Charging and discharging control method of wind power plant energy storage system, storage medium and program product

Abstract

The invention provides a charging and discharging control method of a wind power plant energy storage system, a storage medium and a program product, the charging and discharging control method is used for a third-party control platform, the third-party control platform is in communication connection with a safety access area of a wind power plant through a communication line, and the safety access area is connected with a control system of the wind power plant. The charging and discharging control method comprises the following steps: acquiring wind power plant operation information and energy storage information of a wind power plant from a safety access area; acquiring power transaction information from a power transaction system; constructing a charging and discharging strategy optimization model according to the wind power plant operation information, the energy storage information and the power transaction information; solving the charging and discharging strategy optimization model to obtain a charging and discharging strategy; the charging and discharging strategy is sent to the safety access area in a target data format, so that the safety access area forwards the charging and discharging strategy to a control system, and the target data format comprises a specified data format of reverse isolation equipment of the safety access area. The charging and discharging strategy can be optimized under the condition of low investment, and the utilization efficiency of wind energy is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of wind power energy storage, and more specifically, to a charge and discharge control method, storage medium, and program product for a wind farm energy storage system. Background Art

[0002] The rapid development of wind power and photovoltaics has led to the large-scale integration of new energy sources into the grid. At the same time, the volatility of these new energy sources has posed significant challenges to grid absorption. Energy storage, with its advantages of rapid frequency regulation, peak-to-valley shifting, and improved grid stability, has become a key development direction for addressing the challenges of large-scale new energy absorption and building a new power system.

[0003] However, when wind farms are equipped with energy storage, charging and discharging strategies are primarily formulated based on experience, primarily exploiting peak-valley price differences by charging at low prices and discharging at high prices. This strategy fails to fully consider the impact of energy storage charging and discharging on the wind farm's overall revenue in the spot electricity market. Furthermore, in actual transactions, financial transactions are conducted upfront, with physical delivery of electricity later. Simply formulating charging and discharging strategies based solely on experience can lead to irrational charging and discharging, impacting the overall operational safety and stability of the wind farm. In other words, existing strategy optimization models are unable to meet the actual operational requirements of wind farm energy storage. While more complex optimization methods can theoretically meet these requirements, they consume significant computing power, require the configuration of appropriate hardware for the wind farm, and incur ongoing maintenance costs, significantly increasing wind farm operation and maintenance costs. This diminishes the profit gains from optimizing energy storage charging and discharging strategies, hinders the widespread adoption of energy storage charging and discharging strategy optimization solutions, and, in the long term, hinders the efficient utilization of wind energy. Summary of the Invention

[0004] Therefore, how to balance the actual operational needs of wind farm supporting energy storage and the operation and maintenance costs of wind farms is crucial for the efficient use of wind energy.

[0005] In a general aspect, a charge and discharge control method for a wind farm energy storage system is provided, the charge and discharge control method being used for a third-party control platform, the third-party control platform being communicatively connected to a safe access area of ​​the wind farm via a communication line, the safe access area being connected to a control system of the wind farm, the charge and discharge control method comprising: obtaining wind farm operation information and energy storage information of the wind farm from the safe access area; obtaining power trading information from a power trading system; constructing a charge and discharge strategy optimization model based on the wind farm operation information, the energy storage information and the power trading information; solving the charge and discharge strategy optimization model to obtain a charge and discharge strategy; and sending the charge and discharge strategy to the safe access area in a target data format so that the safe access area forwards the charge and discharge strategy to the control system, the target data format including a specified data format of a reverse isolation device of the safe access area.

[0006] Optionally, the secure access zone includes a first gateway, a reverse isolation device, and a second gateway connected in sequence, the first gateway is communicatively connected to the third-party control platform, and the second gateway is communicatively connected to the control system, wherein sending the charge and discharge strategy in the target data format to the secure access zone includes: sending the charge and discharge strategy and format conversion instructions to the first gateway, so that the first gateway converts the charge and discharge strategy into the specified data format according to the format conversion instructions and sends it to the second gateway via the reverse isolation device, so that the second gateway restores the original data format of the charge and discharge strategy and sends it to the control system.

[0007] Optionally, obtaining the wind farm operation information and energy storage information of the wind farm from the secure access area includes: sending an information acquisition request to the secure access area in the target data format, so that the secure access area forwards the information acquisition request to the control system to request the control system to return the wind farm operation information and the energy storage information within a future target time period at the time required by the information acquisition request.

[0008] Optionally, the third-party control platform and the control system synchronously store at least one control scenario information, each control scenario information corresponds to a different charging and discharging control scenario, and each control scenario information includes an information acquisition time, wherein the sending of an information acquisition request to the secure access zone in the target data format, so that the secure access zone forwards the information acquisition request to the control system, to request the control system to return the wind farm operation information and the energy storage information according to the time required by the information acquisition request within a future target time period, includes: sending an information acquisition request for the target control scenario to the secure access zone in the target data format, so that the secure access zone forwards the information acquisition request for the target control scenario to the control system, to request the control system to query the information acquisition time corresponding to the target control scenario, and to return the wind farm operation information and the energy storage information according to the queried information acquisition time within the future target time period.

[0009] Optionally, constructing a charging and discharging strategy optimization model based on the wind farm operation information, the energy storage information and the power trading information includes: based on the wind farm operation information, the energy storage information and the power trading information, taking the charging and discharging amount of the target time period as an independent variable, constructing an objective function with the goal of maximizing the trading data revenue, and constructing energy storage constraints to obtain the charging and discharging strategy optimization model including the objective function and the energy storage constraints, wherein the charging and discharging strategy obtained by solving the charging and discharging strategy optimization model includes a charging and discharging sequence, and the charging and discharging sequence includes the charging and discharging amounts at multiple moments within the target time period.

[0010] Optionally, solving the charge-discharge strategy optimization model to obtain the charge-discharge strategy includes: obtaining multiple initial individuals in each iterative cycle, wherein each initial individual corresponds to a charge-discharge sequence of an initial charge-discharge strategy; performing mutation processing on the multiple initial individuals to obtain multiple variant individuals corresponding to the multiple initial individuals; performing crossover processing on each initial individual and the corresponding variant individual to obtain a crossover individual; determining one from the initial individuals and the corresponding crossover individuals as an iterative individual based on the objective function value of each initial individual and the objective function value of the crossover individual corresponding to the initial individual; using the iterative individual as the initial individual of the next iterative cycle until a preset end condition is met, determining one from the multiple iterative individuals, and using the candidate charge-discharge strategy corresponding to the determined iterative individual as the solved charge-discharge strategy.

[0011] Optionally, performing mutation processing on the multiple initial individuals to obtain multiple mutant individuals corresponding to the multiple initial individuals includes: randomly dividing the multiple initial individuals into multiple initial individual pairs, wherein each initial individual pair consists of two initial individuals; for each initial individual pair, recording the initial individual with a high objective function value as a winning individual, and recording the initial individual with a low objective function value as a losing individual; performing different mutation processing on the winning individuals and the losing individuals, respectively, to obtain the multiple mutant individuals corresponding to the multiple initial individuals.

[0012] Optionally, different mutation processing is performed on the winning individuals and the losing individuals respectively to obtain the multiple mutant individuals corresponding to the multiple initial individuals, including: randomly selecting three different winning individuals, taking one of the winning individuals as the winning reference vector, and determining a winning differential vector based on the other two winning individuals; determining a winning mutation vector based on the winning reference vector and the winning differential vector to obtain a mutant individual.

[0013] Optionally, different mutation processing is performed on the winning individuals and the losing individuals respectively to obtain the multiple mutant individuals corresponding to the multiple initial individuals, including: taking a losing individual as a failure reference vector; determining a first failure differential vector based on the losing individual and the winning individual that forms an initial individual pair with it; randomly selecting a winning individual and a losing individual, and determining a second failure differential vector based on the randomly selected winning individual and losing individual; determining a failure mutation vector based on the failure reference vector, the first failure differential vector and the second failure differential vector to obtain a mutant individual.

[0014] Optionally, different mutation processing is performed on the winning individuals and the losing individuals respectively to obtain the multiple mutant individuals corresponding to the multiple initial individuals, including: when the current iteration cycle is in the first mutation stage, different preset mutation processing is performed on the winning individuals and the losing individuals respectively to obtain the multiple mutant individuals corresponding to the multiple initial individuals; when the current iteration cycle is in the second mutation stage, different preset mutation processing is performed on the winning individuals and the losing individuals respectively, and perturbation mutation individuals are added according to preset probabilities to obtain the multiple mutant individuals corresponding to the multiple initial individuals, wherein the first mutation stage is earlier than the second mutation stage.

[0015] Optionally, the disturbance variation individual is obtained by the following steps: for each charge and discharge amount in the current initial individual, a reference Levy distribution is obtained with the charge and discharge amount as the center position of a preset Levy distribution; a data that obeys the reference Levy distribution is determined as the disturbance variation charge and discharge amount corresponding to the charge and discharge amount, to obtain the disturbance variation individual, wherein the disturbance variation individual includes the disturbance variation charge and discharge amount corresponding to each charge and discharge amount in the current initial individual.

[0016] Optionally, the mutation scaling factor used in the mutation process decreases nonlinearly with increasing iteration cycles.

[0017] Optionally, the crossover processing of each initial individual and the corresponding variant individual to obtain the crossover individual includes: when the current iteration cycle is in the first crossover stage, using a first crossover rate to crossover each initial individual and the corresponding variant individual to obtain the crossover individual, wherein the first crossover rate decreases with increasing iteration cycles; when the current iteration cycle is in the second crossover stage, using a second crossover rate to crossover each initial individual and the corresponding variant individual to obtain the crossover individual, wherein the second crossover rate is positively correlated with the descending ranking of the objective function value of the initial individual among the multiple initial individuals.

[0018] In another general aspect, a charge and discharge control device for a wind farm energy storage system is provided, the charge and discharge control device being used for a third-party control platform, the third-party control platform being communicatively connected to a safe access area of ​​the wind farm via a communication line, the safe access area being connected to a control system of the wind farm, the charge and discharge control device comprising: a first acquisition unit configured to acquire wind farm operation information and energy storage information of the wind farm from the safe access area; a second acquisition unit configured to acquire power trading information from a power trading system; a model construction unit configured to construct a charge and discharge strategy optimization model based on the wind farm operation information, the energy storage information and the power trading information; a strategy solving unit configured to solve the charge and discharge strategy optimization model to obtain a charge and discharge strategy; a strategy sending unit configured to send the charge and discharge strategy to the safe access area in a target data format, so that the safe access area forwards the charge and discharge strategy to the control system, the target data format including a specified data format of a reverse isolation device of the safe access area.

[0019] In another general aspect, a computer-readable storage medium is provided, which, when instructions in the computer-readable storage medium are executed by at least one processor, prompts the at least one processor to execute the above-mentioned method for controlling charging and discharging of a wind farm energy storage system.

[0020] In another general aspect, a computer device is provided, comprising: at least one processor; and at least one memory storing computer-executable instructions, wherein the computer-executable instructions, when executed by the at least one processor, cause the at least one processor to execute the above-described method for controlling charging and discharging of a wind farm energy storage system.

[0021] In another general aspect, a computer program product is provided, comprising computer instructions, which, when executed by at least one processor, prompt the at least one processor to execute the above-mentioned method for controlling charging and discharging of a wind farm energy storage system.

[0022] The present disclosure provides a charge and discharge control method, storage medium, and program product for a wind farm energy storage system. By establishing a charge and discharge control method for a wind farm energy storage system executed by a third-party control platform, it is possible to combine information from multiple sources to establish and solve a charge and discharge strategy optimization model with higher computational accuracy, thereby meeting the actual operational needs of supporting energy storage in wind farms. Furthermore, the solved charge and discharge strategy is distributed to the wind farm's control system via the wind farm's secure access zone, eliminating the need to configure additional computing hardware for the wind farm to build and solve the model. This allows for charge and discharge strategy optimization with low investment, effectively improving wind energy utilization efficiency.

[0023] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart illustrating a method for controlling charging and discharging of a wind farm energy storage system according to an embodiment of the present disclosure.

[0025] Figure 2 is a schematic flow chart illustrating a method for controlling charging and discharging of a wind farm energy storage system according to an embodiment of the present disclosure.

[0026] Figure 3 is a topology diagram illustrating a third-party control platform and an internal network of a wind farm according to an embodiment of the present disclosure.

[0027] Figure 4 FIG. 4 is a flow chart illustrating steps for solving a charge and discharge strategy according to an embodiment of the present disclosure.

[0028] Figure 5 is a block diagram illustrating a charge and discharge control device for a wind farm energy storage system according to an embodiment of the present disclosure.

[0029] Figure 6 is a block diagram illustrating a computer device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0030] The following detailed description is provided to help the reader gain a comprehensive understanding of the methods, devices and / or systems described herein. However, various changes, modifications and equivalents of the methods, devices and / or systems described herein will be clear after understanding the disclosure of the present application. For example, the order of operations described herein is merely an example and is not limited to those orders set forth herein, but can be changed as will be clear after understanding the disclosure of the present application, except for operations that must occur in a specific order. In addition, for greater clarity and conciseness, descriptions of features known in the art may be omitted.

[0031] The features described herein can be implemented in different forms and should not be construed as limited to the examples described herein. Rather, the examples described herein are provided to illustrate only some of the many possible ways to implement the methods, devices, and / or systems described herein, which will become clear after understanding the disclosure of this application.

[0032] As used herein, the term "and / or" includes any one of the associated listed items and any combination of any two or more.

[0033] Although terms such as "first," "second," and "third" may be used herein to describe various members, components, regions, layers, or portions, these members, components, regions, layers, or portions should not be limited by these terms. Instead, these terms are used solely to distinguish one member, component, region, layer, or portion from another member, component, region, layer, or portion. Thus, what is referred to as a first member, first component, first region, first layer, or first portion in the examples described herein may also be referred to as a second member, second component, second region, second layer, or second portion without departing from the teachings of the examples.

[0034] In the specification, when an element (such as a layer, region, or substrate) is described as being “on,” “connected to,” or “coupled to” another element, the element may be directly “on,” “connected to,” or “coupled to” the other element, or one or more other elements may be present therebetween. Conversely, when an element is described as being “directly on,” “directly connected to,” or “directly coupled to” another element, there may be no other elements present therebetween.

[0035] The terms used herein are only used to describe various examples and are not intended to limit the disclosure. Unless the context clearly indicates otherwise, the singular is intended to include the plural. The terms "comprise," "include," and "have" indicate the presence of the recited features, quantities, operations, components, elements, and / or combinations thereof, but do not preclude the presence or addition of one or more other features, quantities, operations, components, elements, and / or combinations thereof.

[0036] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure pertains after understanding the present disclosure. Unless expressly defined otherwise herein, terms (such as those defined in general dictionaries) should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and should not be interpreted in an idealized or overly formal manner.

[0037] Furthermore, in describing the examples, when it is deemed that a detailed description of well-known related structures or functions would cause ambiguous interpretation of the present disclosure, such detailed description will be omitted.

[0038] Figure 1 is a flow chart illustrating a method for controlling charging and discharging of a wind farm energy storage system according to an embodiment of the present disclosure. Figure 2 This is a schematic flow chart illustrating a method for controlling the charging and discharging of a wind farm energy storage system according to an embodiment of the present disclosure. The method is used by a third-party control platform, which is connected to a secure access zone of the wind farm via a communication line. The secure access zone is connected to the wind farm's control system.

[0039] Reference Figure 1 and Figure 2 , in step S101, wind farm operation information and energy storage information of the wind farm are obtained from the safe access area.

[0040] The operating information of a wind farm is used to reflect the operating status of the wind farm. For example, it includes information describing the operating status of the wind turbines and grid dispatching AGC (Automatic Generation Control) information and other data. The former includes, for example, the actual power generation of the wind turbines during the target period, and the latter includes, for example, the power limit, the allowable deviation ratio, the approved power, etc.

[0041] Energy storage information is used to reflect the operation status of the wind farm energy storage system, including, for example, the current energy storage capacity, SOC (State of Charge) information, the rated capacity of the wind farm's supporting energy storage, and other data.

[0042] The above information will change over time, so it needs to be acquired again for each decision.

[0043] In step S102 , power transaction information is acquired from the power transaction system.

[0044] Power trading information is used to reflect the operation of the power trading system, and includes, for example, day-ahead spot market clearing quantity and price information, day-ahead spot market forecast quantity and price information, real-time spot market clearing quantity and price information, and real-time spot market forecast quantity and price information.

[0045] In step S103 , a charge-discharge strategy optimization model is constructed based on the wind farm operation information, energy storage information, and power transaction information.

[0046] The above information can affect the achievable benefits of the wind farm energy storage system after executing the charging and discharging strategy. Combining this information to build a charging and discharging strategy optimization model can help achieve overall benefits.

[0047] In step S104, the charging and discharging strategy optimization model is solved to obtain the charging and discharging strategy.

[0048] In step S105 , the charge and discharge strategy is sent to the safe access zone in a target data format so that the safe access zone forwards the charge and discharge strategy to the control system. The target data format includes a specified data format of a reverse isolation device in the safe access zone.

[0049] According to the disclosed embodiments of the wind farm energy storage system charge and discharge control method, established and executed by a third-party control platform, it is possible to combine information from multiple sources to establish and solve a charge and discharge strategy optimization model with higher computational accuracy, thereby helping to meet the actual operational needs of wind farm energy storage. Furthermore, the solved charge and discharge strategy is distributed to the wind farm's control system via the wind farm's secure access zone, eliminating the need to configure additional computing hardware for the wind farm to build and solve the model. This allows for charge and discharge strategy optimization with low investment, effectively improving wind energy utilization efficiency.

[0050] Next, the charge and discharge control method of the wind farm energy storage system according to the embodiment of the present disclosure is further introduced in detail.

[0051] Regarding the sending of the solved charge and discharge strategy, in some embodiments, optionally, the operation of sending the charge and discharge strategy to the safe access zone in the target data format in step S105 includes: sending the charge and discharge strategy to the safe access zone in a specified data format. By directly sending the specified data format of the reverse isolation device of the safe access zone, the data format of the charge and discharge strategy can be kept unchanged during the entire sending process, and since other nodes outside the reverse isolation device often have no requirements for the data format, the smooth sending of the charge and discharge strategy can also be guaranteed. It should be understood that this means that each time the third-party control platform solves a charge and discharge strategy, it must be saved or converted in accordance with the specified data format. After receiving the charge and discharge strategy, the control system needs to decode and convert the data format to read the charge and discharge strategy.

[0052] In other embodiments, optionally, referring to Figure 3, the secure access zone includes a first gateway, a reverse isolation device, and a second gateway connected in sequence. The first gateway is connected to a third-party control platform for communication, and communicates using MQTT (Message Queuing Telemetry Transport) or an internal protocol, and the second gateway is connected to the control system for communication. The operation of sending the charge and discharge strategy in the target data format to the secure access zone in step S105 includes: sending the charge and discharge strategy and the format conversion instruction to the first gateway, so that the first gateway converts the charge and discharge strategy into a specified data format according to the format conversion instruction and sends it to the second gateway via the reverse isolation device, so that the second gateway can restore the original data format of the charge and discharge strategy and send it to the control system. By configuring the format conversion instruction, the first gateway can perform corresponding format conversion on the charge and discharge strategy before sending it to the reverse isolation device, so that the converted charge and discharge strategy can pass through the reverse isolation device of the secure access zone smoothly, thereby ensuring the reliable transmission of the charge and discharge strategy. At the same time, the third-party control platform can centrally calculate the charging and discharging strategies for multiple wind farms, which is a large amount of computation. This format conversion operation means that the third-party control platform no longer needs to save or convert the calculated charging and discharging strategies to a specified data format, helping to reduce the computational load on the third-party control platform. After the second gateway receives the charging and discharging strategies in the specified data format sent by the reverse isolation device, it restores the data to the original format, allowing the control system to receive the charging and discharging strategies in the original data format and directly execute them, reducing the computational load and improving the processing efficiency of the control system.

[0053] It should be understood that there may be other data forwarding nodes between the third-party control platform and the first gateway, and between the second gateway and the control system, such as Figure 3As shown, the secure access zone may also include an on-site gateway connected between the first gateway and the third-party control platform, which is not limited in the present disclosure. As an example, the third-party control platform can configure in advance the node information of each node (including the above-mentioned other data forwarding nodes and the first gateway, reverse isolation device, and second gateway) that will be passed on the data transmission path (each wind farm corresponds to at least one data transmission path, for example, it may include a main path and a backup path). The node information includes, for example, the node's port, IP, whether it is over-isolated, and other information. When sending the charge and discharge strategy, the node information of each node of the corresponding data transmission path can be sent together with the charge and discharge strategy, so that each node along the way can send the charge and discharge strategy and node information to the next node in sequence. At this time, if the node information of a node includes "over-isolation", it means that the node is a reverse isolation device. This information can be used as a format conversion instruction. The previous node of the reverse isolation device (such as the first gateway) needs to convert the charge and discharge strategy into a specified data format and continue to send it. After the reverse isolation device receives the data, it can view the node information of the next node. If it includes "not over-isolation", it is necessary to restore the original data format of the charge and discharge strategy and continue to send it. In addition, referring to Figure 3 After receiving the charge and discharge strategy, the control system can send it to the energy storage EMS (Energy Management System). The EMS makes a comprehensive assessment based on the received charge and discharge strategy, the latest SOC information, AGC information, and grid connection point information. It then sends operating instructions to the energy storage PCS (Power Conversion System) to input or extract electrical energy into or from the battery, completing the charging and discharging operations of the wind farm's supporting energy storage. The energy storage SCADA (Supervisory Control and Data Acquisition) system is used to monitor energy storage information.

[0054] Regarding the acquisition of wind farm related information, optionally, step S101 includes: sending an information acquisition request to the secure access zone in a target data format, so that the secure access zone forwards the information acquisition request to the control system, requesting the control system to transmit back the wind farm operation information and energy storage information at the time required by the information acquisition request within the future target period. By sending the information acquisition request carrying the future target period to the control system via the secure access zone in advance, the control system can proactively send the wind farm operation information and energy storage information to the third-party control platform at a regular time according to the corresponding time requirements, so that the third-party control platform does not need to frequently request to obtain information, which simplifies the operation of the third-party control platform and reduces the communication load during the data transmission process. As an example, the information acquisition request can include a specific time within the future target period, and can also include the frequency of information transmission, such as once a day, once an hour, or once every 15 minutes. These are all implementation methods of the present disclosure and fall within the scope of protection of the present disclosure.

[0055] Further, optionally, the third-party control platform and the control system synchronously store at least one control scenario information, each control scenario information corresponding to a different charge-discharge control scenario, and each control scenario information including an information acquisition time. Accordingly, the aforementioned step of sending an information acquisition request in a target data format to the secure access zone, for the secure access zone to forward the information acquisition request to the control system, requesting the control system to transmit wind farm operation information and energy storage information back at the time specified by the information acquisition request within a future target period, includes: sending an information acquisition request for a target control scenario in a target data format to the secure access zone, for the secure access zone to forward the information acquisition request for the target control scenario to the control system, requesting the control system to query the information acquisition time corresponding to the target control scenario, and to transmit wind farm operation information and energy storage information back at the queryed information acquisition time within the future target period. By synchronously storing control scenario information for different charge-discharge control scenarios on the third-party control platform and the wind farm control system, and including the information acquisition time, the information acquisition request can simply specify the target control scenario when sending the information acquisition request, allowing the control system to independently query the information acquisition time accordingly, thereby further simplifying the content of the information acquisition request and significantly reducing the communication load during the data transmission process. As an example, the information acquisition time may include the above-mentioned future target period and the above-mentioned specific time or information sending frequency. The future target period may be a period of preset duration determined with reference to the sending time of the information acquisition request, such as a period of 1 to 3 hours from the sending time of the information acquisition request (a total of 2 hours), or a fixed period on the day when the information acquisition request is sent. The present disclosure does not limit this. Regarding different charge and discharge control scenarios and the information acquisition time in their control scenario information, as an example, different charge and discharge control scenarios may include a day-ahead electricity declaration scenario, a day-ahead electricity clearing scenario, a real-time electricity price clearing scenario, a power curve declaration and execution scenario. Since the day-ahead electricity declaration scenario is executed once a day, its information acquisition time may be the preset time on the day when the information acquisition request is sent. When the future target period is specified to include multiple days, it may also be the preset time of each day in the future target period. The day-ahead electricity clearing scenario is also executed once a day, and its information acquisition time is similar to that of the day-ahead electricity declaration scenario. The real-time electricity price clearing scenario is executed every quarter of the day, so its information acquisition time can be multiple real-time clearing moments within the specified future target period. To reserve sufficient processing time, it can also be a preset time (such as 1 minute, 30 seconds, 15 seconds, etc.) before each real-time clearing moment. The value of the preset time is related to the time required to build and solve the charging and discharging strategy optimization model. The power curve declaration and execution scenario is executed according to the frequency issued by the scheduling AGC. In this case, the frequency issued by the scheduling AGC can be used as the information transmission frequency, achieving minute-level policy refresh.

[0056] Regarding the construction of the charge and discharge strategy optimization model, refer to Figure 2 Optionally, step S103 includes: based on wind farm operating information, energy storage information, and power trading information, using the charge and discharge capacity during the target period as an independent variable, constructing an objective function with the goal of maximizing transaction data revenue, and establishing energy storage constraints, thereby obtaining a charge and discharge strategy optimization model that includes the objective function and energy storage constraints. The charge and discharge strategy obtained by solving the charge and discharge strategy optimization model includes a charge and discharge sequence, which includes the charge and discharge capacity at multiple moments within the target period. By using the charge and discharge capacity during the target period as the independent variable of the objective function, a charge and discharge sequence consisting of the charge and discharge capacity at multiple moments can be directly solved. Compared to a solution that uses the wind farm's overall grid-connected power as the independent variable, this method enables end-to-end data calculation, reduces subsequent data processing, and improves computational efficiency. By maximizing transaction data revenue as the goal, the overall revenue of the wind farm can be effectively guaranteed, fully meeting the actual operational requirements of the wind farm's supporting energy storage. By establishing energy storage constraints, inapplicable charge and discharge capacity calculation results can be proactively screened out, improving the validity and reliability of the calculation results.

[0057] As an example, since the objective function aims to maximize the benefits of trading data, the specific content of the objective function is related to the electricity spot trading rules. However, the relevant policies and rules in different regions vary. Here, taking Gansu Province as an example, the specific construction of the objective function and energy storage constraints is introduced.

[0058] The objective function is as follows:

[0059]

[0060] The first term in the above formula is the settlement income of the wind farm and its energy storage system (hereinafter referred to as wind storage system) in the day-ahead electricity market. d,t is the day-ahead clearing price in period t, Q d,t is the day-ahead cleared electricity quantity in period t, Q l,t is the medium- and long-term decomposition of electricity in period t, and T is the total number of periods.

[0061] The second item is the settlement income of the wind-storage system in the real-time electricity market, which includes the income of wind turbine power generation in the real-time electricity market and the income of energy storage charging and discharging in the real-time electricity market. r,t is the real-time clearing price in period t, Q rf,t is the actual power generation of the wind turbine during period t, Q t Q is the actual charge and discharge amount of the energy storage system in period t. t <0 is energy storage charging, Q t >0 is energy storage discharge, Q t =0 means no energy storage action.

[0062] In the case of wind curtailment and power rationing due to insufficient grid absorption capacity or unstable wind power generation, if the wind turbine power generation exceeds the power limit, the cost of charging the energy storage system using the excess power generated by the wind turbine in excess of the power limit is zero. The charging cost formula for energy storage in this case is as follows:

[0063]

[0064] Q AGC,t is the power limit during period t.

[0065] It should be understood that the above formula calculates the charging cost, while the objective function represents the benefit. Therefore, when substituting it into the second term of the objective function, a negative sign must be added in front, or it can be modified as follows:

[0066]

[0067] The third item is the recovery of the excess power generation income of the wind storage system. When the real-time electricity market electricity energy fee is settled, the actual power generation output of the wind storage system (the actual power generation output of the t period is Q rf,t +Q t , indicating the amount of electricity delivered physically) exceeds the real-time clearing amount (the real-time clearing amount in period t is Q rc,t , indicating the amount of electricity in financial transactions) is settled at the settlement floor price. Low,t The lower limit price of settlement in period t.

[0068] The fourth item is the assessment penalty for the deviation between the actual power generation output of the wind storage system and the issued plan value, P pu,t is the deviation assessment price in period t, Q pu,t is the deviation assessment power in period t, Q pu,t The calculation formula is:

[0069]

[0070] λ below ,λ out The allowable deviation ratios of actual power generation output being lower or higher than the planned value, respectively.

[0071] When making real-time energy storage scheduling decisions, the day-ahead spot clearing has been completed. Therefore, the decision variable of the optimization model with the goal of maximizing the settlement income of the wind storage system in the spot market is the actual charge and discharge amount Q of the energy storage system in period t. t .

[0072] The energy storage constraints mainly include two parts. The first part is the constraints on the overall operation of the wind-storage system. When the wind-storage system is connected to the grid with the same AGC, it must meet the grid connection point and power limit constraints. The AGC power limit and grid connection point power constraints that must be met are:

[0073]

[0074] q R is the approved power of the wind farm, and Δt is the time interval between adjacent time periods.

[0075] The second part is the individual constraints of the energy storage system. During operation, to ensure safety and service life, the energy storage system must limit its charge and discharge power, capacity, and state of charge.

[0076] The charging and discharging power limits during the operation of the energy storage system are as follows:

[0077]

[0078] q min , Q max These are the upper and lower limits of energy storage charging and discharging power, respectively. They are limited by the physical properties of the energy storage battery. The same applies to the minimum and maximum energy storage capacity, energy storage charging and discharging efficiency, and upper and lower limits of state of charge that will be introduced below.

[0079] The capacity limitations during energy storage operation are as follows:

[0080] C min ≤C t ≤C max ,

[0081] C min 、C max are the minimum and maximum energy storage capacities, C t is the capacity at time t, C t The calculation formula is:

[0082]

[0083] Among them, η ch ,η disch are the energy storage charging and discharging efficiency, respectively.

[0084] To prevent overcharging or overdischarging of energy storage batteries, their state of charge must be limited. The state of charge limits during energy storage operation are as follows:

[0085] SOC min ≤SOC t ≤SOC max ,

[0086] SOC max , SOC min They are the upper and lower limits of energy storage state of charge, SOC t is the state of charge of the energy storage at time t, and its calculation formula is as follows:

[0087]

[0088] C N Provide wind farms with energy storage rated capacity.

[0089] In summary, this specific embodiment aims to maximize the settlement revenue of the wind-storage system in the spot market, considers the over-generation revenue recovery and deviation assessment penalty of the wind-storage system in the spot electricity market, uses the charging and discharging sequence of the wind farm's supporting energy storage at each moment as the decision variable, and uses AGC power restrictions, grid connection point power restrictions, and the charging and discharging power, capacity, and state of charge of the wind farm's supporting energy storage as constraints. An optimization model for the wind farm's supporting energy storage charging and discharging strategy in the electricity spot market is constructed as follows:

[0090]

[0091]

[0092] This model can improve the peak-valley arbitrage benefits of wind farm supporting energy storage, smooth out wind power output fluctuations to reduce deviation assessment penalties, and improve the ability to absorb abandoned power in the case of power rationing caused by insufficient grid absorption capacity and unstable wind power generation, thereby increasing the total benefits of wind farms in the spot electricity market.

[0093] Regarding the solution of the charge and discharge strategy (corresponding to Figure 1 The above step S104), refer to Figure 2 Optionally, the present disclosure employs a differential evolution algorithm to achieve the solution. By employing the differential evolution algorithm, multiple iterations can be used to simulate biological evolution, fully exploring possible outcomes while gradually optimizing and ultimately finding a superior solution, thus helping to ensure the reliability of the solution.

[0094] Next, combine Figure 4 The solution process of the charge and discharge strategy is described in detail.

[0095] Figure 4 FIG. 4 is a flow chart illustrating steps for solving a charge and discharge strategy according to an embodiment of the present disclosure.

[0096] Reference Figure 4 ,In step S401, in each iteration cycle, multiple initial individuals are obtained.

[0097] Each initial individual corresponds to a charge-discharge sequence of an initial charge-discharge strategy, serving as the starting value for the iterative calculation. The charge-discharge sequence includes the charge and discharge amounts at specific moments. Multiple initial individuals form a population, which can be considered a biological population. The goal of the iterative calculation is to evolve the population toward the optimal direction.

[0098] It should be understood that the initial individual of the first iteration cycle can be randomly generated. For subsequent iteration cycles, as will be explained in step S405 below, the subsequent iteration cycle can use the result of the previous iteration cycle as the initial individual.

[0099] In step S402, mutation processing is performed on the multiple initial individuals to obtain multiple mutated individuals corresponding to the multiple initial individuals.

[0100] Mutation processing is to make certain changes to the initial individual, thereby simulating gene mutations in biological evolution.

[0101] Regarding the mutation process, optionally, step S402 includes: randomly dividing multiple initial individuals into multiple initial individual pairs, wherein each initial individual pair consists of two initial individuals; for each initial individual pair, recording the initial individual with a high objective function value as a winning individual, and recording the initial individual with a low objective function value as a losing individual; performing different mutation processes on the winning individuals and the losing individuals, respectively, to obtain multiple mutant individuals corresponding to the multiple initial individuals. By adopting a competitive mechanism, the initial individuals can be preliminarily divided, and then different strategies can be adopted for mutation processing, which can improve the mutation efficiency, help reduce the number of iterations or improve the quality of the final optimization result, thereby improving the efficiency of iterative calculation. In addition, with respect to the competitive mechanism, by randomly pairing each initial individual into twos to construct competitors (i.e., initial individual pairs), compared with directly assigning the half of the initial individuals with the highest objective function value as winning individuals and the half of the initial individuals with the lowest objective function value as losing individuals, it can enable richer interactions between the initial individuals, which helps to improve population diversity. As an example, in actual implementation, two initial individuals can be randomly selected directly from multiple initial individuals to form an initial individual pair. Alternatively, multiple initial individuals can be randomly divided into two groups, and then the initial individuals in the two groups are randomly paired. This disclosure does not impose any restrictions on this. It should be noted that the initial individual pairs must be re-determined and competed in each iterative cycle.

[0102] For winning individuals, different mutation processes can optionally be performed on winning individuals and losing individuals to obtain multiple mutant individuals corresponding to multiple initial individuals. The operations include: randomly selecting three different winning individuals, using one of the winning individuals as the winning baseline vector, and determining a winning difference vector based on the other two winning individuals; and determining a winning mutation vector based on the winning baseline vector and the winning difference vector to obtain a mutant individual. By constructing the winning mutation vector using three different mutually exclusive random winning individuals, the diversity within the entire group of winning individuals can be effectively increased, while simultaneously aligning the population as closely as possible to the true optimal position. As an example, when determining the winning mutation vector, a mutation scaling factor can be introduced. The winning difference vector is multiplied by the mutation scaling factor, and the sum of the resulting product and the winning baseline vector is the winning mutation vector.

[0103] For failed individuals, optionally, different mutation processes are performed on winning individuals and failed individuals to obtain multiple mutant individuals corresponding to multiple initial individuals. The process includes: using a failed individual as a failure baseline vector; determining a first failure differential vector based on the failed individual and the winning individual that forms an initial individual pair with it; randomly selecting a winning individual and a failed individual, and determining a second failure differential vector based on the randomly selected winning individual and the failed individual; and determining a failure mutation vector based on the failure baseline vector, the first failure differential vector, and the second failure differential vector to obtain a mutant individual. By using the current failed individual as a baseline and constructing the first failure differential vector using the winning individual that competed with it to win, the evolutionary direction of the current failed individual can be guided by winning individuals that are superior to the current failed individual. Simultaneously, the second failure differential vector is constructed using a randomly selected winning individual and a failed individual, introducing a richer range of individual differences. These two processes work together to guide the evolutionary direction of the current failed individual, maintaining population diversity while improving population convergence and enhancing the efficiency of iterative computation. As an example, when determining the failure mutation vector, the aforementioned additional mutation scaling factor can also be introduced. The mutation scaling factor is multiplied by the first and second failure differential vectors, respectively. The sum of the two products and the failure baseline vector is the failure mutation vector. The same mutation scaling factor can be used for the mutation processing of winning and losing individuals to maintain a consistent mutation rhythm, or different mutation scaling factors can be used, which is not limited in this disclosure.

[0104] Optionally, the mutation scaling factor used in the mutation process decreases nonlinearly with increasing iteration cycles. By allowing the mutation scaling factor to decrease nonlinearly with the progress of iterations, a larger mutation scaling factor can be used in the early stages of the iteration to expand the search range and improve global search capabilities, while a smaller mutation scaling factor can be used in the later stages of the iteration to improve local search capabilities and convergence performance. As an example, a function can be constructed with the iteration cycle as the independent variable and the mutation scaling factor as the hidden variable. The mutation scaling factor for the current iteration cycle is determined by solving this function in each iteration cycle. The specific form of the function is not limited by this disclosure.

[0105] In addition, whether for winning individuals or losing individuals, optionally, different mutation processes are performed on winning individuals and losing individuals respectively to obtain multiple mutant individuals corresponding to multiple initial individuals. The operation includes: when the current iteration cycle is in the first mutation stage, different preset mutation processes are performed on winning individuals and losing individuals respectively to obtain multiple mutant individuals corresponding to multiple initial individuals; when the current iteration cycle is in the second mutation stage, different preset mutation processes are performed on winning individuals and losing individuals respectively, and perturbation mutation individuals are added according to preset probabilities to obtain multiple mutant individuals corresponding to multiple initial individuals, wherein the first mutation stage is earlier than the second mutation stage. By dividing the entire iterative calculation process into two mutation stages, a specific preset mutation process can be performed in the early stage (i.e., the first mutation stage) when the internal differences of the population are more obvious, and perturbation is added in the later stage (i.e., the second mutation stage) when the iteration results are tightened and the internal differences of the population are reduced, which can reduce the risk of the population falling into localization and help improve the population convergence ability and local search ability. It should be understood that the preset mutation process here can adopt the mutation process for winning individuals and losing individuals described above, or it can be other mutation processes, and the present disclosure is not limited to this. In actual implementation, perturbed variant individuals are added according to a preset probability. A uniformly distributed random number can be first determined within the interval [0, 1]. If the random number is less than or equal to the preset probability, the perturbed variant individual is used as the variant individual. If the random number is greater than the preset probability, the preset mutation process is used to obtain the variant individual. Specifically, the preset mutation process can be completed uniformly to obtain multiple corresponding variant individuals. Then, according to the preset probability, the perturbed variant individuals are used to replace some of the previously obtained variant individuals to achieve computational consistency. Alternatively, the preset mutation process can be performed only for each winning or losing individual when the random number is greater than the preset probability to reduce the amount of computation, and this disclosure does not impose any restrictions on this.

[0106] As an example, a perturbed variant individual is obtained by the following steps: for each charge and discharge quantity in the current initial individual, a reference Levy distribution is obtained, with the charge and discharge quantity as the center position of a preset Levy distribution; a data set that obeys the reference Levy distribution is determined as the perturbed variant charge and discharge quantity corresponding to the charge and discharge quantity, thereby obtaining a perturbed variant individual, wherein the perturbed variant individual includes the perturbed variant charge and discharge quantity corresponding to each charge and discharge quantity in the current initial individual. By determining the corresponding perturbed variant charge and discharge quantity for each charge and discharge quantity in the current initial individual as the center position of the preset Levy distribution, and then obtaining the perturbed variant individual, targeted perturbations can be achieved for each charge and discharge quantity within the initial individual. In addition, testing has shown that using the Levy distribution to implement perturbations can improve the quality of the final calculation results. It should be noted that the Levy distribution is a distribution form, and the specific distribution shape is affected by the shape parameter α. The preset Levy distribution is the Levy distribution obtained when the shape parameter α takes a preset value.

[0107] In step S403, crossover processing is performed on each initial individual and the corresponding variant individual to obtain a crossover individual.

[0108] Crossover processing is to instruct a part of the charge and discharge amounts in the initial individual to maintain the initial value (that is, the charge and discharge amounts in the initial individual), and change the other part of the charge and discharge amounts to the mutation value (that is, the charge and discharge amounts in the corresponding mutation individual), so that the mutation only occurs in a part of the data in the initial individual, which is more in line with the evolutionary method of organisms.

[0109] Regarding the crossover process, optionally, step S403 includes: when the current iteration cycle is in the first crossover stage, using the first crossover rate to perform a crossover process on each initial individual and the corresponding variant individual to obtain a crossover individual, wherein the first crossover rate decreases as the iteration cycle increases; when the current iteration cycle is in the second crossover stage, using the second crossover rate to perform a crossover process on each initial individual and the corresponding variant individual to obtain a crossover individual, wherein the second crossover rate is positively correlated with the descending ranking of the objective function value of the initial individual among multiple initial individuals, and the first crossover stage is earlier than the second crossover stage. By adopting a decreasing strategy (specifically, a nonlinear decreasing strategy) to dynamically change the first crossover rate, a larger first crossover rate can be first adopted in the early stage of evolution (i.e., the first crossover stage) to enhance the global search capability, and a smaller first crossover rate can be gradually adopted as the number of iterations increases to enhance the local search capability. In addition, if a smaller crossover rate is always adopted in the later stage of evolution, a local optimum may be resulted. In view of this, by further dividing the late evolutionary stage (i.e., the second crossover stage), the size of the second crossover rate is dynamically changed according to the objective function value of the individual, so that the poorer individuals with smaller objective function values ​​obtain a larger second crossover rate, thereby enhancing the global search capability, and the better individuals with larger objective function values ​​obtain a smaller second crossover rate, thereby enhancing the local search capability, which helps to optimize the crossover effect. It should be understood that when a two-stage strategy is adopted for both the crossover process and the mutation process, the division of the first crossover stage and the second crossover stage can be the same as or different from the division of the first mutation stage and the second mutation stage, and the present disclosure does not limit this. In other words, the crossover process and the mutation process do not interfere with each other. In a certain iterative cycle, from the perspective of the mutation process, if it is in the first mutation stage, then from the perspective of the crossover process, it may be in the first crossover stage or the second crossover stage; the same applies to the second mutation stage. As an example, although when using the crossover rate for crossover processing, theoretically there is a corresponding probability that the crossover individual adopts the mutant individual, in actual execution, there may be a situation where the crossover rate is low and all the crossover individuals are initial individuals. To this end, certain conditions can be set so that at least one crossover individual adopts the mutant individual to ensure the effectiveness of this iteration.

[0110] In step S404, according to the objective function value of each initial individual and the objective function value of the crossover individual corresponding to the initial individual, one of the initial individuals and the corresponding crossover individual is determined as an iterative individual.

[0111] By using the objective function value as the criterion for screening the initial individuals and the corresponding crossover individuals, the principle of survival of the fittest in evolution can be met to complete the iteration of the current cycle.

[0112] In step S405, the iterative individual is used as the initial individual of the next iterative cycle until the preset end condition is met, one is determined from multiple iterative individuals, and the candidate charge and discharge strategy corresponding to the determined iterative individual is used as the solved charge and discharge strategy.

[0113] The multiple individuals obtained after the iterations are considered the optimal population, and one of them is selected to obtain the final solution. As an example, the objective function value can still be used as the criterion, and the individual with the largest objective function value can be selected.

[0114] Next, we will introduce the process of solving the charge and discharge strategy through a specific example. The process includes the following steps:

[0115] (1) Population initialization:

[0116]

[0117] The subscript i=1,2,…,N p , N p Set N as the number of initial individuals in the population p =50. The subscript D is the charge and discharge sequence Q that needs to be solved t The length of the sequence is the number of charge and discharge quantities included in the sequence. The superscript represents the sequence number of the iteration cycle, that is, the number of iterations. Here, 0 means that no iterative calculation has been performed yet and it is the initial individual used in the first iteration cycle.

[0118] (2) Mutation processing

[0119] This specific embodiment proposes a two-stage mutation strategy, and the specific steps are as follows:

[0120] The first mutation stage. In the early stage of evolution, a competition mechanism is used to randomly divide the initial individuals into two groups, and the individuals in the two groups are randomly paired. According to the objective function value, the paired individuals are divided into competition winning subgroups (groups composed of winning individuals) and competition losing subgroups (groups composed of losing individuals). After grouping using the competition mechanism, different mutation strategies are designed according to the different characteristics of the competition winning subgroups and the competition losing subgroups. For the competition winning subgroup, a random winning individual in the competition winning subgroup is used as the winning reference vector, and two mutually exclusive random winning individuals in the competition winning subgroup are used to form a winning differential vector, thereby obtaining the winning mutation vector of the winning individual. The purpose is to enhance the population diversity of the competition winning subgroup and at the same time make the population as close to the true optimal position as possible. The specific formula is as follows:

[0121]

[0122] in, is the mutation vector of individual i in the gth generation, and are three mutually exclusive winning individuals randomly selected from the winning subgroup. r1, r2, and r3 are [1, N p,win ] are mutually exclusive random integers, N p,win is the size of the winning subgroup. δ is the set threshold. g max For the maximum number of iterations, set g max =1000.

[0123] For the competition failure subgroup, the current failure individual is used as the failure baseline vector. An individual is randomly selected from each of the competition winning subgroup and the competition failure subgroup. The two selected individuals are differentiated to construct the second failure difference vector of the competition winning subgroup and the competition failure subgroup. The difference vector is then constructed by the current failure individual and the winning individual paired with it. The competition winning subgroup and the winning individual paired with the current failure individual are used to jointly guide the evolutionary direction of the failure individuals. The goal is to improve the convergence of the population while maintaining population diversity. The specific formula is as follows:

[0124]

[0125] in, is the position vector of the current individual i, is the winning individual paired with the losing individual i, is an individual randomly selected from the competition winning subgroup, is an individual randomly selected from the competition failure subgroup.

[0126] Second mutation stage. In the late stage of evolution, based on the competition mechanism and mutation strategy of the first mutation stage, both the winning and losing sub-populations adopt the Lévy distribution mutation operator with a certain probability to increase disturbance, prevent the population from falling into localization, and improve the population's convergence ability and local search ability.

[0127] The mutation operator formula of the competition winning subgroup in the second mutation phase is as follows:

[0128]

[0129] Lévy(y|α) is the Lévy distribution function, α is the parameter that controls the shape of the Lévy distribution, α∈(0,2). rand is a random number in the interval [0,1] that follows a uniform distribution, θ win The preset probability that the winning individual in the competitive winning subgroup adopts the Lévy distribution perturbation strategy.

[0130] The mutation algorithm formula of the competition failure subgroup in the second mutation phase is as follows:

[0131]

[0132]

[0133] θ lose The preset probability of using the Lévy distribution perturbation strategy for failed individuals in the competition failure subgroup.

[0134] F in the mutation operator formula is the mutation scaling factor. This specific embodiment proposes a nonlinear decreasing scaling factor change strategy, and its calculation formula is:

[0135]

[0136] F max 、F min are the maximum and minimum values ​​of the mutation scaling factor, for example, 0.9 and 0.5, respectively. γ is the nonlinear decay rate. In the early stages of the iteration, a larger scaling factor results in a wider search range and stronger global search capabilities. In the later stages of the iteration, a smaller scaling factor improves local search capabilities and convergence performance.

[0137] (3) Crossover operation

[0138] Through the variation of individual and the initial individual Cross to form new cross individuals Its expression is as follows:

[0139]

[0140] is the value after the crossover operation of the dth dimension (i.e., the dth charge and discharge amount) of individual i in the gth generation. rand is [1,N p ], ensuring that at least one dimension adopts the mutated value. C is the crossover rate. This specific embodiment proposes a hybrid adaptive crossover rate dynamic change strategy, which is calculated as follows:

[0141]

[0142] C o with C f are the initial and final values ​​of the crossover rate C in the early stage of evolution, for example, 0.7 and 0.3 respectively. max 、C min The maximum and minimum crossover rates in the late evolutionary stage are 0.5 and 0.2, respectively. ξ is the number of the current individual ranked by the objective function value among all individuals. u is the set threshold.

[0143] Using a nonlinear decreasing strategy to dynamically adjust the crossover rate allows for a higher crossover rate in the early stages of evolution to enhance global search capabilities, followed by a gradual reduction in the crossover rate over time to enhance local search capabilities. However, maintaining a lower crossover rate in the later stages of evolution may lead to a local optimum. Therefore, in the later stages of evolution, the crossover rate is dynamically adjusted based on the objective function values ​​of the individuals. This allows poorer individuals with lower objective function values ​​to achieve higher crossover rates, enhancing global search capabilities, while better individuals with higher objective function values ​​to achieve lower crossover rates, enhancing local search capabilities.

[0144] (4) Select an operation:

[0145]

[0146] f(·) is the objective function of the optimization model for the wind farm supporting energy storage charging and discharging strategy in the electricity spot market, are the crossover individuals and initial individuals of the g-th generation respectively, and the individual with the larger objective function value is selected as the initial individual of the next generation.

[0147] At the end of each iteration, it is necessary to determine whether the preset end condition is met. If it is met, stop; if not, continue the cycle of mutation, crossover, and selection.

[0148] This specific embodiment improves the global and local search capabilities of the population through a competition mechanism, a two-stage mutation strategy, a nonlinear decreasing scaling factor change strategy, and a hybrid adaptive crossover rate dynamic change strategy, accelerates convergence, and solves the optimal charging and discharging strategy for wind farm supporting energy storage in the electricity spot market.

[0149] Figure 5 1 is a block diagram illustrating a charge and discharge control device for a wind farm energy storage system according to an embodiment of the present disclosure.

[0150] Reference Figure 5 The charge and discharge control device 500 of the wind farm energy storage system includes a first acquisition unit 501 , a second acquisition unit 502 , a model building unit 503 , a strategy solving unit 504 , and a strategy sending unit 505 .

[0151] The first acquiring unit 501 may acquire wind farm operation information and energy storage information of the wind farm from the safe access area.

[0152] The second acquiring unit 502 may acquire power transaction information from the power transaction system.

[0153] The model building unit 503 may build a charging and discharging strategy optimization model based on wind farm operation information, energy storage information, and power transaction information.

[0154] The strategy solving unit 504 can solve the charging and discharging strategy optimization model to obtain the charging and discharging strategy.

[0155] The strategy sending unit 505 can send the charge and discharge strategy to the safe access zone in a target data format so that the safe access zone can forward the charge and discharge strategy to the control system. The target data format includes a specified data format of a reverse isolation device in the safe access zone.

[0156] Optionally, the secure access area includes a first gateway, a reverse isolation device, and a second gateway connected in sequence. The first gateway is communicated with a third-party control platform, and the second gateway is communicated with the control system. The strategy sending unit 505 can also send the charge and discharge strategy and format conversion instructions to the first gateway, so that the first gateway can convert the charge and discharge strategy into a specified data format according to the format conversion instruction and send it to the second gateway via the reverse isolation device, so that the second gateway can restore the original data format of the charge and discharge strategy and send it to the control system.

[0157] Optionally, the first acquisition unit 501 can also send an information acquisition request to the security access zone in a target data format, so that the security access zone forwards the information acquisition request to the control system to request the control system to return the wind farm operation information and energy storage information within the future target period at the time required by the information acquisition request.

[0158] Optionally, the third-party control platform and the control system synchronously store at least one control scenario information, each control scenario information corresponds to a different charging and discharging control scenario, and each control scenario information includes an information acquisition time. The first acquisition unit 501 can also send an information acquisition request for the target control scenario to the secure access area in a target data format, so that the secure access area can forward the information acquisition request for the target control scenario to the control system to request the control system to query the information acquisition time corresponding to the target control scenario, and within the future target time period, return the wind farm operation information and energy storage information according to the queried information acquisition time.

[0159] Optionally, the model building unit 503 can also use the charge and discharge amount in the target period as an independent variable based on the wind farm operation information, energy storage information and power trading information, construct an objective function with the goal of maximizing the transaction data revenue, and construct energy storage constraints to obtain a charge and discharge strategy optimization model including the objective function and energy storage constraints, wherein the charge and discharge strategy obtained by solving the charge and discharge strategy optimization model includes a charge and discharge sequence, and the charge and discharge sequence includes the charge and discharge amounts at multiple moments in the target period.

[0160] Optionally, the strategy solving unit 504 may also: obtain multiple initial individuals in each iteration cycle, wherein each initial individual corresponds to a charge and discharge sequence of an initial charge and discharge strategy; perform mutation processing on the multiple initial individuals to obtain multiple variant individuals corresponding to the multiple initial individuals; perform crossover processing on each initial individual and the corresponding variant individual to obtain a crossover individual; determine one from the initial individual and the corresponding crossover individual as the iterative individual based on the objective function value of each initial individual and the objective function value of the crossover individual corresponding to the initial individual; use the iterative individual as the initial individual of the next iteration cycle until the preset end condition is met, determine one from the multiple iterative individuals, and use the candidate charge and discharge strategy corresponding to the determined iterative individual as the solved charge and discharge strategy.

[0161] Optionally, the strategy solving unit 504 can also: randomly divide the multiple initial individuals into multiple initial individual pairs, wherein each initial individual pair consists of two initial individuals; for each initial individual pair, the initial individual with a higher objective function value is recorded as a winning individual, and the initial individual with a lower objective function value is recorded as a losing individual; and perform different mutation processing on the winning individuals and the losing individuals, respectively, to obtain multiple mutant individuals corresponding to the multiple initial individuals.

[0162] Optionally, the strategy solving unit 504 may also: randomly select three different winning individuals, use one of the winning individuals as the winning reference vector, and determine a winning difference vector based on the other two winning individuals; determine a winning mutation vector based on the winning reference vector and the winning difference vector to obtain a mutation individual.

[0163] Optionally, the strategy solving unit 504 may also: take a failed individual as a failure baseline vector; determine a first failure differential vector based on the failed individual and the winning individual that forms an initial individual pair with it; randomly select a winning individual and a losing individual, and determine a second failure differential vector based on the randomly selected winning individual and losing individual; determine a failure mutation vector based on the failure baseline vector, the first failure differential vector, and the second failure differential vector to obtain a mutation individual.

[0164] Optionally, the strategy solving unit 504 may also: when the current iteration cycle is in the first mutation stage, perform different preset mutation processing on the winning individuals and the losing individuals, respectively, to obtain multiple mutant individuals corresponding to the multiple initial individuals; when the current iteration cycle is in the second mutation stage, perform different preset mutation processing on the winning individuals and the losing individuals, respectively, and add disturbance mutation individuals according to preset probabilities, respectively, to obtain multiple mutant individuals corresponding to the multiple initial individuals, wherein the first mutation stage is earlier than the second mutation stage.

[0165] Optionally, the perturbation variation individual is obtained by the following steps: for each charge and discharge amount in the current initial individual, a reference Levy distribution is obtained with the charge and discharge amount as the center position of a preset Levy distribution; a data that obeys the reference Levy distribution is determined as the perturbation variation charge and discharge amount corresponding to the charge and discharge amount, to obtain the perturbation variation individual, wherein the perturbation variation individual includes the perturbation variation charge and discharge amount corresponding to each charge and discharge amount in the current initial individual.

[0166] Optionally, the mutation scaling factor used in the mutation process decreases nonlinearly with increasing iteration period.

[0167] Optionally, the strategy solving unit 504 may also: when the current iteration cycle is in the first crossover stage, use a first crossover rate to perform crossover processing on each initial individual and the corresponding variant individual to obtain a crossover individual, wherein the first crossover rate decreases with increasing iteration cycles; when the current iteration cycle is in the second crossover stage, use a second crossover rate to perform crossover processing on each initial individual and the corresponding variant individual to obtain a crossover individual, wherein the second crossover rate is positively correlated with the descending ranking of the objective function value of the initial individual among multiple initial individuals, and the first crossover stage is earlier than the second crossover stage.

[0168] Regarding the apparatus in the above embodiment, the specific manner in which each unit performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here.

[0169] The charge and discharge control method of the wind farm energy storage system according to the embodiment of the present disclosure can be written as a computer program and stored on a computer-readable storage medium. When the instructions corresponding to the computer program are executed by the processor, the charge and discharge control method of the wind farm energy storage system as described above can be implemented. Examples of computer-readable storage media include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R LTH, BD-RE, Blu-ray or optical disk storage, hard disk drive (HDD), solid state drive (SSD), card storage (such as, multimedia card, secure digital (SD) card or ultra fast digital (XD) card), magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk and any other device, any other device configured to store the computer program and any associated data, data files and data structures in a non-transitory manner and provide the computer program and any associated data, data files and data structures to a processor or computer so that the processor or computer can execute the computer program. In one example, the computer program and any associated data, data files and data structures are distributed on a networked computer system so that the computer program and any associated data, data files and data structures are stored, accessed and executed in a distributed manner by one or more processors or computers.

[0170] Figure 6 is a block diagram illustrating a computer device according to an embodiment of the present disclosure.

[0171] Reference Figure 6 The computer device 600 includes at least one memory 601 and at least one processor 602. The at least one memory 601 stores a set of computer-executable instructions. When the computer-executable instruction set is executed by the at least one processor 602, the charging and discharging control method of the wind farm energy storage system as described above is executed.

[0172] As an example, the computer device 600 may be a PC, a tablet device, a personal digital assistant, a smart phone, or other device capable of executing the above-mentioned instruction set. Here, the computer device 600 is not necessarily a single electronic device, but may also be any device or circuit collection capable of executing the above-mentioned instructions (or instruction set) individually or in combination. The computer device 600 may also be part of an integrated control system or system manager, or may be configured as a portable electronic device interconnected with a local or remote (e.g., via wireless transmission) interface.

[0173] In computer device 600, processor 602 may include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a dedicated processor system, a microcontroller, or a microprocessor. By way of example and not limitation, the processor may also include an analog processor, a digital processor, a microprocessor, a multi-core processor, a processor array, a network processor, etc.

[0174] The processor 602 can execute instructions or codes stored in the memory 601, wherein the memory 601 can also store data. Instructions and data can also be sent and received over the network via the network interface device, wherein the network interface device can use any known transmission protocol.

[0175] The memory 601 may be integrated with the processor 602, for example, by placing RAM or flash memory within an integrated circuit microprocessor or the like. Furthermore, the memory 601 may comprise a separate device, such as an external disk drive, a storage array, or any other storage device usable by a database system. The memory 601 and the processor 602 may be operatively coupled or may communicate with each other, for example, via an I / O port, a network connection, or the like, such that the processor 602 can access files stored in the memory.

[0176] In addition, the computer device 600 may also include a video display (such as a liquid crystal display) and a user interaction interface (such as a keyboard, a mouse, a touch input device, etc.) All components of the computer device 600 may be connected to each other via a bus and / or a network.

[0177] The computer program product according to an embodiment of the present disclosure includes computer instructions. When the computer instructions are executed by at least one processor, the at least one processor is prompted to execute the above-mentioned method for controlling the charging and discharging of the wind farm energy storage system.

[0178] The present disclosure provides a charge and discharge control method, storage medium, and program product for a wind farm energy storage system. By establishing a charge and discharge control method for a wind farm energy storage system executed by a third-party control platform, it is possible to combine information from multiple sources to establish and solve a charge and discharge strategy optimization model with higher computational accuracy, thereby meeting the actual operational needs of supporting energy storage in wind farms. Furthermore, the solved charge and discharge strategy is distributed to the wind farm's control system via the wind farm's secure access zone, eliminating the need to configure additional computing hardware for the wind farm to build and solve the model. This allows for charge and discharge strategy optimization with low investment, effectively improving wind energy utilization efficiency.

[0179] The specific implementation methods of the present disclosure have been described in detail above. Although some embodiments have been shown and described, those skilled in the art should understand that these embodiments may be modified and varied without departing from the principles and spirit of the present disclosure, the scope of which is defined by the claims and their equivalents. These modifications and variations should also be within the scope of protection of the claims of the present disclosure.

Claims

1. A method for controlling charging and discharging of a wind farm energy storage system, characterized in that: The charge and discharge control method is used for a third-party control platform, the third-party control platform is connected to the safe access area of ​​the wind farm via a communication line, and the safe access area is connected to the control system of the wind farm. The charge and discharge control method includes: acquiring wind farm operation information and energy storage information of the wind farm from the secure access area; Obtain power transaction information from the power transaction system; Constructing a charging and discharging strategy optimization model based on the wind farm operation information, the energy storage information, and the power transaction information; Solving the charging and discharging strategy optimization model to obtain the charging and discharging strategy; The charge and discharge strategy is sent to the safe access zone in a target data format, so that the safe access zone forwards the charge and discharge strategy to the control system. The target data format includes a specified data format of a reverse isolation device of the safe access zone.

2. The charge and discharge control method for the wind farm energy storage system according to claim 1, characterized in that: The secure access zone includes a first gateway, a reverse isolation device, and a second gateway connected in sequence, the first gateway being communicatively connected to the third-party control platform, and the second gateway being communicatively connected to the control system, wherein sending the charge and discharge strategy in a target data format to the secure access zone includes: The charge and discharge strategy and format conversion instruction are sent to the first gateway, so that the first gateway converts the charge and discharge strategy into the specified data format according to the format conversion instruction and sends it to the second gateway via the reverse isolation device, so that the second gateway can restore the original data format of the charge and discharge strategy and send it to the control system.

3. The charge and discharge control method for a wind farm energy storage system according to claim 1, wherein: The obtaining of wind farm operation information and energy storage information of the wind farm from the secure access area includes: An information acquisition request is sent to the secure access zone in the target data format, so that the secure access zone forwards the information acquisition request to the control system, requesting the control system to return the wind farm operation information and the energy storage information within a future target period at the time required by the information acquisition request.

4. The charge and discharge control method for the wind farm energy storage system according to claim 3, characterized in that: The third-party control platform and the control system synchronously store at least one control scenario information, each control scenario information corresponds to a different charge and discharge control scenario, and each control scenario information includes an information acquisition time, wherein the information acquisition request is sent to the secure access zone in the target data format, so that the secure access zone forwards the information acquisition request to the control system to request the control system to return the wind farm operation information and the energy storage information within a future target period at the time required by the information acquisition request, including: An information acquisition request for the target control scenario is sent to the secure access zone in the target data format, so that the secure access zone forwards the information acquisition request for the target control scenario to the control system, so as to request the control system to query the information acquisition time corresponding to the target control scenario, and to return the wind farm operation information and the energy storage information according to the queried information acquisition time within a future target time period.

5. The charge and discharge control method for a wind farm energy storage system according to any one of claims 1 to 4, characterized in that: The constructing of a charge-discharge strategy optimization model based on the wind farm operation information, the energy storage information, and the power transaction information includes: Based on the wind farm operation information, the energy storage information, and the power transaction information, the charge and discharge amount in the target period is used as an independent variable, an objective function is constructed with the goal of maximizing the transaction data benefit, and energy storage constraints are constructed to obtain the charge and discharge strategy optimization model including the objective function and the energy storage constraints. The charging and discharging strategy obtained by solving the charging and discharging strategy optimization model includes a charging and discharging sequence, and the charging and discharging sequence includes charging and discharging amounts at multiple moments within the target time period.

6. The charge and discharge control method for the wind farm energy storage system according to claim 5, characterized in that: Solving the charge-discharge strategy optimization model to obtain the charge-discharge strategy includes: In each iteration cycle, a plurality of initial individuals are obtained, wherein each initial individual corresponds to a charge-discharge sequence of an initial charge-discharge strategy; Performing mutation processing on the multiple initial individuals to obtain multiple mutated individuals corresponding to the multiple initial individuals; Perform crossover processing on each initial individual and the corresponding mutant individual to obtain a crossover individual; According to the objective function value of each initial individual and the objective function value of the crossover individual corresponding to the initial individual, one of the initial individuals and the corresponding crossover individual is determined as an iterative individual; The iterative individual is used as the initial individual of the next iterative cycle until a preset end condition is met, one is determined from the multiple iterative individuals, and the candidate charge and discharge strategy corresponding to the determined iterative individual is used as the charge and discharge strategy to be solved.

7. The charge and discharge control method for the wind farm energy storage system according to claim 6, characterized in that: The performing mutation processing on the multiple initial individuals to obtain multiple mutated individuals corresponding to the multiple initial individuals includes: Randomly dividing the multiple initial individuals into multiple initial individual pairs, wherein each initial individual pair consists of two initial individuals; For each pair of initial individuals, the initial individual with a higher objective function value is recorded as the winning individual, and the initial individual with a lower objective function value is recorded as the losing individual; Different mutation processes are performed on the winning individuals and the losing individuals to obtain the multiple mutant individuals corresponding to the multiple initial individuals.

8. The charge and discharge control method for the wind farm energy storage system according to claim 7, characterized in that: The performing different mutation processing on the winning individuals and the losing individuals respectively to obtain the multiple mutant individuals corresponding to the multiple initial individuals includes: Randomly select three different winning individuals, use one of them as the winning baseline vector, and determine the winning difference vector based on the other two winning individuals; According to the victory reference vector and the victory difference vector, a victory mutation vector is determined to obtain a mutation individual.

9. The charge and discharge control method for the wind farm energy storage system according to claim 7, characterized in that: The performing different mutation processing on the winning individuals and the losing individuals respectively to obtain the multiple mutant individuals corresponding to the multiple initial individuals includes: Take a failed individual as the failure benchmark vector; Determining a first failure difference vector according to the failed individual and the winning individual forming an initial individual pair with the failed individual; Randomly select a winning individual and a losing individual, and determine a second failure difference vector based on the randomly selected winning individual and losing individual; A failure mutation vector is determined according to the failure reference vector, the first failure differential vector, and the second failure differential vector to obtain a mutation individual.

10. The charge and discharge control method for the wind farm energy storage system according to claim 7, characterized in that: The performing different mutation processing on the winning individuals and the losing individuals respectively to obtain the multiple mutant individuals corresponding to the multiple initial individuals includes: When the current iteration cycle is in the first mutation stage, performing different preset mutation processes on the winning individuals and the losing individuals, respectively, to obtain the multiple mutant individuals corresponding to the multiple initial individuals; When the current iteration cycle is in the second mutation stage, different preset mutation processing is performed on the winning individuals and the losing individuals, and perturbed mutation individuals are added according to preset probabilities to obtain the multiple mutation individuals corresponding to the multiple initial individuals, wherein the first mutation stage is earlier than the second mutation stage.

11. The charge and discharge control method for a wind farm energy storage system according to claim 10, wherein: The perturbed variant individual is obtained by the following steps: For each charge and discharge amount in the current initial individual, a reference Levy distribution is obtained with the charge and discharge amount as the center position of a preset Levy distribution; Determine a data that obeys the reference Levy distribution as the disturbance variation charge and discharge amount corresponding to the charge and discharge amount, and obtain the disturbance variation individual, wherein the disturbance variation individual includes the disturbance variation charge and discharge amount corresponding to each charge and discharge amount in the current initial individual.

12. The charge and discharge control method for a wind farm energy storage system according to claim 7, wherein: The mutation scaling factor used in the mutation process decreases nonlinearly with the increase of the iteration period.

13. The charge and discharge control method for a wind farm energy storage system according to claim 7, wherein: The crossover process is performed on each initial individual and the corresponding variant individual to obtain a crossover individual, including: When the current iteration cycle is in the first crossover stage, a first crossover rate is used to perform a crossover process on each initial individual and the corresponding mutant individual to obtain the crossover individual, wherein the first crossover rate decreases as the iteration cycle increases; When the current iteration cycle is in the second crossover stage, each initial individual and the corresponding mutant individual are crossover-processed using a second crossover rate to obtain the crossover individual, wherein the second crossover rate is positively correlated with the descending ranking of the objective function value of the initial individual among the multiple initial individuals, and the first crossover stage is earlier than the second crossover stage.

14. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor is prompted to execute the charge and discharge control method for a wind farm energy storage system according to any one of claims 1 to 13.

15. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by at least one processor, the at least one processor is prompted to execute the charge and discharge control method for a wind farm energy storage system according to any one of claims 1 to 13.

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