New energy power plant black-start capability assessment method

Abstract

The invention relates to a new energy power plant black-start capability evaluation method, which comprises the steps of determining evaluation indexes for evaluating the black-start capability of a new energy power plant, including a continuous output capability index, a black-start voltage regulation capability index, a frequency modulation capability index, a frequency modulation time index and a virtual inertia index; obtaining the value of each evaluation index of the new energy power plant to be evaluated, and constructing a standardized evaluation matrix; and based on the standardized evaluation matrix, adopting an entropy weight fuzzy comprehensive evaluation method to evaluate the black-start capability of the to-be-evaluated new energy power plants, and realizing sorting of the black-start capabilities of the plurality of to-be-evaluated new energy power plants. According to the invention, on the basis of seasonal historical data of the new energy power plant, a black-start capability evaluation index system based on seasonal characteristics of the new energy power plant is constructed. And the lack of research on the black-start capability evaluation scheme of the new energy power plant in the prior art is made up. The method can meet the demand of off-line evaluation, and is suitable for industrial application.

Description

Technical Field

[0001] The present invention relates to the technical field of black start, and in particular to a method for evaluating the black start capability of a new energy power plant. Background Art

[0002] A black start is the process of gradually restoring power to the entire power grid, starting with the black start generators, after a system-wide outage caused by a disaster or failure. In traditional power grids primarily based on synchronous generators, self-starting hydropower units and gas turbines are the primary black start power sources, gradually restoring power to the grid and loads through a "top-down" approach. With the continuous advancement of hardware and control technologies for renewable energy grid integration, renewable energy power plants have also developed black start capabilities under certain conditions. However, due to the inherent randomness and fluctuations of renewable energy, the feasibility and capacity of renewable energy power plants as black start power sources are constantly evolving.

[0003] Existing technology typically assesses the black start capability of renewable energy sites (such as wind farms with energy storage and photovoltaic power plants) through online prediction using artificial intelligence (AI) neural networks. This approach primarily involves building a black start simulation model to obtain sample data on frequency and voltage deviations and limit-exceeding durations; defining relevant evaluation metrics such as the start-up service safety level and the spatiotemporal black start support capability; and training a neural network using the inputs of sunlight intensity, installed photovoltaic generator capacity, energy storage configuration, storage SOC, source-load electrical distance, and load level to be restored, with the output of the start-up service safety level metric. This method rapidly predicts the spatiotemporal black start support capability of renewable energy sources. This approach is only suitable for online prediction and evaluation. Furthermore, it fails to consider the inherent random and fluctuating characteristics of renewable energy sources and the impact of these factors on black start capability. Consequently, this approach suffers from limitations in both applicability and accuracy in practical industrial applications. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention provides a method for evaluating the black start capability of a new energy power plant, which makes up for the defect of the existing technology that there is a lack of an effective and correct evaluation method for the black start capability of different new energy power plants with seasonal characteristics.

[0005] The technical solution adopted in the present invention is as follows: The present invention provides a method for evaluating the black start capability of a new energy power plant, comprising the following steps: Determine the evaluation indicators for evaluating the black start capability of the new energy power plant, which include: Sustained output capacity indicator, which is used to quantify the power output's ability to sustainably support load demand in a certain season; Black start voltage regulation capability, which quantifies the ability of a new energy power plant to maintain the grid connection point voltage within the operating limits specified by the grid by dynamically adjusting the reactive power output by the inverter and on-site reactive power compensation equipment; Frequency regulation capability indicator, which is used to quantify the ability of frequency regulation reserve power to support load demand during black start in a certain season; Frequency regulation time indicator, which is used to reflect the response speed of renewable energy power plants to frequency steps; and virtual inertia index; Obtaining the values ​​of the evaluation indicators of the new energy power plant to be evaluated and constructing a standardized evaluation matrix; Based on the standardized evaluation matrix, the black start capability of the new energy power plant to be evaluated is evaluated by adopting the entropy weight fuzzy comprehensive evaluation method, so as to achieve the ranking of the black start capabilities of the multiple new energy power plants to be evaluated.

[0006] Further technical solutions are: The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the continuous output capability indicator, which includes: According to the historical data of the new energy power plant in the set season, the proportion of the new energy output continuously greater than the started load within the set time is counted, and the proportion is used as the value of the continuous output capacity indicator.

[0007] The calculation formula of the proportion is as follows:

[0008] in, Indicates the frequency or probability of the event in brackets; Indicates the time from the set season t At the time t + T New energy output during the period; k is a proportional coefficient greater than 1; P load is the required power of the started load.

[0009] The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the black start voltage regulation capability indicator, which includes: Calculate the adjustable range of reactive power of the grid-connected inverter of a new energy power plant:

[0010] in, are respectively the maximum and minimum values ​​of the reactive power of the grid-connected inverter; They are the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the remaining apparent power capacity, the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the reserve power, and the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the inverter's own current and voltage. Calculate the maximum adjustable range of reactive power of new energy power plants: in, are the maximum reactive power that can be provided and absorbed by the new energy power plant respectively; The maximum reactive power that can be provided and absorbed by the reactive power compensation equipment in the factory respectively; by The difference is used as the value of the black start voltage regulation capability indicator.

[0011] The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the frequency regulation capability indicator, which includes: Based on the historical data of the new energy power plant in the set season, the sum of the new energy output and the maximum output power of the energy storage equipped by the new energy power plant is continuously greater than the started load within the set time. times the proportion, and the proportion is used as the value of the frequency modulation capability indicator.

[0012] The calculation formula of the proportion is as follows: in, Indicates the frequency or probability of the event in brackets; Indicates the time from t At the time t+T f The output of new energy during the period, T f is the FM duration; k f is the frequency regulation standby ratio coefficient; P load is the required power of the started load; The maximum output power of energy storage equipped for new energy power plants.

[0013] The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the frequency modulation time indicator, which includes: Calculating FM response time : Where, t 1 is the frequency deviation of the new energy power plant When the preset dead zone threshold is exceeded, t 2 is the moment when the new energy output begins to change; Calculate adjustment time : Where, To ensure that the active power output of renewable energy reaches its target frequency modulation power moments, in which H Less than 100; The frequency modulation response time and the adjustment time are added together to obtain the value of the frequency modulation time indicator.

[0014] The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the virtual inertia indicator, which includes: The inertia of a new energy power plant under grid control is estimated using the following estimation model: H s : in, S is the rated apparent power of the new energy power plant; P m Active power reference value set for the controller of the new energy power plant with virtual inertia control add-on; P e The actual output active power of the new energy grid connection point; is the time rate of change of the grid frequency; is the rated frequency; is the deviation between the grid frequency and the rated frequency; Fit a polynomial curve to the frequency response to determine The value of , and substitute it into the estimation model to obtain the estimated value of the inertia constant : in, A 1 is the coefficient of the fitted polynomial; The estimated value of the inertia constant is used as the value of the virtual inertia index.

[0015] The entropy weight fuzzy comprehensive evaluation method is used to evaluate the black start capability of the new energy power plant to be evaluated. The standardized evaluation matrix is ​​constructed, including: In the calculation of the standardized evaluation matrix, i The first new energy power plant j The value of the evaluation index The entropy and entropy weight of the evaluation indicators are combined with the subjective weight of the experts to calculate the comprehensive weight of each evaluation indicator, and a comprehensive weight set is constructed to describe the importance of each evaluation indicator; wherein, i =1,2,…, m ; j =1,2,…, n ; m , n are the number of new energy power plants to be evaluated and the number of evaluation indicators; Determining a review set including multiple review levels; Calculate the value of the evaluation index Based on the membership degree of each comment level, a fuzzy evaluation matrix of each new energy power plant is obtained; Combining the comprehensive weight set and the fuzzy evaluation matrix of each new energy power plant through fuzzy synthesis operation to obtain a comprehensive evaluation set, which is used to reflect the membership distribution of the black start capability of each new energy power plant relative to all evaluation levels; The comprehensive evaluation set is normalized to obtain an evaluation of the black start capability of each renewable energy power plant.

[0016] The construction of the standardized evaluation matrix includes: Get the first i The first new energy power plant j The value of the evaluation index , construct the original evaluation matrix; According to the characteristics of each evaluation index, the original evaluation matrix is ​​standardized to obtain After standardization ,make It is a positive indicator where the larger the value, the better the performance.

[0017] The beneficial effects of the present invention are as follows: Based on historical seasonal data from new energy power plants, this paper constructs a black start capability evaluation index system tailored to the seasonal characteristics of new energy power plants. This index system encompasses sustained output capability, frequency regulation capability, frequency regulation time, virtual inertia, and voltage regulation capability. Based on this capability evaluation index system, an entropy-weighted fuzzy comprehensive evaluation method is employed to comprehensively assess the overall black start capability of new energy power plants. This approach addresses the lack of existing research on black start capability assessment schemes for new energy power plants. It can meet the need for off-line evaluation and is suitable for industrial applications.

[0018] This invention uses evaluation indicators: renewable energy continuous output capability, frequency regulation capability, frequency regulation time, virtual inertia, and voltage regulation capability. These indicators encompass key performance dimensions for maintaining system stability and achieving rapid recovery during a black start. Therefore, they comprehensively reflect the black start capabilities of renewable energy sources and provide a reference for selecting renewable energy black start power sources. The renewable energy continuous output capability reflects the ability of renewable energy sources to overcome inherent fluctuations and stably cover load power demand during the system recovery period (tens of minutes to several hours), rather than focusing on peak power. The frequency regulation capability indicator directly reflects the degree to which backup capacity matches actual system recovery requirements, providing greater engineering guidance. The frequency regulation time indicator prioritizes power plants with ultra-fast primary frequency regulation response, thereby avoiding power sources with slow response due to communication delays, complex calculations, or protection logic. The virtual inertia indicator quantifies the ability of a renewable energy power plant to act as a virtual synchronous generator and is a key indicator of whether the system can withstand the initial disturbance without crashing. The voltage regulation capability indicator reflects the overall reactive power and voltage support capabilities of a renewable energy power plant, measuring its ability to survive and maintain stability under the extreme operating conditions of a black start. Therefore, the present invention takes into account the inherent randomness and fluctuation characteristics of renewable energy and considers the impact of factors related to the random fluctuation characteristics of renewable energy on black start capability. The evaluation results are more realistic and more accurate.

[0019] Other features and advantages of the present invention will be set forth in the following description or may be learned by practicing the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Schematic diagram of the process of the embodiment of the present invention. DETAILED DESCRIPTION

[0021] The specific embodiments of the present invention are described below with reference to the accompanying drawings.

[0022] See also Figure 1 A method for evaluating the black start capability of a new energy power plant in this embodiment includes the following steps: S1. Determine evaluation indicators for evaluating the black start capability of the new energy power plant, including: Sustained output capacity indicator, which is used to quantify the power output's ability to sustainably support load demand in a certain season; Black start voltage regulation capability, which quantifies the ability of a renewable energy power plant to maintain the point of common coupling (PCC) voltage within the operating limits specified by the grid by dynamically adjusting the reactive power output of the inverter and on-site reactive power compensation equipment; Frequency regulation capability indicator, which is used to quantify the ability of frequency regulation reserve power to support load demand during black start in a certain season; Frequency regulation time indicator, which is used to reflect the response speed of renewable energy power plants to frequency steps; and virtual inertia index; S2. Obtain the values ​​of the evaluation indicators of the new energy power plant to be evaluated and construct a standardized evaluation matrix; S3. Based on the standardized evaluation matrix, an entropy weight fuzzy comprehensive evaluation method is used to evaluate the black start capability of the new energy power plant to be evaluated, so as to achieve ranking of the black start capabilities of multiple new energy power plants to be evaluated.

[0023] This example constructs a seasonal evaluation index system for renewable energy black start capability based on historical renewable energy data. It uses an entropy-weighted fuzzy comprehensive evaluation method to comprehensively assess the overall black start capability of renewable energy power plants. This addresses the lack of seasonal renewable energy black start capability assessment in existing evaluation methods.

[0024] The step of obtaining the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes: 1. During a black start of a power grid, the renewable energy source serving as the black start power source must maintain continuous and stable output to support the recovery of the black start path. Therefore, this embodiment sets an indicator that can quantify this capability. As a preferred method, obtaining the value of the continuous output capability indicator includes: According to the historical data of the new energy power plant in the set season, the proportion of the new energy output continuously greater than the started load within the set time is counted, and the proportion is used as the value of the continuous output capacity indicator.

[0025] The calculation formula for the land occupation is preferably as follows:

[0026] in, Indicates the frequency or probability of the event in brackets, which is used to characterize the proportion described; Indicates the time from the set season t At the time t + T It is understandable that new energy output T is the set value; k A proportional coefficient greater than 1 to take into account network losses, active and reactive power regulation margins, preferably 1.2; P load is the required power of the started load.

[0027] 2. Considering that the maximum reactive power that a new energy grid-connected inverter can provide / absorb is limited by the remaining apparent power capacity, active power output level, reserve power, and the current and voltage of the inverter itself, as a preferred method, obtaining the value of the black start voltage regulation capability indicator includes: Calculate the adjustable range of reactive power of the grid-connected inverter of a new energy power plant:

[0028] in, are respectively the maximum and minimum values ​​of the reactive power of the grid-connected inverter; They are the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the remaining apparent power capacity, the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the reserve power, and the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the inverter's own current and voltage. Calculate the maximum adjustable range of reactive power of new energy power plants: in, are the maximum reactive power that can be provided and absorbed by the new energy power plant respectively; are the maximum reactive power that can be provided and absorbed by the reactive power compensation equipment in the plant, respectively; the reactive power compensation equipment in the plant includes SVG, STATCOM, capacitor bank and reactor bank, etc.; by The difference is used as the value of the black start voltage regulation capability indicator.

[0029] Among them, the maximum adjustable range of the grid-connected inverter reactive power under the constraint of the remaining apparent power capacity is: Where, are the maximum reactive power that the grid-connected inverter can provide and absorb under the constraint of the remaining apparent power capacity; is the apparent power capacity of the inverter; kP load is the current active power output level.

[0030] Among them, the maximum adjustable range of reactive power of the grid-connected inverter under the reserve power constraint is: Where, It is the maximum reactive power that the grid-connected inverter can provide and absorb under the reserve power constraint; It is the seasonal average power of the new energy power plant under the premise of meeting the continuous output capacity index. It is mainly affected by wind speed or light intensity and can be obtained by statistics based on historical data. If the predicted power at the time of black start can be obtained, It can also be replaced by predicted power.

[0031] Among them, the maximum adjustable range of reactive power of the grid-connected inverter under the constraints of the inverter's own current and voltage is: Set the minimum voltage of the grid connection point , maximum voltage , then: Where: are the maximum reactive power that the grid-connected inverter can provide and absorb under the constraints of the inverter's own current and voltage respectively; They are respectively the maximum and minimum (negative values) of the q-axis component of the current output from the grid connection point.

[0032] 3. As a black start power source, new energy sources need to have a certain amount of frequency modulation standby power during the black start process. Therefore, this embodiment uses a frequency modulation capability index to quantify this capability. As a preferred method, obtaining the value of the frequency modulation capability index includes: Based on the historical data of the new energy power plant in the set season, the sum of the new energy output and the maximum output power of the energy storage equipped by the new energy power plant is continuously greater than the started load within the set time. times the proportion, and the proportion is used as the value of the frequency modulation capability indicator.

[0033] The calculation formula of the proportion is preferably as follows: in, Indicates the frequency or probability of the event in brackets, which is used to characterize the proportion described; Indicates the time from t At the time t+T f The output of new energy during the period, T f is the duration of frequency modulation, which can be 0.5h; k f is the frequency regulation standby ratio coefficient, which can be set to 1.5; P load is the required power of the started load; The maximum output power of energy storage equipped for new energy power plants.

[0034] 4. Renewable energy sources have a rapid frequency modulation response. The response speed of photovoltaic power generation depends primarily on inverter control, often reaching hundreds of milliseconds, but initial power depends on sunlight intensity. The response speed of wind power generation is significantly affected by turbine type and control strategy. Wind turbines with full-power converters (permanent magnet direct drive, doubly fed asynchronous + full-power back-to-back) can achieve a response in seconds. This embodiment uses a frequency modulation time indicator to reflect the response speed of a new energy power plant to a frequency step. As a preferred method, obtaining the value of the frequency modulation time indicator includes: Calculating FM response time : Where, t 1 is the frequency deviation of the new energy power plant When the preset dead zone threshold (which can be set to ±0.1Hz) is exceeded, t 2 is the moment when the new energy output begins to change; Calculate adjustment time : Where, To ensure that the active power output of renewable energy reaches its target frequency modulation power moments, in which HLess than 100, preferably 90 or 95; Add the frequency modulation response time and the adjustment time , as the value of the FM time indicator:

[0035] 5. The inertia of the power system refers to the change in the amount of energy stored inside the system when the power system is subjected to load changes in a short period of time. The reduction in inertia will lead to rapid changes in the rate of change of grid frequency (RoCoF) (Hz / s) and greater frequency deviation, which may trigger the action of the RoCoF relay and the low-frequency load reduction relay, and even cause cascade tripping, causing the entire system to collapse, thereby causing the black start failure. During the black start process, the grid-connected new energy power plant, as the only power source, provides the entire inertia of the system, that is, the system inertia at this time is equal to the asynchronous inertia of the new energy power plant as the black start power source. As a preferred method, this embodiment obtains the value of the virtual inertia indicator, including: The inertia of a new energy power plant under grid control is estimated using the following estimation model: H s : in, S is the rated apparent power of the new energy power plant, in volt-ampere (VA); P m Active power reference value set for the controller of the new energy power plant with virtual inertia control add-on; P e The actual output active power of the new energy grid connection point; is the time rate of change of the grid frequency; is the rated frequency; is the deviation between the grid frequency and the rated frequency; The value of is preferably determined by fitting a polynomial curve to the frequency response, as shown below: All coefficients of the fitted polynomial can be determined by curve fitting … ; At the disturbance moment (i.e., t=0s), the higher-order terms are omitted, so that , which is substituted into the estimation model to obtain the estimated value of the inertia constant :

[0036] The estimated value of the inertia constant is used as the value of the virtual inertia index.

[0037] Specifically, this indicator can be obtained by building a simulation model and then performing simulation calculations.

[0038] As a preferred embodiment, the entropy weight fuzzy comprehensive evaluation method is used to evaluate the black start capability of the new energy power plant to be evaluated. The construction of the standardized evaluation matrix specifically includes the following steps: (1) Obtain the i The first new energy power plant j The value of the evaluation index , construct the original evaluation matrix: in, i =1,2,…, m ; j =1,2,…, n ; m , n are the number of new energy power plants to be evaluated and the number of evaluation indicators respectively; it can be understood that in this embodiment n That is 5; According to the characteristics of each evaluation index, the original evaluation matrix is ​​standardized to obtain After standardization ,make It is a positive indicator where the larger the value, the better the performance, thus obtaining a standardized evaluation matrix.

[0039] Specifically, in this embodiment, the frequency regulation time indicator is a cost-based indicator; that is, the smaller this indicator is, the stronger the black start capability of the new energy power plant. The continuous output capability indicator, frequency regulation capability indicator, virtual inertia indicator, and voltage regulation capability indicator are benefit-based indicators; that is, the larger these indicators are, the stronger the black start capability of the new energy power plant is.

[0040] Standardize according to the characteristics of different indicators and process the benefit-type indicators as follows: Cost-type indicators are processed as follows:

[0041] In the above two formulas, is the index value after normalization, that is, the element in the normalized evaluation matrix.

[0042] (2) Calculate the standardized evaluation matrix, i The first new energy power plant j Evaluation indicators The entropy of the value and entropy weight : Where, ; , ; Get the entropy weight vector of the five evaluation indicators , and then combined with the expert's subjective weight λ1 Calculate the comprehensive weight of each evaluation index: , obtain the comprehensive weight set used to describe the importance of each evaluation index ;in μ is the expert’s subjective weight ratio coefficient. μ= 1 means that the objective entropy weight is equal to the subjective expert weight.

[0043] (3) Determine the review set containing multiple review levels: .

[0044] (4) Calculate the value of the evaluation index The membership degree of each comment level is used to obtain the fuzzy evaluation matrix of each new energy power plant.

[0045] Specifically, choose the isosceles triangle membership function:

[0046] Where, For the i The first new energy power plant j Evaluation indicators c ij Relative to the k ( k =1,2,3,4,5) comments v k The degree of membership of p k is the left boundary; parameter q k is the center and peak value; parameter s k is the right boundary. v 1 take 、 、 ;right v 2 take ,right v 3 take ,right v 4 take ,right v 5 take .

[0047] Thus we get the i The fuzzy evaluation matrix of a new energy power plant:

[0048] (5) Through fuzzy synthesis operation, the comprehensive weight set A and the fuzzy evaluation matrix of each new energy power plant are synthesized to obtain the comprehensive evaluation set , which is used to reflect the membership distribution of the black start capability of the new energy power plant relative to all evaluation levels; operator Adoption model , then:

[0049] right Perform normalization:

[0050] Can get the first i Fuzzy comprehensive evaluation results of new energy power plants: ; The black start capability evaluation of each renewable energy power plant can be determined based on the maximum membership principle. By setting a score for each evaluation, the comprehensive black start capability score of each renewable energy power plant can be calculated. :

[0051] The comprehensive evaluation set is normalized to obtain an evaluation of the black start capability of each renewable energy power plant.

[0052] The feasibility and effectiveness of the method of this embodiment are further illustrated by using specific examples below.

[0053] The example dataset uses historical winter data from 10 wind farms in North China. The data resolution is 15 minutes, and each sample contains the short-term predicted power, actual wind speed, and actual power of the 10 wind farms. The wind farm information is shown in Table 1:

[0054] Assume that the above 10 wind power plants have undergone grid-type transformation: This includes converting 20% ​​of wind turbines into grid-type wind turbines, and incorporating a grid-type battery energy storage device with a capacity of 25% of the wind power plant's maximum power at each wind farm's grid connection point, with a storage capacity capable of sustainably outputting the maximum power for 1 hour.

[0055] The calculation of winter black start evaluation indicators and comprehensive evaluation results of 10 wind power plants are shown in Table 2.

[0056] Table 2 Index calculation and comprehensive evaluation results

[0057] Table 2 shows that wind farms WF1, WF5, WF6, and WF9 are deemed infeasible due to their weak seasonal sustained output capabilities, failing to meet black start requirements. Six wind farms, including WF7, are capable of black start. A comprehensive evaluation of wind farms with feasible indicators reveals that WF7 possesses the strongest winter black start capability.

[0058] Those skilled in the art will understand that the foregoing descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will be able to modify the technical solutions described in the foregoing embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for evaluating the black start capability of a new energy power plant, characterized in that: The following steps are involved: Determine the evaluation indicators for evaluating the black start capability of the new energy power plant, which include: Sustained output capacity indicator, which is used to quantify the power output's ability to sustainably support load demand in a certain season; Black start voltage regulation capability, which quantifies the ability of a new energy power plant to maintain the grid connection point voltage within the operating limits specified by the grid by dynamically adjusting the reactive power output by the inverter and on-site reactive power compensation equipment; Frequency regulation capability indicator, which is used to quantify the ability of frequency regulation reserve power to support load demand during black start in a certain season; Frequency regulation time indicator, which is used to reflect the response speed of renewable energy power plants to frequency steps; and virtual inertia index; Obtaining the values ​​of the evaluation indicators of the new energy power plant to be evaluated and constructing a standardized evaluation matrix; Based on the standardized evaluation matrix, the black start capability of the new energy power plant to be evaluated is evaluated by adopting the entropy weight fuzzy comprehensive evaluation method, so as to achieve the ranking of the black start capabilities of the multiple new energy power plants to be evaluated.

2. The black start capability assessment method for a new energy power plant according to claim 1, characterized in that: The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the continuous output capability indicator, which includes: According to the historical data of the new energy power plant in the set season, the proportion of the new energy output continuously greater than the started load within the set time is counted, and the proportion is used as the value of the continuous output capacity indicator.

3. The black start capability assessment method of a new energy power plant according to claim 2, characterized in that: The calculation formula of the proportion is as follows: ,in, Indicates the frequency or probability of the event in brackets; Indicates the time from the set season t At the time t + T New energy output during the period; k is a proportional coefficient greater than 1; P load is the required power of the started load.

4. The black start capability assessment method of a new energy power plant according to claim 1, characterized in that: The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the black start voltage regulation capability indicator, which includes: Calculate the adjustable range of reactive power of the grid-connected inverter of a new energy power plant: ,in, are respectively the maximum and minimum values ​​of the reactive power of the grid-connected inverter; They are the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the remaining apparent power capacity, the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the reserve power, and the maximum and minimum reactive power values ​​of the grid-connected inverter under the constraint of the inverter's own current and voltage. Calculate the maximum adjustable range of reactive power of new energy power plants: ,in, are the maximum reactive power that can be provided and absorbed by the new energy power plant respectively; Respectively, the maximum reactive power that can be provided and absorbed by the reactive power compensation equipment in the factory; The difference is used as the value of the black start voltage regulation capability indicator.

5. The black start capability assessment method of a new energy power plant according to claim 1, characterized in that: The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the frequency regulation capability indicator, which includes: Based on the historical data of the new energy power plant in the set season, the sum of the new energy output and the maximum output power of the energy storage equipped by the new energy power plant is continuously greater than the started load within the set time. times the proportion, and the proportion is used as the value of the frequency modulation capability indicator.

6. The black start capability assessment method of a new energy power plant according to claim 5, characterized in that: The calculation formula of the proportion is as follows: ,in, Indicates the frequency or probability of the event in brackets; Indicates the time from t At the time t+T f The output of new energy during the period, T f is the FM duration; k f is the frequency regulation standby ratio coefficient; P load is the required power of the started load; The maximum output power of energy storage equipped for new energy power plants.

7. The black start capability assessment method of a new energy power plant according to claim 1, characterized in that: The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the frequency modulation time indicator, which includes: Calculating FM response time : , where t 1 is the frequency deviation of the new energy power plant When the preset dead zone threshold is exceeded, t 2 is the moment when the new energy output starts to change; calculate the adjustment time : , where To ensure that the active power output of renewable energy reaches its target frequency modulation power moments, in which H Less than 100; summing the frequency modulation response time and the adjustment time as the value of the frequency modulation time indicator.

8. The black start capability assessment method of a new energy power plant according to claim 1, characterized in that: The obtaining of the values ​​of the evaluation indicators of the new energy power plant to be evaluated includes obtaining the value of the virtual inertia indicator, which includes: The inertia of a new energy power plant under grid control is estimated using the following estimation model: H s : ,in, S is the rated apparent power of the new energy power plant; P m Active power reference value set for the controller of the new energy power plant with virtual inertia control add-on; P e The actual output active power of the new energy grid connection point; is the time rate of change of the grid frequency; is the rated frequency; is the deviation between the grid frequency and the rated frequency; Fit a polynomial curve to the frequency response to determine The value of , and substitute it into the estimation model to obtain the estimated value of the inertia constant : ,in, A 1 is the coefficient of the fitted polynomial; The estimated value of the inertia constant is used as the value of the virtual inertia index.

9. The black start capability assessment method of a new energy power plant according to claim 1, characterized in that: The entropy weight fuzzy comprehensive evaluation method is used to evaluate the black start capability of the new energy power plant to be evaluated. The standardized evaluation matrix is ​​constructed, including: In the calculation of the standardized evaluation matrix, i The first new energy power plant j The value of the evaluation index The entropy and entropy weight of the evaluation indicators are combined with the subjective weight of the experts to calculate the comprehensive weight of each evaluation indicator, and a comprehensive weight set is constructed to describe the importance of each evaluation indicator; wherein, i =1,2,…, m ; j =1,2,…, n ; m , n are the number of new energy power plants to be evaluated and the number of evaluation indicators; Determine a review set containing multiple review levels; calculate the value of the evaluation index Based on the membership degree of each comment level, a fuzzy evaluation matrix of each new energy power plant is obtained; Combining the comprehensive weight set and the fuzzy evaluation matrix of each new energy power plant through fuzzy synthesis operation to obtain a comprehensive evaluation set, which is used to reflect the membership distribution of the black start capability of each new energy power plant relative to all evaluation levels; The comprehensive evaluation set is normalized to obtain an evaluation of the black start capability of each renewable energy power plant.

10. The black start capability assessment method of a new energy power plant according to claim 9, characterized in that: The construction of the standardized evaluation matrix includes: Get the first i The first new energy power plant j The value of the evaluation index , construct the original evaluation matrix; According to the characteristics of each evaluation index, the original evaluation matrix is ​​standardized to obtain After standardization ,make It is a positive indicator where the larger the value, the better the performance.

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