the regulation capacity evaluation calculation and control result data information under the virtual power plant's charging station resources.

2. The method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant according to claim 1, characterized in that: The expression of the working day baseline load calculation model of the charging station resources in the virtual power plant is as follows: Where: For charging station resources working day at time t Baseline load value; The first of five consecutive normal working days before the charging station resource response invitation date d working days at time t Historical electricity load values; For charging station resources, please work for 5 consecutive normal working days before the invitation date. t The maximum value of historical power load; For charging station resources, please work for 5 consecutive normal working days before the invitation date. t The minimum value of the historical power load value; Ξmax{*} is the maximum value function among multiple data; Ξmin{*} is the minimum value function among multiple data; The expression of the baseline load calculation model for charging station resources on weekends in the virtual power plant is as follows: Where: For charging station resources on weekends at time t Baseline load value; The first of five consecutive normal weekends before the day of the charging station resource response invitation q Weekdays off at time t Historical electricity load values; For charging station resources, respond to the invitation for 5 consecutive normal weekends before the date of the invitation. t The maximum value of historical power load; For charging station resources, respond to the invitation for 5 consecutive normal weekends before the date of the invitation. t The minimum value of the historical power load value; Ξmax{*} is the maximum value function among multiple data; Ξmin{*} is the minimum value function among multiple data; The expression of the statutory holiday baseline load calculation model for charging station resources in the virtual power plant is as follows: Where: is the baseline load value of the charging station resource on statutory holidays at time t; It is the historical daily electricity load value of charging station resources during statutory holidays.

3. The method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant according to claim 1, characterized in that: The expression of the predicted real-time maximum down-regulation capability evaluation calculation model is as follows: Where: Predicting the real-time maximum down-regulation capacity for charging station resources in virtual power plants; The power load value of a sampling point of the charging station resource in the virtual power plant; The power load value of the latest sampling point of the charging station resources in the virtual power plant; Predict the power load value of the first sampling point in the future for the charging station resources in the virtual power plant; Predict the power load value of the second sampling point in the future for the charging station resources in the virtual power plant; is the minimum safety load requirement for the operation and maintenance of charging station resources in the virtual power plant; Δt is the interval between power sampling points for the power load of charging station resources in the virtual power plant; The expression of the response period real-time maximum down-regulation capability evaluation calculation model is as follows: Where: It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the baseline load value of the charging station resource at time t on a working day; is the baseline load value of the charging station resource at time t on weekends; is the baseline load value of the charging station resource on statutory holidays at time t; The minimum safety load requirement for operation and maintenance of charging station resources in the virtual power plant; Ω response is a set of time periods for charging station resource response periods; A function that operates on one of multiple data values; The expression of the calculation model for evaluating the regulatory ability under the response period willingness is as follows: Where: The adjustment capability of charging station resources in the virtual power plant under the willingness response period; The willingness of charging station resources to respond in the virtual power plant is 0, indicating no response to regulation, and 1 indicates the maximum degree of participation in response regulation. is the real-time maximum down-regulation capability of the charging station resource response period in the virtual power plant; Ξmin{*} is the minimum value function among multiple data; It is the minimum security load requirement for the operation and maintenance of charging station resources in the virtual power plant.

4. The method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant according to claim 1, characterized in that: The expression of the profit boundary analysis model for regulating response and control of charging station resources in the virtual power plant is as follows: Where: Ω response is a set of time periods for charging station resource response periods; is the time-of-use electricity price of the charging service of the charging station in the virtual power plant at time t; is the time-sharing price of the charging service of the charging station in the virtual power plant at time t; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the adjustment capacity of the charging station resource response period willingness in the virtual power plant; Δt is the interval time between the power sampling points of the charging station resource power load in the virtual power plant; ε losscost ΣΩ is the unit comprehensive loss cost of the charging load demand caused by the interruption of charging station resources in the virtual power plant, which includes the cost of compensating charging users, regulation costs, operation and maintenance costs, labor costs, etc. response is the total length of the charging station resource response period; β responseprice is the unit compensation income of the charging station resource response period in the virtual power plant; is the willingness of charging station resources to respond in the virtual power plant. A value of 0 indicates no response to regulation, and a value of 1 indicates maximum participation in response regulation. start The starting time of the charging station resource response period; The profit boundary analysis model of the regulation response control of charging station resources in the virtual power plant is calculated and solved. The lower limit of If the lower limit value of is 0, it means that there is no profit space for response regulation and no response regulation should be made; if If the lower limit value is greater than 0, it means that there is profit space when participating in response regulation at least at this lower limit value.

5. The method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant according to claim 1, characterized in that: The expression for establishing the control model for releasing the regulation capacity of charging station resources in the virtual power plant is as follows: Where: is the control instruction received by the charging station resources in the virtual power plant at time t; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; The adjustment capability of charging station resources in the virtual power plant under the willingness response period; is the control instruction received by each charging pile within the charging station resources in the virtual power plant at time t; The smallest positive integer operation function whose upward value is greater than the operation result, and the minimum result of this operation function is 1; The rated charging power of the charging piles within the charging station resources in the virtual power plant; The minimum power for charging the charging piles within the charging station resources in the virtual power plant; Ω response is a set of time periods for charging station resource response periods; The intermediate process quantity related to the evaluation and calculation of the control instructions received by each charging pile within the charging station resources in the virtual power plant at time t; The control instructions are produced and issued according to the output of the control model of the regulation capacity released by the charging station resources in the virtual power plant. The output of the station control system at the charging station resource level is Tracking execution instructions for charging stations; output Down to each charging pile within the charging station resources, the output Execute instructions for tracking charging piles.

6. The method for evaluating, calculating and controlling the regulation capacity of charging station resources in a virtual power plant according to claim 1, characterized in that: The expression of the profit effect calculation model of the regulation response control under the charging station resources in the virtual power plant is as follows: Where: Ω is the profit value of the charging station resource adjustment in the virtual power plant; response is a set of time periods for charging station resource response periods; is the time-of-use electricity price of the charging service of the charging station in the virtual power plant at time t; is the time-sharing price of the charging service of the charging station in the virtual power plant at time t; is the control instruction received by each charging pile within the charging station resources in the virtual power plant at time t; The smallest positive integer operation function whose upward value is greater than the operation result, and the minimum result of this operation function is 1; It is the real-time maximum down-regulation capability of the charging station resources in the virtual power plant during the response period; is the rated charging power of the charging pile within the charging station resources in the virtual power plant; Δt is the interval between the power sampling points of the power load of the charging station resources in the virtual power plant; is the adjustment capacity of charging station resources in the virtual power plant under the willingness response period; β responseprice is the unit compensation income of the charging station resource response period in the virtual power plant; ΣΩ response is the total length of the charging station resource response period; ε losscost The unit comprehensive loss cost of the charging load demand caused by the interruption of charging station resources in the virtual power plant includes the cost of compensating charging users, regulation cost, operation and maintenance cost, labor cost, etc.; start The starting time of the charging station resource response period.

7. The method for evaluating, calculating and controlling the regulation capability of charging station resources in a virtual power plant according to any one of claims 1 to 6, characterized in that: The collection of initialization startup data information for evaluating, calculating, and regulating the regulation capacity of charging station resources in the virtual power plant includes: The historical electricity load values on the invitation day and the five consecutive normal working days before the invitation day, the historical electricity load values on the five consecutive normal weekends before the invitation day, the historical electricity load values on the same days of statutory holidays, the historical electricity load power values at the two sampling points before the current moment, the predicted electricity load power values at the two sampling points before the current moment, the interval between the sampling points of the electricity load power of the charging station resources, the minimum security load requirement for the operation and maintenance of the charging station resources, the set of time periods of the charging station resource response period, the charging time-of-use electricity price of the charging service of the charging station in the virtual power plant at each time, the service fee time-of-use price of the charging service of the charging station in the virtual power plant at each time, the unit comprehensive loss cost of the charging load demand of the charging station resources in the virtual power plant due to interruption, the total length of the charging station resource response period, the unit compensation income of the charging station resource response period in the virtual power plant, the rated charging power of the charging piles within the charging station resources in the virtual power plant, and the minimum charging operation power of the charging piles within the charging station resources in the virtual power plant; The output of the virtual power plant charging station resource regulation capacity evaluation calculation and regulation result data information includes: The baseline load values of charging station resources at various times on weekdays, the baseline load values of charging station resources at various times on weekends, the baseline load values of charging station resources at various times on statutory holidays, the predicted real-time maximum down-regulation capacity of charging station resources in the virtual power plant, the real-time maximum down-regulation capacity of charging station resources in the virtual power plant during the response period, the willingness value of charging station resources in the virtual power plant during the response period, the control instructions received by charging station resources in the virtual power plant at various times, the control instructions received by each charging pile within the charging station resources in the virtual power plant at various times, and the control profit value of the down-regulation response of charging station resources in the virtual power plant.

8. The evaluation, calculation and control system for regulating capacity of charging station resources in virtual power plants is characterized by: include: The first model building module establishes a baseline load calculation model for charging station resources in the virtual power plant, including: a baseline load calculation model for charging station resources on weekdays, a baseline load calculation model for charging station resources on weekends, and a baseline load calculation model for charging station resources on statutory holidays in the virtual power plant; The second model building module establishes a calculation model for evaluating the down-regulation capability of charging station resources in the virtual power plant based on the baseline load calculation model of charging station resources in the virtual power plant, including: a calculation model for evaluating the predicted real-time maximum down-regulation capability, a calculation model for evaluating the real-time maximum down-regulation capability during the response period, and a calculation model for evaluating the willingness down-regulation capability during the response period; The third model building module establishes a profit boundary analysis model for regulating the response of charging station resources in the virtual power plant based on the calculation model for evaluating the regulation capability of charging station resources in the virtual power plant, calculates and solves the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant, and solves the lower limit of the willingness of the charging station resources in the virtual power plant to respond during the period; a fourth model building module, which establishes a control model for releasing the regulation capacity of charging station resources in the virtual power plant based on the profit boundary analysis model for regulating the response of charging station resources in the virtual power plant, and generates and issues control instructions according to the output of the control model for releasing the regulation capacity of charging station resources in the virtual power plant; a fifth model building module, based on the regulation model for releasing the regulation capacity of the charging station resources in the virtual power plant, establishing a profit-making effect calculation model for regulating the response of the charging station resources in the virtual power plant, and evaluating and calculating the profit-making effect of regulating the response of the charging station resources in the virtual power plant; The data information input and output module collects the initialization startup data information of the regulation capacity evaluation calculation and regulation under the virtual power plant's charging station resources, and inputs the collected initialization startup data information into the baseline load calculation model of the charging station resources in the virtual power plant, the regulation capacity evaluation calculation model under the virtual power plant's charging station resources, the regulation response regulation profit boundary analysis model under the virtual power plant's charging station resources, the regulation model of the regulation capacity release under the virtual power plant's charging station resources, and the regulation response regulation profit effect calculation model under the virtual power plant's charging station resources, and outputs the regulation capacity evaluation calculation and regulation result data information under the virtual power plant's charging station resources.

9. An electronic device, characterized in that It includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the method for evaluating, calculating, and controlling the regulation capacity of charging station resources in a virtual power plant as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for evaluating, calculating, and controlling the regulation capacity of charging station resources in a virtual power plant according to any one of claims 1 to 7.

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