Quantitative evaluation method and device for controllability of energy storage power station

Abstract

The invention relates to the technical field of energy storage, and particularly provides an energy storage power station controllable capability quantitative evaluation method and device, and the method comprises the steps: obtaining a standard value and a comprehensive weight corresponding to each controllable capability quantitative evaluation index of a to-be-evaluated energy storage power station; determining a controllable capability quantitative evaluation result of the energy storage power station to be evaluated based on the standard value and the comprehensive weight; and performing controllable capability quantitative evaluation on the to-be-evaluated energy storage power station by using the controllable capability quantitative evaluation result. According to the technical scheme provided by the invention, the controllability of the energy storage power station can be measured more comprehensively, so that the evaluation result is more practical.

Description

Technical Field

[0001] This invention relates to the field of energy storage technology, and specifically to a method and apparatus for quantitatively evaluating the controllability of an energy storage power station. Background Technology Currently, energy storage power stations are a primary means of improving the transient stability of power systems, with superconducting magnetic energy storage and flywheel energy storage being key technologies, mainly due to their rapid response capabilities. Therefore, assessing the controllability of energy storage power stations is particularly important.

[0002] The assessment of the controllability of energy storage power stations mainly focuses on the evaluation of their regulation capabilities in three application scenarios: peak shaving and valley filling, smoothing power fluctuations from new energy sources, and participation in power system frequency regulation. Some scholars have used the analytic hierarchy process (AHP) to conduct comprehensive evaluations of energy storage power stations based on evaluation indicators such as investment cost, lifespan, net present value, payback period, return on investment, and net energy storage revenue. Furthermore, in the scenario where energy storage participates in system frequency regulation, the SOC (State of Charge) of energy storage is evaluated and analyzed based on the power output control accuracy and response speed of the energy storage system. However, existing methods only focus on the regulation capabilities of energy storage itself, and there is a lack of research on the assessment of the availability and controllability of energy storage power stations in terms of grid transient support. Summary of the Invention

[0003] To overcome the above-mentioned shortcomings, this invention proposes a method and device for quantitatively evaluating the controllability of energy storage power stations.

[0004] Firstly, a method for quantitatively assessing the controllability of an energy storage power station is provided, the method comprising: Obtain the standard values ​​and comprehensive weights of each controllable capability quantitative evaluation index of the energy storage power station to be evaluated; The controllability quantitative assessment result of the energy storage power station to be evaluated is determined based on the standard value and comprehensive weight. The controllability quantitative assessment results are used to conduct a quantitative assessment of the controllability of the energy storage power station to be evaluated.

[0005] Preferably, the controllability quantitative evaluation index includes at least one of the following: active response time, reactive response time, maximum active output power, maximum reactive output power, minimum active duration of energy storage power output, minimum reactive duration of energy storage power output, SOC margin, active response accuracy, reactive response accuracy, and inertia level.

[0006] Furthermore, the active power response time and reactive power response time are as follows:

[0007]

[0008] In the above formula, △ t P For active response time, △ t Q For reactive response time, t 90%,P , t start,P These are the time to reach 90% steady-state power and the start-up time, respectively, during the active power response process. t 90%,Q , t start,Q These are the time it takes for the reactive response process to reach 90% steady-state power and the start-up time, respectively.

[0009] Furthermore, the maximum active power output and the maximum reactive power output are as follows:

[0010]

[0011] In the above formula, P max For maximum active power output, Q max This is the maximum reactive power output. P maxi For the first i The maximum active power output capacity of each energy storage unit. Q maxi For the first i The maximum reactive power output capacity of each energy storage unit, where n is the number of energy storage units.

[0012] Furthermore, when the energy storage is in a discharging state, the SOC margin is as follows:

[0013] When the energy storage is in a charging state, the SOC margin is as follows:

[0014] In the above formula, SOC mrg , SOC max , SOC t These represent the SOC margin, maximum SOC value, and current SOC value, respectively. SOC min This is the minimum SOC value.

[0015] Furthermore, the active power response accuracy and reactive power response accuracy are as follows:

[0016]

[0017] In the above formula, β P For active response accuracy, β Q For reactive response accuracy, P real , P order , Q real , Q order These are the active power execution value, active power command value, reactive power execution value, and reactive power command value of the energy storage power station, respectively.

[0018] Furthermore, the inertia level is as follows:

[0019] In the above formula, H bess The virtual inertia that energy storage can provide. H gen It can provide inertia for conventional units. H res It can provide inertia for new energy sources. H sys For inertia level.

[0020] Preferably, when the controllability quantitative evaluation index is a positive index, the standard value corresponding to the controllability quantitative evaluation index is as follows:

[0021] When the controllability quantitative assessment indicator is negative, the standard value corresponding to the controllability quantitative assessment indicator is as follows:

[0022] In the above formula, X last The standard value corresponding to the quantitative assessment index of controllability. X scale For the quantified data values ​​corresponding to the controllability assessment indicators, max( X scale ) represents the maximum value among the ensemble data corresponding to the quantitative assessment index of controllability, min( X scale ) represents the minimum value among the ensemble data corresponding to the quantitative assessment index of controllability.

[0023] Furthermore, the centralized data values ​​corresponding to the quantitative evaluation indicators of controllability are as follows:

[0024] In the above formula, X The indicator values ​​corresponding to the quantitative assessment indicators of controllability. Median(X) The central data for the indicator values ​​corresponding to the quantitative assessment indicators of controllability. IQR(X) The interquartile range of the index values ​​corresponding to the quantitative assessment indicators of controllability.

[0025] Furthermore, the central data and interquartile range of the index values ​​corresponding to the quantitative evaluation index of controllability are as follows:

[0026]

[0027] In the above formula, This represents the (m+1) / 2th data value in the vector of index values ​​corresponding to the quantitative assessment index of controllability. This represents the m / 2-th data value in the vector of indicator values ​​corresponding to the quantitative assessment indicators of controllability. Q 1. Q 3 represents the first and third quartiles in the vector of index values ​​corresponding to the quantitative assessment index of controllability.

[0028] Preferably, the process of obtaining the comprehensive weight includes: obtaining the comprehensive weight by using a game theory combined weighting method based on the subjective weight and objective weight corresponding to each controllable capability quantitative evaluation index, wherein the subjective weight is obtained by the analytic hierarchy process and the objective weight is obtained by the CRITIC method.

[0029] Furthermore, the quantitative assessment results of the controllability of the energy storage power station to be evaluated are as follows:

[0030] In the above formula, X Z The result is a quantitative assessment of the controllability of the energy storage power station to be evaluated. W represents the comprehensive weight, and T represents the transpose symbol.

[0031] Secondly, a device for quantitatively evaluating the controllability of an energy storage power station is provided, the device comprising: The acquisition module is used to acquire the standard values ​​and comprehensive weights of each controllable capability quantitative evaluation index of the energy storage power station to be evaluated. The determination module is used to determine the quantitative assessment result of the controllability of the energy storage power station to be evaluated based on the standard value and comprehensive weight. The evaluation module is used to perform a quantitative evaluation of the controllability of the energy storage power station to be evaluated using the quantitative evaluation results of the controllability.

[0032] Thirdly, a computer device is provided, comprising: one or more processors; The processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method for quantitatively evaluating the controllability of the energy storage power station is implemented.

[0033] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, wherein when the computer program is executed, the method for quantitatively evaluating the controllability of the energy storage power station is implemented.

[0034] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects: This invention provides a method and apparatus for quantitatively evaluating the controllability of an energy storage power station, comprising: acquiring standard values ​​and comprehensive weights corresponding to each controllability quantitative evaluation index of the energy storage power station to be evaluated; determining the controllability quantitative evaluation result of the energy storage power station to be evaluated based on the standard values ​​and comprehensive weights; and using the controllability quantitative evaluation result to perform a controllability quantitative evaluation of the energy storage power station to be evaluated. The technical solution provided by this invention constructs an index system for evaluating the controllability of energy storage power stations from multiple aspects, which can more comprehensively measure the controllability of energy storage power stations. Furthermore, when calculating the indicators, the current operating state of the energy storage (charging, discharging, fault ride-through, etc.) is also considered, differentiating the quantitative results of the controllability measurement indicators under different operating states, making the evaluation results more practical. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the main steps of the quantitative evaluation method for the controllability of energy storage power stations according to an embodiment of the present invention; Figure 2 This is a block diagram of the system architecture for quantitative evaluation of the controllability of energy storage power stations according to an embodiment of the present invention; Figure 3 This is a scatter plot of the comprehensive quantitative evaluation of an embodiment of the present invention; Figure 4 This is a statistical chart of the number of evaluation points in each interval according to an embodiment of the present invention; Figure 5 This is a comparison chart of the advantages and disadvantages of various types of indicators in embodiments of the present invention. Detailed Implementation

[0036] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Example 1 See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a method for quantitatively evaluating the controllability of an energy storage power station according to an embodiment of the present invention. Figure 1 As shown, the method for quantitatively evaluating the controllability of an energy storage power station in this embodiment of the invention mainly includes the following steps: Step S101: Obtain the standard values ​​and comprehensive weights corresponding to the quantitative evaluation indicators of each controllable capability of the energy storage power station to be evaluated; Step S102: Determine the quantitative assessment result of the controllability of the energy storage power station to be evaluated based on the standard value and comprehensive weight; Step S103: Use the controllability quantitative assessment results to conduct a controllability quantitative assessment of the energy storage power station to be assessed.

[0039] In this embodiment, the controllability quantitative evaluation index includes at least one of the following: active response time, reactive response time, maximum active output power, maximum reactive output power, minimum active duration of energy storage power output, minimum reactive duration of energy storage power output, SOC margin, active response accuracy, reactive response accuracy, and inertia level.

[0040] The above indicators take into account multiple aspects such as response speed, power output capability, capacity level, response accuracy, and inertia level. Based on this, such as Figure 2 As shown, a quantitative evaluation system for the controllability of energy storage power stations is constructed.

[0041] In one implementation, the active power response time and reactive power response time are as follows:

[0042]

[0043] In the above formula, △ t P For active response time, △ t Q For reactive response time, t 90%,P , t start,PThese are the time to reach 90% steady-state power and the start-up time, respectively, during the active power response process. t 90%,Q , t start,Q These are the time it takes for the reactive response process to reach 90% steady-state power and the start-up time, respectively.

[0044] In one embodiment, the maximum active power output and the maximum reactive power output are as follows:

[0045]

[0046] In the above formula, P max For maximum active power output, Q max This is the maximum reactive power output. P maxi For the first i The maximum active power output capacity of each energy storage unit. Q maxi For the first i The maximum reactive power output capacity of each energy storage unit, where n is the number of energy storage units.

[0047] In one implementation, when the energy storage is in a discharging state, the SOC margin is as follows:

[0048] When the energy storage is in a charging state, the SOC margin is as follows:

[0049] In the above formula, SOC mrg , SOC max , SOC t These represent the SOC margin, maximum SOC value, and current SOC value, respectively. SOC min This is the minimum SOC value.

[0050] In one implementation, the active power response accuracy and reactive power response accuracy are as follows:

[0051]

[0052] In the above formula, β P For active response accuracy, β Q For reactive response accuracy,P real , P order , Q real , Q order These are the active power execution value, active power command value, reactive power execution value, and reactive power command value of the energy storage power station, respectively.

[0053] In one implementation, the inertia level is as follows:

[0054] In the above formula, H bess The virtual inertia that energy storage can provide. H gen It can provide inertia for conventional units. H res It can provide inertia for new energy sources. H sys For inertia level.

[0055] In this embodiment, to avoid the impact of outliers in the indicator data on the overall normalization result, the present invention uses a robust normalization method for processing.

[0056] Robust normalization is a method specifically designed to handle outliers. It does not rely on the maximum and minimum values ​​of the data, but instead uses the median and interquartile range (IQR) for normalization. This makes it insensitive to outliers and better able to handle data with outliers. When the controllability quantitative evaluation index is a positive index, the standard value corresponding to the controllability quantitative evaluation index is as follows:

[0057] When the controllability quantitative assessment indicator is negative, the standard value corresponding to the controllability quantitative assessment indicator is as follows:

[0058] In the above formula, X last The standard value corresponding to the quantitative assessment index of controllability. X scale For the quantified data values ​​corresponding to the controllability assessment indicators, max( X scale ) represents the maximum value among the ensemble data corresponding to the quantitative assessment index of controllability, min( X scale) represents the minimum value among the ensemble data corresponding to the quantitative assessment index of controllability.

[0059] In one implementation, the centralized data values ​​corresponding to the controllability quantitative evaluation index are as follows:

[0060] In the above formula, X The indicator values ​​corresponding to the quantitative assessment indicators of controllability. Median(X) The central data for the indicator values ​​corresponding to the quantitative assessment indicators of controllability. IQR(X) The interquartile range of the index values ​​corresponding to the quantitative assessment indicators of controllability.

[0061] In one implementation, the central data and interquartile range of the index values ​​corresponding to the controllability quantitative evaluation index are as follows:

[0062]

[0063] In the above formula, This represents the (m+1) / 2th data value in the vector of index values ​​corresponding to the quantitative assessment index of controllability. This represents the m / 2-th data value in the vector of indicator values ​​corresponding to the quantitative assessment indicators of controllability. Q 1. Q 3 represents the first and third quartiles in the vector of index values ​​corresponding to the quantitative assessment index of controllability.

[0064] In this embodiment, the process of obtaining the comprehensive weight includes: obtaining the comprehensive weight by using a game theory combined weighting method based on the subjective weight and objective weight corresponding to each controllable capability quantitative evaluation index, wherein the subjective weight is obtained by the analytic hierarchy process and the objective weight is obtained by the CRITIC method.

[0065] The game theory-based combinatorial weighting method is a multi-attribute decision analysis method. Its basic idea is to obtain the weight relationships between attributes through a game process, thereby comprehensively evaluating the evaluation object. This method has the following advantages: (1) It can fully consider the mutual influence between the attributes and avoid the limitations of traditional weight determination methods.

[0066] (2) It can quantitatively describe the game process between attributes, thereby improving the objectivity and accuracy of the evaluation results.

[0067] (3) It can flexibly adjust the game parameters according to the characteristics of the evaluation object, and has strong adaptability.

[0068] In one implementation, the quantitative assessment results of the controllability of the energy storage power station to be evaluated are as follows:

[0069] In the above formula, X Z The result is a quantitative assessment of the controllability of the energy storage power station to be evaluated. W represents the comprehensive weight, and T represents the transpose symbol.

[0070] In one implementation, as shown in the above formula, the evaluation result is a discretized data set distributed between 0 and 1. To evaluate the quality of the data, it is subjected to interval grading, and the grading criteria are shown in Table 1 below: Table 1

[0071] Based on the above-mentioned interval classification standards and comprehensive quantitative results, the quantitative assessment results and distribution of the controllability of energy storage power stations under multiple assessments can be calculated.

[0072] Based on the aforementioned controllability assessment theory, a total of 100 assessments were conducted on the energy storage participation in the regulation process. The assessment results are as follows: Figure 3 As shown, by Figure 3 It can be seen that in the multiple assessments of the controllability of energy storage power stations, most assessment points were distributed in the "good" and "medium" range. Among them, the best assessment result was the 89th assessment, with a comprehensive assessment result of 0.791; the worst assessment result was the 46th assessment, with a comprehensive assessment result of 0.315. Table 2 below summarizes the extreme values ​​and average values ​​of the assessment results and other relevant information.

[0073] Table 2

[0074] The statistical results show that, after multiple assessments, the controllability evaluation quality of the energy storage power station fluctuated around 0.553, which is considered a good evaluation standard. To further clarify the data's interval distribution, Figure 4 The specific number of evaluation points for each evaluation interval is displayed.

[0075] Depend on Figure 4 It can be seen that the data distributed in the "good" and "medium" ranges constitute the majority, accounting for 43% and 44% of the total number of data, respectively, while a small amount of data is distributed in the "excellent" and "poor" ranges, accounting for 7% and 6%, respectively. The core task of subsequent control is to increase the amount of data in the excellent range and reduce the amount of data in the "medium" range, especially the "poor" range, so as to achieve a comprehensive improvement in the controllability of energy storage.

[0076] Finally, to effectively measure the controllability of energy storage power stations at different levels, quantitative evaluations were conducted from several perspectives, including response speed, power output capacity, capacity level, response accuracy, and inertia level. A horizontal comparison was made of the advantages and disadvantages of various indicators across multiple evaluation processes, such as... Figure 5 As shown.

[0077] Example 2 Based on the same inventive concept, the present invention also provides a device for quantitatively evaluating the controllability of an energy storage power station, the device comprising: The acquisition module is used to acquire the standard values ​​and comprehensive weights of each controllable capability quantitative evaluation index of the energy storage power station to be evaluated. The determination module is used to determine the quantitative assessment result of the controllability of the energy storage power station to be evaluated based on the standard value and comprehensive weight. The evaluation module is used to perform a quantitative evaluation of the controllability of the energy storage power station to be evaluated using the quantitative evaluation results of the controllability.

[0078] Preferably, the controllability quantitative evaluation index includes at least one of the following: active response time, reactive response time, maximum active output power, maximum reactive output power, minimum active duration of energy storage power output, minimum reactive duration of energy storage power output, SOC margin, active response accuracy, reactive response accuracy, and inertia level.

[0079] Furthermore, the active power response time and reactive power response time are as follows:

[0080]

[0081] In the above formula, △ t P For active response time, △ t Q For reactive response time, t 90%,P , t start,P These are the time to reach 90% steady-state power and the start-up time, respectively, during the active power response process. t 90%,Q , t start,Q These are the time it takes for the reactive response process to reach 90% steady-state power and the start-up time, respectively.

[0082] Furthermore, the maximum active power output and the maximum reactive power output are as follows:

[0083]

[0084] In the above formula, P max For maximum active power output, Q max This is the maximum reactive power output. P maxi For the first i The maximum active power output capacity of each energy storage unit. Q maxi For the first i The maximum reactive power output capacity of each energy storage unit, where n is the number of energy storage units.

[0085] Furthermore, when the energy storage is in a discharging state, the SOC margin is as follows:

[0086] When the energy storage is in a charging state, the SOC margin is as follows:

[0087] In the above formula, SOC mrg , SOC max , SOC t These represent the SOC margin, maximum SOC value, and current SOC value, respectively. SOC min This is the minimum SOC value.

[0088] Furthermore, the active power response accuracy and reactive power response accuracy are as follows:

[0089]

[0090] In the above formula, β P For active response accuracy, β Q For reactive response accuracy, P real , P order , Q real , Q order These are the active power execution value, active power command value, reactive power execution value, and reactive power command value of the energy storage power station, respectively.

[0091] Furthermore, the inertia level is as follows:

[0092] In the above formula,H bess The virtual inertia that energy storage can provide. H gen It can provide inertia for conventional units. H res It can provide inertia for new energy sources. H sys For inertia level.

[0093] Preferably, when the controllability quantitative evaluation index is a positive index, the standard value corresponding to the controllability quantitative evaluation index is as follows:

[0094] When the controllability quantitative assessment indicator is negative, the standard value corresponding to the controllability quantitative assessment indicator is as follows:

[0095] In the above formula, X last The standard value corresponding to the quantitative assessment index of controllability. X scale For the quantified data values ​​corresponding to the controllability assessment indicators, max( X scale ) represents the maximum value among the ensemble data corresponding to the quantitative assessment index of controllability, min( X scale ) represents the minimum value among the ensemble data corresponding to the quantitative assessment index of controllability.

[0096] Furthermore, the centralized data values ​​corresponding to the quantitative evaluation indicators of controllability are as follows:

[0097] In the above formula, X The indicator values ​​corresponding to the quantitative assessment indicators of controllability. Median(X) The central data for the indicator values ​​corresponding to the quantitative assessment indicators of controllability. IQR(X) The interquartile range of the index values ​​corresponding to the quantitative assessment indicators of controllability.

[0098] Furthermore, the central data and interquartile range of the index values ​​corresponding to the quantitative evaluation index of controllability are as follows:

[0099]

[0100] In the above formula, This represents the (m+1) / 2th data value in the vector of index values ​​corresponding to the quantitative assessment index of controllability. This represents the m / 2-th data value in the vector of indicator values ​​corresponding to the quantitative assessment indicators of controllability. Q 1. Q 3 represents the first and third quartiles in the vector of index values ​​corresponding to the quantitative assessment index of controllability.

[0101] Preferably, the process of obtaining the comprehensive weight includes: obtaining the comprehensive weight by using a game theory combined weighting method based on the subjective weight and objective weight corresponding to each controllable capability quantitative evaluation index, wherein the subjective weight is obtained by the analytic hierarchy process and the objective weight is obtained by the CRITIC method.

[0102] Furthermore, the quantitative assessment results of the controllability of the energy storage power station to be evaluated are as follows:

[0103] In the above formula, X Z The result is a quantitative assessment of the controllability of the energy storage power station to be evaluated. W represents the comprehensive weight, and T represents the transpose symbol.

[0104] Example 3 Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby realizing the steps of the energy storage power station controllability quantitative evaluation method in the above embodiments.

[0105] Example 4 Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the energy storage power station controllability quantitative evaluation method in the above embodiments.

[0106] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0107] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0108] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0109] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for quantitatively evaluating the controllability of an energy storage power station, characterized in that, The method includes: Obtain the standard values ​​and comprehensive weights of each controllable capability quantitative evaluation index of the energy storage power station to be evaluated; The controllability quantitative assessment result of the energy storage power station to be evaluated is determined based on the standard value and comprehensive weight. The controllability quantitative assessment results are used to conduct a quantitative assessment of the controllability of the energy storage power station to be evaluated.

2. The method as described in claim 1, characterized in that, The controllability quantitative evaluation index includes at least one of the following: active response time, reactive response time, maximum active output power, maximum reactive output power, minimum active duration of energy storage power output, minimum reactive duration of energy storage power output, SOC margin, active response accuracy, reactive response accuracy, and inertia level.

3. The method as described in claim 2, characterized in that, The active power response time and reactive power response time are as follows: In the above formula, △ t P For active response time, △ t Q For reactive response time, t 90%,P , t start,P These are the time to reach 90% steady-state power and the start-up time, respectively, during the active power response process. t 90%,Q , t start,Q These are the time it takes for the reactive response process to reach 90% steady-state power and the start-up time, respectively.

4. The method as described in claim 2, characterized in that, The maximum active power output and maximum reactive power output are as follows: In the above formula, P max For maximum active power output, Q max This is the maximum reactive power output. P maxi For the first i The maximum active power output capacity of each energy storage unit. Q maxi For the first i The maximum reactive power output capacity of each energy storage unit, where n is the number of energy storage units.

5. The method as described in claim 2, characterized in that, When the energy storage is in a discharging state, the SOC margin is as follows: When the energy storage is in a charging state, the SOC margin is as follows: In the above formula, SOC mrg , SOC max , SOC t These represent the SOC margin, maximum SOC value, and current SOC value, respectively. SOC min This is the minimum SOC value.

6. The method as described in claim 2, characterized in that, The active power response accuracy and reactive power response accuracy are as follows: In the above formula, β P For active response accuracy, β Q For reactive response accuracy, P real , P order , Q real , Q order These are the active power execution value, active power command value, reactive power execution value, and reactive power command value of the energy storage power station, respectively.

7. The method as described in claim 2, characterized in that, The inertia level is as follows: In the above formula, H bess The virtual inertia that energy storage can provide. H gen It can provide inertia for conventional units. H res It can provide inertia for new energy sources. H sys For inertia level.

8. The method as described in claim 1, characterized in that, When the controllability quantitative evaluation index is a positive index, the standard value corresponding to the controllability quantitative evaluation index is as follows: When the controllability quantitative assessment indicator is negative, the standard value corresponding to the controllability quantitative assessment indicator is as follows: In the above formula, X last The standard value corresponding to the quantitative assessment index of controllability. X scale For the quantified data values ​​corresponding to the controllability assessment indicators, max( X scale ) represents the maximum value among the ensemble data corresponding to the quantitative assessment index of controllability, min( X scale ) represents the minimum value among the ensemble data corresponding to the quantitative assessment index of controllability.

9. The method as described in claim 8, characterized in that, The centralized data values ​​corresponding to the quantitative evaluation indicators of controllability are as follows: In the above formula, X The indicator values ​​corresponding to the quantitative assessment indicators of controllability. Median(X) The central data for the indicator values ​​corresponding to the quantitative assessment indicators of controllability. IQR(X) The interquartile range of the index values ​​corresponding to the quantitative assessment indicators of controllability.

10. The method as described in claim 9, characterized in that, The central data and interquartile range of the index values ​​corresponding to the quantitative evaluation index of controllability are as follows: In the above formula, This represents the (m+1) / 2th data value in the vector of index values ​​corresponding to the quantitative assessment index of controllability. This represents the m / 2-th data value in the vector of indicator values ​​corresponding to the quantitative assessment indicators of controllability. Q 1. Q 3 represents the first and third quartiles in the vector of index values ​​corresponding to the quantitative assessment index of controllability.

11. The method as described in claim 1, characterized in that, The process of obtaining the comprehensive weight includes: obtaining the comprehensive weight by using a game theory combination weighting method based on the subjective and objective weights corresponding to each controllable capability quantitative evaluation index, wherein the subjective weights are obtained by the analytic hierarchy process and the objective weights are obtained by the CRITIC method.

12. The method as described in claim 8, characterized in that, The quantitative assessment results of the controllability of the energy storage power station to be evaluated are as follows: In the above formula, X Z The result is a quantitative assessment of the controllability of the energy storage power station to be evaluated. W represents the comprehensive weight, and T represents the transpose symbol.

13. An apparatus based on the quantitative evaluation method for the controllability of an energy storage power station according to any one of claims 1-12, characterized in that, The device includes: The acquisition module is used to acquire the standard values ​​and comprehensive weights of each controllable capability quantitative evaluation index of the energy storage power station to be evaluated. The determination module is used to determine the quantitative assessment result of the controllability of the energy storage power station to be evaluated based on the standard value and comprehensive weight. The evaluation module is used to perform a quantitative evaluation of the controllability of the energy storage power station to be evaluated using the quantitative evaluation results of the controllability.

14. A computer device, characterized in that, include: One or more processors; The processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method for quantitatively evaluating the controllability of an energy storage power station as described in any one of claims 1 to 12 is implemented.

15. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the method for quantitatively evaluating the controllability of an energy storage power station as described in any one of claims 1 to 12.

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