A method and system for evaluating frequency modulation capability of a photovoltaic power station

Abstract

The application discloses a photovoltaic power station frequency modulation capability evaluation method and system, comprising: obtaining photovoltaic power station data and power system data; taking photovoltaic power station power generation power indexes, load indexes and frequency modulation indexes as evaluation elements of photovoltaic power station frequency modulation capability evaluation, so as to determine corresponding evaluation indexes under each evaluation element; determining the weights of each evaluation element and evaluation index according to the analytic hierarchy process; determining the quantitative values of each evaluation index according to the obtained photovoltaic power station data and power system data; calculating the membership degrees of the quantitative values of single evaluation indexes according to the formulated evaluation grades, so as to obtain the membership degree matrix of each evaluation element; and obtaining the comprehensive evaluation result of the photovoltaic power station frequency modulation capability according to the weights and the membership degree matrix. The method can cope with the time-varying and scattered characteristics of light resources and can meet the demand of evaluating the photovoltaic power station frequency modulation capability under different power grids.

Description

Technical Field

[0001] This invention relates to the field of electrical engineering technology, and in particular to a method and system for evaluating the frequency regulation capability of photovoltaic power plants. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] To enable photovoltaic (PV) power plants to actively support the power system, it is necessary to obtain timely information on their frequency regulation capabilities. However, solar resources are affected by geographical location and weather factors, resulting in random and fluctuating PV power generation. Furthermore, the frequency regulation capabilities of PV power plants are also influenced by external grid conditions. Therefore, it is crucial to analyze and evaluate the frequency regulation capabilities of PV power plants to meet the frequency regulation requirements under different grid conditions. Summary of the Invention

[0004] To address the aforementioned issues, this invention proposes a method and system for evaluating the frequency regulation capability of photovoltaic power plants. This method can address the time-varying stray characteristics of solar resources and meet the requirements for evaluating the frequency regulation capability of photovoltaic power plants under different power grids.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a method for evaluating the frequency regulation capability of photovoltaic power stations, comprising:

[0007] Acquire photovoltaic power plant data and power system data;

[0008] The photovoltaic power generation index, load index and frequency regulation index are used as the evaluation elements for assessing the frequency regulation capability of photovoltaic power stations, thereby determining the corresponding evaluation index under each evaluation element.

[0009] The weights of each evaluation element and indicator are determined using the analytic hierarchy process (AHP).

[0010] Based on the acquired photovoltaic power plant data and power system data, the quantitative values ​​of each evaluation indicator are determined;

[0011] Based on the established evaluation levels, the membership degree of each quantitative value of an individual evaluation indicator is calculated, thereby obtaining the membership degree matrix for each evaluation element.

[0012] The comprehensive evaluation results of the frequency regulation capability of photovoltaic power plants are obtained based on the weight and membership matrix.

[0013] As an optional implementation, the photovoltaic power generation data includes the photovoltaic power generation prediction curve, the actual photovoltaic power generation curve, the photovoltaic power generation capacity, and the photovoltaic inverter response time.

[0014] The power system data includes the power system load curve and the power system frequency curve.

[0015] As an optional implementation, the evaluation indicators under the photovoltaic power generation index include the photovoltaic power generation change rate, photovoltaic power generation prediction error, photovoltaic power generation adjustment margin, and photovoltaic power generation adjustment rate.

[0016] The evaluation indicators under the load index include the net load peak-valley difference and the actual photovoltaic grid connection rate;

[0017] The evaluation indicators under the frequency modulation index include maximum frequency deviation, adjustment response time, frequency modulation settling time and steady-state frequency deviation.

[0018] As an alternative implementation method, the process for determining the quantitative values ​​of each evaluation index includes:

[0019] The photovoltaic power generation change rate is the ratio of the change in photovoltaic power generation within one period to the installed capacity of the photovoltaic power station.

[0020] The photovoltaic power generation prediction error includes absolute error and root mean square error. The absolute error is the difference between the actual photovoltaic power generation curve and the photovoltaic power generation prediction curve, and the root mean square error is obtained from the absolute error.

[0021] The photovoltaic power generation adjustment margin is the difference between the current maximum photovoltaic output power and the initial output power;

[0022] The photovoltaic power generation regulation rate is obtained based on the photovoltaic inverter response time and the photovoltaic power station installed capacity.

[0023] The net load peak-valley difference is obtained based on the maximum / minimum net load of the power system and the maximum / minimum load of the power system.

[0024] The actual photovoltaic grid connection rate is the ratio of the actual photovoltaic output power to the load power at a certain time.

[0025] The maximum frequency deviation is the difference between the peak frequency and the rated frequency;

[0026] The adjustment response time is the difference between the peak time and the disturbance time;

[0027] The frequency modulation settling time is the difference between the steady-state moment and the peak moment;

[0028] The steady-state frequency deviation is the difference between the steady-state frequency and the rated frequency.

[0029] As an alternative implementation, the root mean square error e R for: Among them, e hLet N be the absolute error and N be the number of predictions.

[0030] As an alternative implementation, the photovoltaic power generation regulation rate P s for: Where ε is the response time of the photovoltaic inverter, P B This refers to the installed capacity of photovoltaic power stations.

[0031] As an alternative implementation method, the net load peak-to-valley difference τ is:

[0032] τ=(max(P net )-in(P net ))-(max(P load )-min(P load ))

[0033] Where max(P) net ) and min(P net ) represent the maximum and minimum net load values ​​of the power system, respectively; max(P load ) and min(P load ) represent the maximum and minimum values ​​of the power system load, respectively.

[0034] As an alternative implementation method, the comprehensive evaluation process for the frequency regulation capability of photovoltaic power plants includes:

[0035] For photovoltaic power station m, calculate F for each evaluation element. * Comprehensive fuzzy evaluation set

[0036]

[0037] in, This represents the weight vector of the evaluation indicators; For evaluation element F * The membership matrix;

[0038] The comprehensive fuzzy evaluation set S of photovoltaic power station m m for:

[0039] S m =·[S F1 S F2 S F3 ] T

[0040] Where W is the weight vector of the evaluation elements; S F1 S F2 S F3 For each evaluation element, a comprehensive fuzzy evaluation set is provided.

[0041] Fuzzy evaluation score N of photovoltaic power station m mfor:

[0042] N m = m · T

[0043] Where E is the score set based on the established evaluation levels.

[0044] Secondly, the present invention provides a photovoltaic power station frequency regulation capability assessment system, comprising:

[0045] The data acquisition module is configured to acquire photovoltaic power plant data and power system data;

[0046] The indicator determination module is configured to use photovoltaic power generation indicators, load indicators and frequency regulation indicators as evaluation elements for assessing the frequency regulation capability of photovoltaic power stations, thereby determining the corresponding evaluation indicators for each evaluation element.

[0047] The weight determination module is configured to determine the weights of each evaluation element and indicator based on the analytic hierarchy process (AHP).

[0048] The quantitative indicator module is configured to determine the quantitative values ​​of each evaluation indicator based on the acquired photovoltaic power plant data and power system data.

[0049] The membership determination module is configured to calculate the membership degree of a single evaluation indicator based on the established evaluation level, thereby obtaining the membership degree matrix for each evaluation element.

[0050] The comprehensive evaluation module is configured to obtain a comprehensive evaluation result of the frequency regulation capability of photovoltaic power plants based on the weight and membership matrix.

[0051] Thirdly, the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0052] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in the first aspect.

[0053] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0054] To address the challenge of assessing the frequency regulation capability of photovoltaic (PV) power plants, this invention proposes a method and system for evaluating PV power plant frequency regulation capability. The system establishes a hierarchical structure comprising a target layer, an element layer, and an indicator layer, and determines the weights of the element layer and the indicator layer using the analytic hierarchy process (AHP). Quantitative values ​​for each evaluation indicator are determined using acquired PV power plant data and power system data. A scoring standard for assessing the frequency regulation capability of PV power plants is established, and single-factor evaluations and membership degree calculations are performed based on this standard, thereby completing a comprehensive assessment of the frequency regulation capability of PV power plants. This method can address the time-varying stray characteristics of solar resources and meets the needs of assessing the frequency regulation capability of PV power plants under different power grid conditions.

[0055] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0056] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0057] Figure 1 This is a flowchart of the photovoltaic power station frequency regulation capability assessment method provided in Embodiment 1 of the present invention. Detailed Implementation

[0058] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0059] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0060] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0061] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0062] Example 1

[0063] This embodiment provides a method for evaluating the frequency regulation capability of photovoltaic power stations, such as... Figure 1 As shown, it includes:

[0064] Acquire data from photovoltaic power plants and power systems;

[0065] The photovoltaic power generation index, load index and frequency regulation index are used as the evaluation elements for assessing the frequency regulation capability of photovoltaic power stations, thereby determining the corresponding evaluation index under each evaluation element.

[0066] The weights of each evaluation element and indicator are determined using the analytic hierarchy process (AHP).

[0067] Based on the acquired photovoltaic power plant data and power system data, the quantitative values ​​of each evaluation indicator are determined;

[0068] Based on the established evaluation levels, the membership degree of each quantitative value of an individual evaluation indicator is calculated, thereby obtaining the membership degree matrix for each evaluation element.

[0069] The comprehensive evaluation results of the frequency regulation capability of photovoltaic power plants are obtained based on the weight and membership matrix.

[0070] In this embodiment, the acquired photovoltaic power generation data includes: photovoltaic power generation prediction curve, photovoltaic power generation actual curve, photovoltaic power generation capacity, and photovoltaic inverter response time;

[0071] The acquired power system data includes: the power system load curve and the power system frequency curve.

[0072] In this embodiment, a hierarchical structure for evaluating the frequency regulation capability of photovoltaic power plants is constructed, including a target layer T, an element layer F, and an index layer K;

[0073] Among them, the target layer T is the assessment of the frequency regulation capability of photovoltaic power stations;

[0074] The element layer F includes three evaluation elements: photovoltaic power generation index F1, load index F2, and frequency regulation index F3.

[0075] The indicator layer K includes various evaluation indicators corresponding to the three evaluation elements;

[0076] Specifically:

[0077] The photovoltaic power generation index F1 includes: photovoltaic power generation change rate K1, photovoltaic power generation prediction error K2, photovoltaic power generation adjustment margin K3, and photovoltaic power generation adjustment rate K4;

[0078] The load index F2 includes: net load peak-to-valley difference K5 and actual photovoltaic grid connection rate K6;

[0079] The frequency modulation index F3 includes: maximum frequency deviation K7, adjustment response time K8, frequency modulation settling time K9, and steady-state frequency deviation K. 10 .

[0080] In this embodiment, the process of determining the weights of each evaluation element and indicator according to the analytic hierarchy process includes:

[0081] (1) Construct the judgment matrix;

[0082] Based on the expert panel's opinions, a judgment matrix S was constructed by determining the relative importance of each evaluation element;

[0083] Among them, the elements s in the judgment matrix ij The importance of the element in the i-th row relative to the element in the j-th column is indicated. Obviously, the judgment matrix S is an orthogonal matrix, with the elements on the diagonal being 1 and the elements on both sides of the diagonal being reciprocals of each other. Therefore, the judgment matrix S can be determined by comparing each evaluation element n(n-1) / 2 times.

[0084] (2) Multiply the elements of each row in the judgment matrix:

[0085]

[0086] In the formula, n represents the number of evaluation elements.

[0087] (3) Calculate F for each evaluation element i weight w i :

[0088]

[0089] (4) Consistency is verified by calculating the consistency index CI:

[0090]

[0091] To verify the consistency of the judgment matrix, an average random consistency index RI is introduced. When the consistency ratio CR = CI / RI < 0.1, the consistency test of the judgment matrix is ​​considered to have passed. Otherwise, the judgment matrix is ​​readjusted until the consistency test is passed.

[0092] Therefore, the weight vector of the element layer is W = [w1, w2, w3].

[0093] Similarly, the weights of each evaluation index can be obtained, thus yielding the weight vectors WF1, WF2, and WF3 for the index layer.

[0094] In this embodiment, the process of determining the quantitative values ​​of each evaluation index based on the acquired photovoltaic power plant data and power system data includes:

[0095] For different photovoltaic power stations m, the corresponding index K n Represented as x mn n = 1, 2, ... 10;

[0096] Specifically:

[0097] (1) Rate of change of photovoltaic power generation; Photovoltaic power generation is volatile and uncertain. Fluctuations in solar irradiance will cause photovoltaic power generation to fluctuate accordingly, which may cause system active power imbalance. Therefore, the rate of change of photovoltaic power generation is an important factor affecting the system frequency regulation capability.

[0098] The photovoltaic power generation change rate γ% is:

[0099]

[0100] In the formula, ΔP p P represents the change in photovoltaic power generation over one period. B This refers to the installed capacity of the photovoltaic power station.

[0101] (2) Photovoltaic power generation prediction error; Due to the randomness of photovoltaic power generation, the predicted value is not the same as the actual value, and there is an error between them.

[0102] The photovoltaic power generation prediction error is:

[0103]

[0104] In the formula, e h For absolute error; f h For the actual data sequence; f′ h For predicting data sequences; e R denoted as root mean square error; N represents the number of predictions.

[0105] (3) The photovoltaic power generation regulation margin can reflect the maximum regulation capability of the photovoltaic power station to participate in the system frequency regulation. The larger the photovoltaic power generation regulation margin, the smaller the steady-state deviation of the system frequency.

[0106] Photovoltaic power generation regulation margin P r for:

[0107] P r =P pmax -P O

[0108] In the formula, P pmax P represents the maximum output power of the photovoltaic system under the current weather conditions. O This represents the initial output power.

[0109] (4) Photovoltaic power generation regulation rate, which is the maximum output power change of a photovoltaic power station per unit time; the faster the photovoltaic power generation regulation rate, the faster the system frequency can recover to steady state, which helps the power system to operate safely and stably.

[0110] Photovoltaic power generation regulation rate P S The value is closely related to the performance of the inverter and is:

[0111]

[0112] In the formula, ε is the inverter's response time, which is equal to the time it takes for the inverter's output power to reach 90% of the set value; P B This refers to the installed capacity of photovoltaic power stations.

[0113] (5) Net load peak-valley difference, i.e. load minus photovoltaic power generation; the randomness and volatility of photovoltaic power generation means that the net load also has randomness and volatility.

[0114] The net load peak-to-valley difference τ is:

[0115]

[0116] In the formula, max(P) net ) and min(P net ) represent the maximum / minimum net load of the system; max(P) load ) and min(P load () represent the maximum and minimum system loads, respectively.

[0117] (6) Actual photovoltaic grid connection rate; By analyzing the photovoltaic output power, it is assessed whether the system needs to change its frequency regulation capacity; The actual photovoltaic grid connection rate β is:

[0118]

[0119] In the formula, P p P represents the actual output power of the photovoltaic system at a certain moment. load The load power at a certain moment.

[0120] (7) Maximum frequency deviation Δf max for:

[0121] Δf max =f m -f N

[0122] In the formula, f m f is the peak frequency; N The table shows the rated frequency.

[0123] (8) Adjusting the response time t Rfor:

[0124] t R =t m -t d

[0125] In the formula, t m The peak time; t d This represents the moment of disturbance.

[0126] (9) Frequency modulation settling time t S for:

[0127] t S =t s -t m

[0128] In the formula, t s This represents the steady-state moment.

[0129] (10) Steady-state frequency deviation Δf s for:

[0130] Δf s =f s -f N

[0131] In the formula, f s This is the steady-state frequency.

[0132] In this embodiment, an evaluation level for the frequency regulation capability assessment of photovoltaic power stations is established, and the evaluation results are divided into four levels: excellent, good, medium and poor. Therefore, the evaluation set for the frequency regulation capability assessment of photovoltaic power stations is V = [V1, V2, V3, V4], and the corresponding score set is E = [10, 7, 4, 1].

[0133] Calculate the membership degree of a single evaluation index based on its quantitative value; for a photovoltaic power station m, the corresponding membership degree matrix is ​​R. mn ={r mn_V1 ,r mn_V2 ,r mn_V3 ,r mn_V4}, where r mn_V* The quantitative value x represents the evaluation index. mn Belongs to evaluation V * (V * The membership degree of ∈[V1V2V3V4]);

[0134] The membership matrix for each evaluation element is as follows:

[0135] Membership matrix of photovoltaic power generation indicators: R m_F1 =[R m1 ,R m2 ,R m3 ,R m4 ]T ;

[0136] Membership matrix of load index: R m_F2 =[R m5 ,R m6 ] T ;

[0137] Membership matrix of frequency modulation index: R m_F3 =[R m7 ,R m8 ,R m9 ,R m10 ] T ;

[0138] The membership matrix of the target layer is R. m =[R m_F1 ,R m_F2 ,R m_F3 ] T .

[0139] In this embodiment, the process of obtaining the comprehensive evaluation result of the frequency regulation capability of the photovoltaic power station based on the weight and membership matrix includes:

[0140] (1) For photovoltaic power station m, calculate F for each evaluation element. * (F * The comprehensive fuzzy evaluation set ∈ [F1F2F3]):

[0141]

[0142] in, This represents the weight vector of the evaluation indicators;

[0143] (2) The comprehensive fuzzy evaluation set of photovoltaic power station m is:

[0144] S m =W·[S F1 S F2 S F3 ] T

[0145] Where W is the weight vector of the evaluation elements;

[0146] (3) The fuzzy evaluation score of photovoltaic power station m is:

[0147] N m =S m ·E T .

[0148] This embodiment addresses the difficulty in assessing the frequency regulation capability of photovoltaic power plants by designing a method for assessing the frequency regulation capability of photovoltaic power plants. This method can address the time-varying stray characteristics of solar resources and meet the needs of assessing the frequency regulation capability of photovoltaic power plants under different power grids.

[0149] Example 2

[0150] This embodiment provides a photovoltaic power station frequency regulation capability assessment system, including:

[0151] The data acquisition module is configured to acquire photovoltaic power plant data and power system data;

[0152] The indicator determination module is configured to use photovoltaic power generation indicators, load indicators and frequency regulation indicators as evaluation elements for assessing the frequency regulation capability of photovoltaic power stations, thereby determining the corresponding evaluation indicators for each evaluation element.

[0153] The weight determination module is configured to determine the weights of each evaluation element and indicator based on the analytic hierarchy process (AHP).

[0154] The quantitative indicator module is configured to determine the quantitative values ​​of each evaluation indicator based on the acquired photovoltaic power plant data and power system data.

[0155] The membership determination module is configured to calculate the membership degree of a single evaluation indicator based on the established evaluation level, thereby obtaining the membership degree matrix for each evaluation element.

[0156] The comprehensive evaluation module is configured to obtain a comprehensive evaluation result of the frequency regulation capability of photovoltaic power plants based on the weight and membership matrix.

[0157] It should be noted that the above modules correspond to the steps described in Embodiment 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0158] In further embodiments, the following is also provided:

[0159] An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0160] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0161] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0162] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0163] The method in Example 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0164] Those skilled in the art will recognize that the units, i.e., algorithm steps, of the various examples described in connection with this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0165] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for evaluating the frequency regulation capability of photovoltaic power plants, characterized in that, include: Acquire data from photovoltaic power plants and power systems; The photovoltaic power generation index, load index, and frequency regulation index are used as the evaluation elements for assessing the frequency regulation capability of photovoltaic power stations, thereby determining the corresponding evaluation index under each evaluation element. The evaluation indicators under the photovoltaic power generation index include the photovoltaic power generation change rate, photovoltaic power generation prediction error, photovoltaic power generation adjustment margin, and photovoltaic power generation adjustment rate. The evaluation indicators under the load index include the net load peak-valley difference and the actual photovoltaic grid connection rate; The evaluation indicators under the frequency modulation index include maximum frequency deviation, adjustment response time, frequency modulation settling time and steady-state frequency deviation; The weights of each evaluation element and indicator are determined using the analytic hierarchy process (AHP). Based on the acquired photovoltaic power plant data and power system data, the quantitative values ​​of each evaluation indicator are determined; Based on the established evaluation levels, the membership degree of each quantitative value of an individual evaluation indicator is calculated, thereby obtaining the membership degree matrix for each evaluation element. The comprehensive evaluation results of the frequency regulation capability of photovoltaic power plants are obtained based on the weight and membership matrix.

2. The method for evaluating the frequency regulation capability of a photovoltaic power station as described in claim 1, characterized in that, The photovoltaic power generation data includes the photovoltaic power generation prediction curve, the actual photovoltaic power generation curve, the photovoltaic power generation capacity, and the photovoltaic inverter response time. The power system data includes the power system load curve and the power system frequency curve.

3. The method for evaluating the frequency regulation capability of a photovoltaic power station as described in claim 1, characterized in that, The process of determining the quantitative values ​​of each evaluation indicator includes: The photovoltaic power generation change rate is the ratio of the change in photovoltaic power generation within one period to the installed capacity of the photovoltaic power station. The photovoltaic power generation prediction error includes absolute error and root mean square error. The absolute error is the difference between the actual photovoltaic power generation curve and the photovoltaic power generation prediction curve, and the root mean square error is obtained from the absolute error. The photovoltaic power generation adjustment margin is the difference between the current maximum photovoltaic output power and the initial output power; The photovoltaic power generation regulation rate is obtained based on the photovoltaic inverter response time and the photovoltaic power station installed capacity. The net load peak-valley difference is obtained based on the maximum / minimum net load of the power system and the maximum / minimum load of the power system. The actual photovoltaic grid connection rate is the ratio of the actual photovoltaic output power to the load power at a certain time. The maximum frequency deviation is the difference between the peak frequency and the rated frequency; The adjustment response time is the difference between the peak time and the disturbance time; The frequency modulation settling time is the difference between the steady-state moment and the peak moment; The steady-state frequency deviation is the difference between the steady-state frequency and the rated frequency.

4. The method for evaluating the frequency regulation capability of a photovoltaic power station as described in claim 3, characterized in that, The root mean square error for: ;in, For absolute error, N For the number of predictions.

5. The method for evaluating the frequency regulation capability of a photovoltaic power station as described in claim 3, characterized in that, The photovoltaic power generation regulation rate for: ;in, For the response time of the photovoltaic inverter, For the installed capacity of photovoltaic power stations; The peak-to-valley difference of net load for: in, and These are the maximum and minimum values ​​of the net load of the power system, respectively. and These represent the maximum and minimum values ​​of the power system load, respectively.

6. The method for evaluating the frequency regulation capability of a photovoltaic power station as described in claim 1, characterized in that, The comprehensive evaluation process for the frequency regulation capability of photovoltaic power plants includes: For photovoltaic power stations m Calculate each evaluation element Comprehensive fuzzy evaluation set : in, This represents the weight vector of the evaluation indicators; For evaluation elements The membership matrix; Comprehensive fuzzy evaluation set of photovoltaic power station m for: in, The weight vector for evaluating the elements; For each evaluation element, a comprehensive fuzzy evaluation set is provided. Fuzzy evaluation score of photovoltaic power station m for: in, This is based on the score set in the established assessment levels.

7. A system for evaluating the frequency regulation capability of photovoltaic power plants, characterized in that, include: The data acquisition module is configured to acquire photovoltaic power plant data and power system data; The indicator determination module is configured to use photovoltaic power generation indicators, load indicators, and frequency regulation indicators as evaluation elements for assessing the frequency regulation capability of photovoltaic power stations, thereby determining the corresponding evaluation indicators for each evaluation element. The evaluation indicators under the photovoltaic power generation index include the photovoltaic power generation change rate, photovoltaic power generation prediction error, photovoltaic power generation adjustment margin, and photovoltaic power generation adjustment rate. The evaluation indicators under the load index include the net load peak-valley difference and the actual photovoltaic grid connection rate; The evaluation indicators under the frequency modulation index include maximum frequency deviation, adjustment response time, frequency modulation settling time and steady-state frequency deviation; The weight determination module is configured to determine the weights of each evaluation element and indicator based on the analytic hierarchy process (AHP). The quantitative indicator module is configured to determine the quantitative values ​​of each evaluation indicator based on the acquired photovoltaic power plant data and power system data. The membership determination module is configured to calculate the membership degree of a single evaluation indicator based on the established evaluation level, thereby obtaining the membership degree matrix for each evaluation element. The comprehensive evaluation module is configured to obtain a comprehensive evaluation result of the frequency regulation capability of photovoltaic power plants based on the weight and membership matrix.

8. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, perform the method described in any one of claims 1-6.

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