Energy storage coordination control system

Abstract

The invention discloses an energy storage coordination control system, and the system comprises an extraction module which is used for analyzing a historical operation log of the energy storage coordination control system, and extracting control parameters of an energy storage converter at different historical time nodes and operation state parameters of a power grid corresponding to the historical time nodes; the analysis module is used for calculating a state conversion coefficient, determining related operation state parameters according to the state conversion coefficient, analyzing the related operation state parameters and the control parameters, determining characteristic control parameters and generating a characteristic parameter group; the construction module is used for determining an optimal control parameter set and constructing an optimal energy storage coordination control model; and the control module is used for determining optimal control parameters of the real-time related operation state parameters based on the optimal energy storage coordination control model, generating a control strategy according to the optimal control parameters, reducing data analysis quantity and processing quantity, generating optimal control strategies under different control instructions, and realizing an advanced control function of the energy storage coordination control system.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage coordinated control, and in particular to an energy storage coordinated control system. Background Art

[0002] The energy storage coordination controller connects the battery system to the power grid and detects the voltage, frequency and power of the network points. It can receive control instructions from the dispatching and electrochemical energy storage power station monitoring system, control multiple energy storage devices, and realize control functions such as frequency regulation and dynamic reactive voltage regulation of the entire station.

[0003] In the prior art, the energy storage coordinated control system receives the adjustment instructions issued and performs adjustments according to common control strategies or human experience. In addition, a large amount of data and analysis is involved, and it is impossible to make an effective optimization control strategy, thereby reducing the control effect of the energy storage coordinated control system. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides an energy storage coordinated control system, which screens the relevant operating status parameters of each preset control instruction, determines the characteristic parameter group of each preset control instruction according to the relationship between the relevant operating status parameters and the control parameters, calculates the application evaluation values ​​of multiple control parameters in the same characteristic parameter group, screens out the preferred control parameter set according to the application evaluation values, and constructs a preferred energy storage coordinated control model, thereby reducing the amount of data analysis and processing, improving the control timeliness of the energy storage coordinated control model, and generating optimized control strategies under different control instructions to realize the advanced control functions of the energy storage coordinated control system.

[0005] In some embodiments of the present application, a coordinated energy storage control system is provided, comprising:

[0006] An extraction module is used to analyze the historical operation log of the energy storage coordinated control system, extract the control parameters of the energy storage converter at different historical time nodes, and the operation status parameters of the power grid at the corresponding historical time nodes;

[0007] An analysis module, used to calculate a state conversion coefficient of an operating state parameter, determine relevant operating state parameters of a preset control instruction according to the state conversion coefficient, analyze relevant operating state parameters and control parameters, determine characteristic control parameters, and generate a characteristic parameter group for each preset control instruction;

[0008] A construction module is used to analyze the characteristic parameter group of the same preset control instruction, determine the preferred control parameter set of each preset control instruction according to the analysis result, and construct the preferred energy storage coordinated control model according to the preferred control parameter set;

[0009] The control module is used to obtain real-time related operating status parameters, determine the preferred control parameters of the real-time related operating status parameters based on the preferred energy storage coordinated control model, and generate a control strategy according to the preferred control parameters.

[0010] In some embodiments of the present application, determining the relevant operating state parameters of the preset control instruction according to the state transition coefficient includes:

[0011] Analyze multiple preset control instructions, determine the control flow involved in each preset control instruction, and arrange the control flow in a control order to obtain a control flow sequence K, K (k1, k2, ..., kn) of each preset control instruction, where ki is the i-th control flow and n is the number of control flows;

[0012] Obtain the operating status parameters of adjacent historical time periods of multiple historical control time periods of the control process involved in each preset control instruction, calculate multiple state transition coefficients of each operating status parameter in adjacent historical time periods, and if multiple state transition coefficients are all greater than the preset state coefficient threshold, set the corresponding operating status parameter as the relevant operating status parameter of the corresponding control process of the preset control instruction.

[0013] In some embodiments of the present application, relevant operating state parameters and control parameters are analyzed to determine characteristic control parameters, including:

[0014] Establishing a time reference line according to multiple historical control time periods of each control process of the preset control instruction, and marking multiple acquisition time nodes on the time reference line based on the preset time interval;

[0015] For each of the multiple collection time nodes of each time reference line, relevant operating status parameters are collected respectively, and the change amount mean analysis is performed on the relevant operating status parameters on the same time reference line, and the change time nodes whose change amount mean is greater than the preset change amount mean threshold are marked, and the weight coefficient of the marked corresponding change time node is set according to the change amount mean difference whose change amount mean is greater than the preset change amount mean threshold;

[0016] Acquire multiple control parameters of the marked change time nodes of the same time reference line, and compare the multiple control parameters with the corresponding control parameters in the previous time period to obtain the change value of each control parameter at the marked change time node;

[0017] The number of marked change time nodes whose change values ​​in the same time reference line are greater than a preset change value threshold, and the difference of the change values ​​whose change values ​​are greater than the preset change value threshold, are used to generate the importance of the control parameter in the historical control time period corresponding to the time reference line;

[0018] Obtain the number of the same control parameter whose importance is greater than the importance threshold in multiple historical control time periods of each control process, and generate a quantity ratio with the total number of historical control time periods of the same control process; if the quantity ratio is greater than a preset quantity ratio threshold, set the current control parameter as the characteristic control parameter of the corresponding control process;

[0019] The characteristic control parameters of each control flow of the same preset control instruction are used to generate characteristic control parameters of the corresponding preset control instruction.

[0020] In some embodiments of the present application, generating the importance of the control parameter corresponding to the historical control time period on the time reference line includes:

[0021] The calculation formula of the importance Gi is:

[0022]

[0023] Among them, f is the number of marked change time nodes in the same time reference line whose change value is greater than the preset change value threshold, y is the total number of marked change time nodes in the same time reference line, qs is the difference in the change value of the control parameter at the marked sth change time node, and as is the weight coefficient of the marked sth change time node.

[0024] In some embodiments of the present application, a characteristic parameter group for each preset control instruction is constructed, including:

[0025] The relevant operating state parameters and corresponding characteristic control parameters of each control flow in different historical control time periods under the same preset control instruction are used to construct a characteristic parameter group corresponding to the preset control instruction.

[0026] In some embodiments of the present application, the characteristic parameter group of the same preset control instruction is analyzed, including:

[0027] Comprehensively analyze multiple characteristic parameter groups of the same control process of each preset control instruction to obtain the historical control duration of each characteristic parameter group under the control parameters of different historical control time periods, the parameter difference between the relevant operating state parameters after the historical control duration and the standard operating state parameter interval, and multiple grid frequencies after the historical control duration;

[0028] A compensation coefficient is set according to the historical control duration of multiple characteristic parameter groups of the same control process, a first evaluation value is set according to the multiple parameter differences between multiple relevant operating state parameters after the historical control duration and the standard operating state parameter interval, and a second evaluation value is set according to the fluctuation range of multiple power grid frequencies after the historical control duration;

[0029] Generate application evaluation values ​​of control parameters of different historical control time periods in the corresponding characteristic parameter group according to the first evaluation value, the second evaluation value and the compensation coefficient;

[0030] The application evaluation value is: H = h1*h2*c;

[0031] Among them, H is the application evaluation value, h1 is the first evaluation value, h2 is the second evaluation value, and c is the compensation coefficient.

[0032] In some embodiments of the present application, determining a preferred control parameter set for each preset control instruction according to the analysis result includes:

[0033] Sorting the application evaluation values ​​corresponding to the control parameters of the characteristic parameter group of the same control flow of the same preset control instruction, and setting the multiple control parameters corresponding to the first-ranked application evaluation value as the preferred control parameter subset of the corresponding control flow;

[0034] Based on the time sequence of the preset control process, the preferred control parameter subsets of the same preset control instruction are sorted, and the preferred control parameter set corresponding to the preset control instruction is generated according to the sorting result.

[0035] In some embodiments of the present application, a preferred energy storage coordinated control model is constructed according to a preferred control parameter set, including:

[0036] According to the relevant operating state parameters of each preset control instruction as input data, multiple control parameters in the preferred control parameter set of each preset control instruction are used as output data, and neural network training is performed to obtain the preferred energy storage coordinated control model.

[0037] In some embodiments of the present application, generating a control strategy according to the preferred control parameters includes:

[0038] Acquire real-time relevant operating state parameters of the energy storage coordinated control system, input the real-time relevant operating state parameters into the optimal energy storage coordinated control model, and obtain multiple optimal control parameters;

[0039] Based on the mapping relationship between the preferred control parameters and the preset control process, the preferred control parameters are sorted by control time, and a control strategy is generated according to the sorting result.

[0040] Compared with the prior art, the energy storage coordination control system of the embodiment of the present application has the following beneficial effects:

[0041] By screening the relevant operating status parameters of each preset control instruction, determining the characteristic parameter group of each preset control instruction according to the relationship between the relevant operating status parameters and the control parameters, calculating the application evaluation values ​​of multiple control parameters in the same characteristic parameter group, screening out the preferred control parameter set according to the application evaluation values, and constructing the preferred energy storage coordinated control model, the amount of data analysis and processing can be reduced, the control timeliness of the energy storage coordinated control model can be improved, and the optimized control strategies under different control instructions can be generated to realize the advanced control functions of the energy storage coordinated control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of an energy storage coordination control system in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0043] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0044] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0045] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0046] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0047] like Figure 1 As shown, a preferred embodiment of the present application embodiment is an energy storage coordination control system, comprising:

[0048] An extraction module is used to analyze the historical operation log of the energy storage coordinated control system, extract the control parameters of the energy storage converter at different historical time nodes, and the operation status parameters of the power grid at the corresponding historical time nodes;

[0049] An analysis module, used to calculate a state conversion coefficient of an operating state parameter, determine relevant operating state parameters of a preset control instruction according to the state conversion coefficient, analyze relevant operating state parameters and control parameters, determine characteristic control parameters, and generate a characteristic parameter group for each preset control instruction;

[0050] A construction module is used to analyze the characteristic parameter group of the same preset control instruction, determine the preferred control parameter set of each preset control instruction according to the analysis result, and construct the preferred energy storage coordinated control model according to the preferred control parameter set;

[0051] The control module is used to obtain real-time related operating status parameters, determine the preferred control parameters of the real-time related operating status parameters based on the preferred energy storage coordinated control model, and generate a control strategy according to the preferred control parameters.

[0052] In this embodiment, the operating status parameter refers to data that is associated with the operating status of the power grid and has a high degree of association, and the preset control instructions include instructions such as fast power response, auxiliary frequency regulation, and voltage regulation.

[0053] In this embodiment, by screening the relevant operating status parameters of each preset control instruction, according to the relationship between the relevant operating status parameters and the control parameters, the characteristic parameter group of each preset control instruction is determined, the application evaluation values ​​of multiple control parameters in the same characteristic parameter group are calculated, and the preferred control parameter set is screened according to the application evaluation values, and an optimal energy storage coordinated control model is constructed, thereby reducing the amount of data analysis and processing, improving the control timeliness of the energy storage coordinated control model, and generating optimized control strategies under different control instructions to realize the advanced control function of the energy storage coordinated control system.

[0054] In some embodiments of the present application, determining the relevant operating state parameters of the preset control instruction according to the state transition coefficient includes:

[0055] Analyze multiple preset control instructions, determine the control flow involved in each preset control instruction, and arrange the control flow in a control order to obtain a control flow sequence K, K (k1, k2, ..., kn) of each preset control instruction, where ki is the i-th control flow and n is the number of control flows;

[0056] Obtain the operating status parameters of adjacent historical time periods of multiple historical control time periods of the control process involved in each preset control instruction, calculate multiple state transition coefficients of each operating status parameter in adjacent historical time periods, and if multiple state transition coefficients are all greater than the preset state coefficient threshold, set the corresponding operating status parameter as the relevant operating status parameter of the corresponding control process of the preset control instruction.

[0057] In this embodiment, the control flow refers to multiple control processes when each preset control instruction is running, and each control process is set as a control flow. For example, when the preset control instruction is a fast power tracking response, the control flow includes receiving external power, calculating the output power of the energy storage system, controlling the output power, judging the accuracy of the output power, etc. Each preset control instruction is divided into multiple control flows, so as to accurately obtain the relevant operating status parameters of each preset control instruction, lay the foundation for the subsequent determination of the characteristic control parameters, and improve the accuracy of the characteristic control parameters.

[0058] In this embodiment, the historical control time period refers to the regulation time of each control process. The regulation time period is set according to the regulation efficiency of the corresponding control parameters. Multiple historical control time periods are different. The adjacent historical time periods of the historical control time period refer to the operating status parameters within 10 minutes before and after the historical control time period. The operating status parameters before and after the control process correspond to the operating status of the power grid and generate a state coefficient. When the operating status is normal, the state coefficient takes a value of (0.75, 1.25). When the operating status is abnormal, the state coefficient takes a value of (0, 0.5). The state conversion coefficient refers to the degree of conversion of the state coefficient of the operating status parameter before and after the control process. If the difference between the state coefficients before and after is greater than 0.15, it is set to the relevant operating status parameter of the corresponding control process.

[0059] In some embodiments of the present application, relevant operating state parameters and control parameters are analyzed to determine characteristic control parameters, including:

[0060] Establishing a time reference line according to multiple historical control time periods of each control process of the preset control instruction, and marking multiple acquisition time nodes on the time reference line based on the preset time interval;

[0061] For each of the multiple collection time nodes of each time reference line, relevant operating status parameters are collected respectively, and the change amount mean analysis is performed on the relevant operating status parameters on the same time reference line, and the change time nodes whose change amount mean is greater than the preset change amount mean threshold are marked, and the weight coefficient of the marked corresponding change time node is set according to the change amount mean difference whose change amount mean is greater than the preset change amount mean threshold;

[0062] Acquire multiple control parameters of the marked change time nodes of the same time reference line, and compare the multiple control parameters with the corresponding control parameters in the previous time period to obtain the change value of each control parameter at the marked change time node;

[0063] The number of marked change time nodes whose change values ​​in the same time reference line are greater than a preset change value threshold, and the difference of the change values ​​whose change values ​​are greater than the preset change value threshold, are used to generate the importance of the control parameter in the historical control time period corresponding to the time reference line;

[0064] Obtain the number of the same control parameter whose importance is greater than the importance threshold in multiple historical control time periods of each control process, and generate a quantity ratio with the total number of historical control time periods of the same control process; if the quantity ratio is greater than a preset quantity ratio threshold, set the current control parameter as the characteristic control parameter of the corresponding control process;

[0065] The characteristic control parameters of each control flow of the same preset control instruction are used to generate characteristic control parameters of the corresponding preset control instruction.

[0066] In this embodiment, the previous time period refers to the control parameters within 10 minutes before the first marked change time node, and the mean change refers to the average value of the change of the relevant operating status parameters of each acquisition time node in the same time reference line. According to the importance of the control parameters in the same time reference line (i.e., in the same historical control time period), the characteristic control parameters in each historical control time period are determined, laying the foundation for the subsequent construction of the characteristic parameter group, improving the subsequent energy storage coordinated control system in the face of various operating conditions, quickly formulating control strategies, improving the management efficiency of the energy storage coordinated control system, and ensuring the safe and stable operation of the power grid.

[0067] In some embodiments of the present application, generating the importance of the control parameter corresponding to the historical control time period on the time reference line includes:

[0068] The calculation formula of the importance Gi is:

[0069]

[0070] Among them, f is the number of marked change time nodes in the same time reference line whose change value is greater than the preset change value threshold, y is the total number of marked change time nodes in the same time reference line, qs is the difference in the change value of the control parameter at the marked sth change time node, and as is the weight coefficient of the marked sth change time node.

[0071] In some embodiments of the present application, a characteristic parameter group for each preset control instruction is constructed, including:

[0072] The relevant operating state parameters and corresponding characteristic control parameters of each control flow in different historical control time periods under the same preset control instruction are used to construct a characteristic parameter group corresponding to the preset control instruction.

[0073] In some embodiments of the present application, the characteristic parameter group of the same preset control instruction is analyzed, including:

[0074] Comprehensively analyze multiple characteristic parameter groups of the same control process of each preset control instruction to obtain the historical control duration of each characteristic parameter group under the control parameters of different historical control time periods, the parameter difference between the relevant operating state parameters after the historical control duration and the standard operating state parameter interval, and multiple grid frequencies after the historical control duration;

[0075] A compensation coefficient is set according to the historical control duration of multiple characteristic parameter groups of the same control process, a first evaluation value is set according to the multiple parameter differences between multiple relevant operating state parameters after the historical control duration and the standard operating state parameter interval, and a second evaluation value is set according to the fluctuation range of multiple power grid frequencies after the historical control duration;

[0076] Generate application evaluation values ​​of control parameters of different historical control time periods in the corresponding characteristic parameter group according to the first evaluation value, the second evaluation value and the compensation coefficient;

[0077] The application evaluation value is: H = h1*h2*c;

[0078] Among them, H is the application evaluation value, h1 is the first evaluation value, h2 is the second evaluation value, and c is the compensation coefficient.

[0079] In this embodiment, multiple preset compensation coefficients are set in advance, which are set in advance based on the relationship between the historical control time and the preset control time interval. When the preset control time interval in which the historical control time is located is longer, the compensation coefficient is smaller, and when the preset control time interval in which the historical control time is located is shorter, the compensation coefficient is larger. The value range of the compensation coefficient is (0.75, 1.25).

[0080] In this embodiment, multiple preset first evaluation values ​​are set in advance, which are set in advance based on the relationship between the sum of multiple parameter differences and the preset parameter difference range. When the sum of multiple parameter differences is larger, the first evaluation value is smaller, and when the sum of parameter differences is smaller, the first evaluation value is larger. The value range of the preset first evaluation value is (0, 1).

[0081] In this embodiment, multiple preset second evaluation values ​​are set in advance, which are set in advance according to the relationship between the fluctuation range of the power grid frequency and the preset fluctuation range interval. When the preset fluctuation range interval of the fluctuation range is larger, the second evaluation value is smaller, and when the preset fluctuation range interval of the fluctuation range is smaller, the second evaluation value is larger. The value range of the preset second evaluation value is (0, 1).

[0082] In this embodiment, based on the application evaluation values ​​of the control parameters in multiple characteristic parameter groups of the same control process, the preferred characteristic parameter group of each control process is screened out, laying the foundation for the subsequent construction of the preferred energy storage coordinated control model and improving the advanced control function of the energy storage coordinated control system.

[0083] In some embodiments of the present application, determining a preferred control parameter set for each preset control instruction according to the analysis result includes:

[0084] Sorting the application evaluation values ​​corresponding to the control parameters of the characteristic parameter group of the same control flow of the same preset control instruction, and setting the multiple control parameters corresponding to the first-ranked application evaluation value as the preferred control parameter subset of the corresponding control flow;

[0085] Based on the time sequence of the preset control process, the preferred control parameter subsets of the same preset control instruction are sorted, and the preferred control parameter set corresponding to the preset control instruction is generated according to the sorting result.

[0086] In this embodiment, the preferred control parameter subset is constructed based on multiple control parameters in the historical control time period corresponding to the first-ranked application evaluation value, and the preferred control parameter subsets of the same preset control instruction are sorted in chronological order of the preset control process. For example, the preferred control parameter set of the preset control instruction is (d1, d2,…, dn), where di is the preferred control parameter subset of the i-th control process ki of the current preset control instruction.

[0087] In some embodiments of the present application, a preferred energy storage coordinated control model is constructed according to a preferred control parameter set, including:

[0088] According to the relevant operating state parameters of each preset control instruction as input data, multiple control parameters in the preferred control parameter set of each preset control instruction are used as output data, and neural network training is performed to obtain the preferred energy storage coordinated control model.

[0089] In some embodiments of the present application, generating a control strategy according to the preferred control parameters includes:

[0090] Acquire real-time relevant operating state parameters of the energy storage coordinated control system, input the real-time relevant operating state parameters into the optimal energy storage coordinated control model, and obtain multiple optimal control parameters;

[0091] Based on the mapping relationship between the preferred control parameters and the preset control process, the preferred control parameters are sorted by control time, and a control strategy is generated according to the sorting result.

[0092] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present application. These improvements and substitutions should also be regarded as the scope of protection of the present application.

Claims

1. A coordinated energy storage control system, characterized in that: include: An extraction module is used to analyze the historical operation log of the energy storage coordinated control system, extract the control parameters of the energy storage converter at different historical time nodes, and the operation status parameters of the power grid at the corresponding historical time nodes; An analysis module, used to calculate a state conversion coefficient of an operating state parameter, determine relevant operating state parameters of a preset control instruction according to the state conversion coefficient, analyze relevant operating state parameters and control parameters, determine characteristic control parameters, and generate a characteristic parameter group for each preset control instruction; A construction module is used to analyze the characteristic parameter group of the same preset control instruction, determine the preferred control parameter set of each preset control instruction according to the analysis result, and construct the preferred energy storage coordinated control model according to the preferred control parameter set; The control module is used to obtain real-time related operating status parameters, determine the preferred control parameters of the real-time related operating status parameters based on the preferred energy storage coordinated control model, and generate a control strategy according to the preferred control parameters.

2. The energy storage coordination control system according to claim 1, characterized in that: Determine the relevant operating state parameters of the preset control instruction according to the state conversion coefficient, including: Analyze multiple preset control instructions, determine the control flow involved in each preset control instruction, and arrange the control flow in a control order to obtain a control flow sequence K, K (k1, k2, ..., kn) of each preset control instruction, where ki is the i-th control flow and n is the number of control flows; Obtain the operating status parameters of adjacent historical time periods of multiple historical control time periods of the control process involved in each preset control instruction, calculate multiple state transition coefficients of each operating status parameter in adjacent historical time periods, and if multiple state transition coefficients are all greater than the preset state coefficient threshold, set the corresponding operating status parameter as the relevant operating status parameter of the corresponding control process of the preset control instruction.

3. The energy storage coordination control system according to claim 2, characterized in that: Analyze relevant operating status parameters and control parameters to determine characteristic control parameters, including: Establishing a time reference line according to multiple historical control time periods of each control process of the preset control instruction, and marking multiple acquisition time nodes on the time reference line based on the preset time interval; For each of the multiple collection time nodes of each time reference line, relevant operating status parameters are collected respectively, and the change amount mean analysis is performed on the relevant operating status parameters on the same time reference line, and the change time nodes whose change amount mean is greater than the preset change amount mean threshold are marked, and the weight coefficient of the marked corresponding change time node is set according to the change amount mean difference whose change amount mean is greater than the preset change amount mean threshold; Acquire multiple control parameters of the marked change time nodes of the same time reference line, and compare the multiple control parameters with the corresponding control parameters in the previous time period to obtain the change value of each control parameter at the marked change time node; The number of marked change time nodes whose change values ​​in the same time reference line are greater than a preset change value threshold, and the difference of the change values ​​whose change values ​​are greater than the preset change value threshold, are used to generate the importance of the control parameter in the historical control time period corresponding to the time reference line; Obtain the number of the same control parameter whose importance is greater than the importance threshold in multiple historical control time periods of each control process, and generate a quantity ratio with the total number of historical control time periods of the same control process; if the quantity ratio is greater than a preset quantity ratio threshold, set the current control parameter as the characteristic control parameter of the corresponding control process; The characteristic control parameters of each control flow of the same preset control instruction are used to generate characteristic control parameters of the corresponding preset control instruction.

4. The energy storage coordination control system according to claim 3, characterized in that: Generate the importance of the control parameters in the time reference line corresponding to the historical control time period, including: The calculation formula of the importance Gi is: Among them, f is the number of marked change time nodes in the same time reference line whose change value is greater than the preset change value threshold, y is the total number of marked change time nodes in the same time reference line, qs is the difference in the change value of the control parameter at the marked sth change time node, and as is the weight coefficient of the marked sth change time node.

5. The energy storage coordination control system according to claim 4, characterized in that: Construct a characteristic parameter group for each preset control instruction, including: The relevant operating state parameters and corresponding characteristic control parameters of each control flow in different historical control time periods under the same preset control instruction are used to construct a characteristic parameter group corresponding to the preset control instruction.

6. The energy storage coordination control system according to claim 5, characterized in that: Analyze the characteristic parameter group of the same preset control instruction, including: Comprehensively analyze multiple characteristic parameter groups of the same control process of each preset control instruction to obtain the historical control duration of each characteristic parameter group under the control parameters of different historical control time periods, the parameter difference between the relevant operating state parameters after the historical control duration and the standard operating state parameter interval, and multiple grid frequencies after the historical control duration; A compensation coefficient is set according to the historical control duration of multiple characteristic parameter groups of the same control process, a first evaluation value is set according to the multiple parameter differences between multiple relevant operating state parameters after the historical control duration and the standard operating state parameter interval, and a second evaluation value is set according to the fluctuation range of multiple power grid frequencies after the historical control duration; Generate application evaluation values ​​of control parameters of different historical control time periods in the corresponding characteristic parameter group according to the first evaluation value, the second evaluation value and the compensation coefficient; The application evaluation value is: H = h1*h2*c; Among them, H is the application evaluation value, h1 is the first evaluation value, h2 is the second evaluation value, and c is the compensation coefficient.

7. The energy storage coordination control system according to claim 6, characterized in that: Determine the optimal control parameter set for each preset control instruction based on the analysis results, including: Sorting the application evaluation values ​​corresponding to the control parameters of the characteristic parameter group of the same control flow of the same preset control instruction, and setting the multiple control parameters corresponding to the first-ranked application evaluation value as the preferred control parameter subset of the corresponding control flow; Based on the time sequence of the preset control process, the preferred control parameter subsets of the same preset control instruction are sorted, and the preferred control parameter set corresponding to the preset control instruction is generated according to the sorting result.

8. The energy storage coordination control system according to claim 7, characterized in that: The optimal energy storage coordinated control model is constructed according to the optimal control parameter set, including: According to the relevant operating state parameters of each preset control instruction as input data, multiple control parameters in the preferred control parameter set of each preset control instruction are used as output data, and neural network training is performed to obtain the preferred energy storage coordinated control model.

9. The energy storage coordination control system according to claim 8, characterized in that: Generate control strategies according to the optimal control parameters, including: Acquire real-time relevant operating state parameters of the energy storage coordinated control system, input the real-time relevant operating state parameters into the optimal energy storage coordinated control model, and obtain multiple optimal control parameters; Based on the mapping relationship between the preferred control parameters and the preset control process, the preferred control parameters are sorted by control time, and a control strategy is generated according to the sorting result.

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