Frequency support capability evaluation method and device for new energy stations based on output characteristics

Abstract

The present invention provides a method and device for evaluating the frequency support capability of a new energy station based on output characteristics, which is mainly used in the field of power grid dispatching technology. Specifically, the method for evaluating the frequency support capability of a new energy station includes: in response to a frequency support capability evaluation request for a first target station, when the first target station does not participate in frequency modulation, a frequency support capability test is performed on the first target station to obtain the test results of each of the multiple evaluation sub-factors of the first target station; based on the test results of each of the multiple evaluation sub-factors, a membership matrix of the first target station is constructed; based on the active power data of each of the multiple stations in the historical period, the evaluation weights of each of the multiple evaluation factors are obtained; based on the preset weights of each of the multiple evaluation sub-factors, the evaluation weights of each of the multiple evaluation factors and the membership matrix, the frequency support capability evaluation result of the first target station is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid dispatching, and more specifically, to a method and device for evaluating the frequency support capability of a new energy station based on output characteristics. Background Art

[0002] With the rapid development of new energy technologies in recent years, the power system has gradually become dominated by renewable energy such as wind power and solar energy. However, with the continuous increase in the capacity of new energy grid connection, the power system faces severe frequency security issues.

[0003] In order to make up for the insufficient frequency regulation capability of the power grid caused by the access of new energy, the power grid requires that new energy stations must have a certain frequency support capability when connected to the grid. However, the control strategy and implementation method of the existing technology for providing frequency support for new energy stations are currently unable to quantitatively evaluate the frequency support capability of new energy stations; in addition, when building a frequency support capability evaluation system, a large amount of operating data needs to be collected. However, these data may come from different monitoring systems and sensors, and there are problems with inconsistent data formats, sampling frequencies and accuracy, which increases the complexity and difficulty of data processing. Summary of the invention

[0004] In view of this, the present invention provides a method and device for evaluating the frequency support capability of a new energy station based on output characteristics.

[0005] One aspect of the present invention provides a method for evaluating the frequency support capability of a new energy station based on output characteristics, comprising: in response to a frequency support capability evaluation request for a first target station, performing a frequency support capability test on the first target station when the first target station does not participate in frequency modulation, and obtaining test results of multiple evaluation sub-factors of the first target station; constructing a membership matrix of the first target station based on the test results of the multiple evaluation sub-factors; obtaining evaluation weights of the multiple evaluation factors based on active power data of the multiple stations in historical time periods; obtaining frequency support capability evaluation results of the first target station based on the preset weights of the multiple evaluation sub-factors, the evaluation weights of the multiple evaluation factors and the membership matrix.

[0006] Another aspect of the present invention provides a frequency support capability evaluation device for a new energy station based on output characteristics, including: a testing module, for responding to a frequency support capability evaluation request for a first target station, and performing a frequency support capability test on the first target station when the first target station does not participate in frequency modulation, to obtain test results of each of the multiple evaluation sub-factors of the first target station; a construction module, for constructing a membership matrix of the first target station based on the test results of each of the multiple evaluation sub-factors; a weight determination module, for obtaining evaluation weights of each of the multiple evaluation factors based on active power data of each of the multiple stations in a historical period; and a result determination module, for obtaining a frequency support capability evaluation result of the first target station based on the preset weights of each of the multiple evaluation sub-factors, the evaluation weights of each of the multiple evaluation factors and the membership matrix.

[0007] According to an embodiment of the present invention, by comprehensively considering multiple frequency support capability evaluation indicators, the frequency support capability of a new energy station is comprehensively and accurately evaluated; by constructing a membership matrix of the new energy station and the evaluation weights of multiple evaluation factors, the test results of each evaluation sub-factor are quantified, thereby more accurately reflecting the frequency support capability of the station; the frequency support capability evaluation results obtained based on the membership matrix of the new energy station and the evaluation weights of multiple evaluation factors can provide a basis for the dispatching management of the new energy station during the grid connection process of the new energy station, so as to ensure the frequency stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0009] Figure 1 A flow chart of a method for evaluating frequency support capability of a new energy station based on output characteristics according to an embodiment of the present invention is shown.

[0010] Figure 2 A flow chart of a method for determining evaluation weights of respective evaluation factors in a wind farm station according to an embodiment of the present invention is shown.

[0011] Figure 3 A flow chart of a method for determining evaluation weights of respective evaluation factors in a photovoltaic power generation station according to an embodiment of the present invention is shown.

[0012] Figure 4 A schematic diagram of a low-frequency disturbance device according to an embodiment of the present invention is shown.

[0013] Figure 5 A block diagram of a device for evaluating frequency support capability of a new energy station based on output characteristics according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0014] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

[0015] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0016] With the rapid development of new energy technologies in recent years, the construction of a new power system based on renewable energy such as wind and solar energy not only represents a profound transformation of the energy structure, but also heralds a comprehensive innovation in the operation and management of the power system. However, with the continuous increase in the capacity of new energy grid connection, the power system faces severe frequency security issues.

[0017] Due to the volatility, intermittency and unpredictability of renewable energy generation, it is difficult for the power grid to maintain a stable frequency level under the high penetration rate of renewable energy. When the output of renewable energy generation suddenly decreases or the load demand suddenly increases, the frequency of the power grid may drop rapidly. If it cannot be effectively adjusted in time, it may cause frequency stability accidents, posing a serious threat to the safe and stable operation of the power system.

[0018] In order to make up for the insufficient frequency regulation capability of the power grid caused by the access of new energy, the power grid requires that new energy stations must have a certain frequency support capability when connected to the grid. This means that new energy stations must not only be able to generate electricity stably, but also be able to respond quickly when the power grid frequency fluctuates, and assist the power grid in maintaining a stable frequency level by adjusting the output characteristics of new energy stations.

[0019] However, most of the existing technologies mainly focus on the control strategies and implementation methods for providing frequency support for new energy stations, and are unable to quantitatively evaluate the frequency support capabilities of new energy stations. In addition, when building a frequency support capability evaluation system, a large amount of operating data needs to be collected. However, these data may come from different monitoring systems and sensors, and there are problems with data formats, sampling frequencies and accuracy inconsistencies, which increases the complexity and difficulty of data processing.

[0020] In view of this, the embodiments of the present invention comprehensively and accurately evaluate the frequency support capability of a new energy station by comprehensively considering multiple frequency support capability evaluation indicators; quantify the test results of each evaluation sub-factor by constructing a membership matrix of the new energy station and the evaluation weights of multiple evaluation factors, thereby more accurately reflecting the frequency support capability of the station; the frequency support capability evaluation results obtained based on the membership matrix of the new energy station and the evaluation weights of multiple evaluation factors can provide a basis for the dispatching management of the new energy station during the grid connection process of the new energy station, so as to ensure the frequency stability of the power grid.

[0021] Specifically, an embodiment of the present invention provides a method for evaluating the frequency support capability of a new energy station based on output characteristics, including: in response to a frequency support capability evaluation request for a first target station, performing a frequency support capability test on the first target station when the first target station does not participate in frequency modulation, and obtaining test results of multiple evaluation sub-factors of the first target station; constructing a membership matrix of the first target station based on the test results of each of the multiple evaluation sub-factors; obtaining evaluation weights of each of the multiple evaluation factors based on the active power data of each of the multiple stations in a historical period; and obtaining a frequency support capability evaluation result of the first target station based on the preset weights of each of the multiple evaluation sub-factors, the evaluation weights of each of the multiple evaluation factors and the membership matrix.

[0022] Figure 1 A flow chart of a method for evaluating frequency support capability of a new energy station based on output characteristics according to an embodiment of the present invention is shown.

[0023] like Figure 1 As shown, the method includes operations S101 to S104.

[0024] In operation S101, in response to a frequency support capability evaluation request for a first target station, a frequency support capability test is performed on the first target station when the first target station does not participate in frequency modulation, and test results of multiple evaluation sub-factors of the first target station are obtained.

[0025] According to an embodiment of the present invention, the first target station can be used to characterize a new energy power station such as a wind farm, a photovoltaic power plant, etc. The evaluation index of the frequency support capability of the first target station includes multiple evaluation factors, each of which includes multiple evaluation sub-factors.

[0026] Specifically, in one embodiment of the present invention, if the first target station is a wind farm station, its evaluation factors may include frequency adaptability, inertia response capability, and frequency response capability. Among them, the frequency adaptability evaluation factor may include evaluation sub-factors such as low-frequency ride-through capability, continuous operation capability, and high-frequency ride-through capability. The inertia response capability evaluation factor may include evaluation sub-factors such as steady-state deviation of active power variation and rise time of active power variation. The frequency response capability evaluation factor may include evaluation sub-factors such as steady-state deviation of active power variation, lag time of active power variation, rise time of active power variation, and adjustment time of active power variation. Among them, the frequency adaptability of the wind farm refers to the function of the wind farm to continuously operate stably without disconnecting from the grid after the power system frequency exceeds the dead zone. The inertia response capability of the wind farm refers to the function of the wind farm to quickly adjust its own active power in response to the system frequency change rate when the power system frequency changes rapidly. The frequency response capability of the wind farm refers to the function of the wind farm to quickly adjust its own active power in response to the system frequency deviation when the power system frequency deviates from the rated value.

[0027] In another embodiment of the present invention, if the first target station is a photovoltaic power station, its evaluation factors may include frequency adaptability and frequency response capability. Frequency adaptability evaluation factors may include low-frequency ride-through capability, continuous operation capability, high-frequency ride-through capability, rate of change ride-through capability and other evaluation sub-factors. Frequency response capability evaluation factors may include active power change steady-state deviation, active power change lag time, active power change rise time, active power change adjustment time and other evaluation sub-factors. Among them, the frequency adaptability of a photovoltaic power station refers to the function of a photovoltaic power station being able to operate stably and continuously without disconnecting from the grid after the power system frequency exceeds the dead zone. The frequency response capability of a photovoltaic power station refers to the function of a photovoltaic power station to quickly adjust its own active power in response to the system frequency deviation when the power system frequency deviates from the rated value.

[0028] According to an embodiment of the present invention, when the renewable energy power station does not participate in frequency modulation, a low-frequency disturbance device can be installed on the high-voltage side of the step-up transformer of the renewable energy station, and the low-frequency disturbance device can be used to send out excitation signals such as frequency deviation and frequency change rate, so as to collect remote signaling and telemetry signals such as the operating status and active power change of the renewable energy station, so as to test the frequency support capability of the renewable energy power station and obtain the test results of the frequency support capability evaluation index of the renewable energy power station.

[0029] In operation S102, a membership matrix of the first target site is constructed based on the test results of each of the plurality of evaluation sub-factors.

[0030] According to an embodiment of the present invention, in the process of quantifying the test results of each of the multiple evaluation sub-factors, a membership matrix of a new energy power generation station can be constructed based on a multi-level fuzzy comprehensive evaluation method. The membership matrix can be used to reflect the degree of membership of each evaluation sub-factor relative to different evaluation levels. For example, each row of the membership matrix can be used to represent an evaluation sub-factor, and each column of the membership matrix can be used to represent an evaluation level.

[0031] In operation S103, evaluation weights of respective evaluation factors are obtained based on active power data of respective multiple stations in a historical period.

[0032] According to an embodiment of the present invention, the plurality of stations include a first target station and a plurality of second target stations, and the second target stations include new energy stations of the same type as the first target stations and located in the same area.

[0033] Specifically, before determining the evaluation weights of each of the multiple evaluation factors, it is necessary not only to obtain the active power data of the first target station, i.e., the new energy power station that needs to undergo the frequency support capability test, in the historical period, but also to obtain the active power data of one or more other new energy power stations located in the same area as the new energy power station in the historical period. The first target station is of the same type as the second target station. For example, when the first target station is a wind farm, the second target station is also one or more other wind farms located in the same area as the wind farm.

[0034] According to the embodiment of the present invention, since different new energy sites will show different characteristics in the frequency support capability evaluation index, different new energy sites will show different emphasis in responding to the "frequency adaptability demand", "inertia response demand" and "frequency response demand" of the power grid. Therefore, when the active power data of multiple sites in their respective historical periods are obtained, the analysis method based on the output characteristics of new energy can be used, but is not limited to, to obtain the evaluation weights of multiple evaluation factors.

[0035] For example, an analysis method based on the output characteristics of renewable energy can be used. Based on the active power data of multiple stations in the region in historical periods, the output characteristics such as the peak simultaneous output rate of renewable energy output, the change rate of simultaneous output rate, and the simultaneous output rate of peak power consumption in the morning and evening can be obtained to determine the role of the renewable energy station in supporting the frequency of the regional power grid, thereby comprehensively determining the evaluation weights of multiple evaluation factors.

[0036] In operation S104, based on the preset weights of the plurality of evaluation sub-factors, the evaluation weights of the plurality of evaluation factors, and the membership matrix, a frequency support capability evaluation result of the first target site is obtained.

[0037] According to an embodiment of the present invention, the preset weights of the plurality of evaluation sub-factors can be determined by, but are not limited to, empirical judgment methods. Specifically, the possibility of occurrence of these events in actual operation can be evaluated by identifying events related to each evaluation sub-factor. In this case, a corresponding weight can be assigned to each evaluation sub-factor based on the possibility of occurrence of the event corresponding to each evaluation sub-factor in the actual operation of the power system, that is, the more "high" the importance of a certain evaluation factor to the power grid dispatching organization, the greater the weight assigned to the evaluation factor.

[0038] In addition, analysis can also be performed based on the operating status of multiple sites, external environmental factors (such as weather, changes in load demand, etc.), and the characteristics of renewable energy power generation sites to obtain the evaluation weights of multiple evaluation sub-factors.

[0039] According to an embodiment of the present invention, the frequency support capability evaluation result of the first target station can be determined based on the evaluation results of each of the multiple evaluation factors. The evaluation results of each of the multiple evaluation factors can be determined based on the evaluation weights of each of the multiple evaluation factors and the weighted membership of each evaluation sub-factor. The weighted membership of each evaluation sub-factor can be determined based on the preset weight and membership matrix of the evaluation sub-factor. The evaluation weights of each of the multiple evaluation factors can be determined based on the active power data of each of the multiple stations in the historical period.

[0040] According to an embodiment of the present invention, the frequency support capability evaluation result of the first target site may be in the form of a specific numerical value, such as a specific score, or a fuzzy evaluation level such as excellent, good, medium, poor, etc.

[0041] According to an embodiment of the present invention, the frequency support capability evaluation result of the first target station can be used to reasonably allocate grid frequency modulation resources. For example, when the grid frequency fluctuates, the grid dispatching center gives priority to calling stations with stronger frequency support capabilities for frequency modulation to ensure the stability of the grid frequency. In addition, the frequency support capability evaluation result can also be used to provide a basis for optimizing the operation strategy of the grid. For example, in areas where a high proportion of new energy sources such as wind power and photovoltaics are connected to the grid, the grid connection strategy of new energy can be adjusted according to the frequency support capability of the station to reduce the impact on the grid frequency.

[0042] Based on this, the embodiments of the present invention comprehensively and accurately evaluate the frequency support capability of new energy stations by comprehensively considering multiple frequency support capability evaluation indicators; quantify the test results of each evaluation sub-factor by constructing a membership matrix of new energy stations and the evaluation weights of multiple evaluation factors, thereby more accurately reflecting the frequency support capability of the station; the frequency support capability evaluation results obtained based on the membership matrix of new energy stations and the evaluation weights of multiple evaluation factors can provide a basis for the dispatching management of new energy stations during the grid connection process of new energy stations to ensure the frequency stability of the power grid.

[0043] Figure 2 A flow chart of a method for determining evaluation weights of respective evaluation factors in a wind farm station according to an embodiment of the present invention is shown.

[0044] like Figure 2 As shown, the method includes operations S201 to S205.

[0045] In operation S201, based on active power data of each of the multiple stations, a time series of output simultaneity rates of each of the multiple stations is obtained.

[0046] According to an embodiment of the present invention, when the first target site includes a wind farm to be evaluated, the output simultaneity time series of each site is calculated based on multiple active power data of the wind farm to be evaluated and other second target sites in a historical period, such as nearly one year. The output simultaneity refers to the ratio of the actual active power generated by the site at a certain point in time to its installed capacity.

[0047] In operation S202, a first sequence value is determined based on a change rate of a sequence element in a time series of output simultaneity rates of each of a plurality of stations.

[0048] According to an embodiment of the present invention, the output simultaneity rate of each sequence element is extracted from the output simultaneity rate time series of multiple stations in the past year, and the output simultaneity rate change rate between multiple adjacent sequence elements is calculated. The output simultaneity rate change rates between multiple adjacent sequence elements are sorted to obtain the first sequence value of the wind farm to be evaluated.

[0049] According to an embodiment of the present invention, multiple output simultaneity rate change rates can be used to reflect the volatility of the output power of the station. The first sequence value can be used to represent the output simultaneity rate change rate value corresponding to the ranking order of the wind farm to be evaluated. The sequence elements in the output simultaneity rate time series can be represented as multiple time points.

[0050] In operation S203, a second sequence value is determined based on a subsequence corresponding to the first peak period in the output simultaneity time series of each of the plurality of stations.

[0051] According to an embodiment of the present invention, a subsequence of the output simultaneity rate of each station in the first peak period is extracted from the output simultaneity rate time series of each of the multiple stations. Then, the subsequences of the output simultaneity rate of the multiple stations in the first peak period are sorted to obtain a second order value of the wind farm to be evaluated.

[0052] According to an embodiment of the present invention, the first peak period may be represented as a period that meets the first power generation resource threshold, such as 0:00-7:00 every day in the past year.

[0053] According to an embodiment of the present invention, the second order value may be used to represent the output simultaneity value corresponding to the ranking order of the wind farm to be evaluated in the first peak period.

[0054] In operation S204, a third order value is determined based on the sampling values ​​in the second peak period in the output simultaneity time series of each of the plurality of stations.

[0055] According to an embodiment of the present invention, the output simultaneity time series of each wind farm is sampled to extract the sampling value in the second peak period. Based on the sampling value in the second peak period, multiple farms are sorted to determine the relative position of the farm to be evaluated among all the farms, and the third order value of the wind farm to be evaluated is obtained.

[0056] According to an embodiment of the present invention, the second peak period may be represented as a period that meets the second power generation resource threshold, such as 16:00-21:00 in a day.

[0057] According to an embodiment of the present invention, the third order value may be used to represent the output simultaneity value corresponding to the ranking order of the wind farm to be evaluated in the second peak period.

[0058] In operation S205 , evaluation weights of respective evaluation factors are obtained based on the first ordinal value, the second ordinal value, and the third ordinal value.

[0059] According to an embodiment of the present invention, based on the first ordinal value, the second ordinal value and the third ordinal value, methods such as weighted average and median sorting are used to determine the evaluation weights of the multiple evaluation factors of the wind farm to be evaluated.

[0060] Based on this, the embodiments of the present invention can evaluate the volatility of the output power of the wind farm to be evaluated by quantifying the rate of change of the output simultaneity rate, so as to ensure the operating stability of the farm; in addition, by calculating the output simultaneity rate subsequences and sampling values ​​of the first peak period and the second peak period, the power generation capacity of the wind farm to be evaluated in the critical period can be identified, thereby determining the importance of different evaluation weights in evaluating the frequency support capacity of the farm.

[0061] According to an embodiment of the present invention, a first sequence value is determined based on the change rate of sequence elements in a time series of output simultaneity rates of respective multiple stations, including: calculating the change rate of sequence elements in a time series based on the output simultaneity rate time series of respective multiple stations to obtain a simultaneity rate change rate time series of respective multiple stations; obtaining an average simultaneity rate change rate of respective multiple stations based on the simultaneity rate change rate time series of respective multiple stations; and obtaining the first sequence value based on the order of magnitude of the average simultaneity rate change rate of the first target station among the average simultaneity rate change rates of respective multiple second target stations.

[0062] According to an embodiment of the present invention, based on the active power data of each of the multiple stations, obtaining the output simultaneity time series of each of the multiple stations specifically includes: based on the active power data of each of the multiple stations, obtaining the actual active power and installed capacity in the multiple active power data. Based on the actual active power and installed capacity of the wind farm to be evaluated, multiple output simultaneity rates can be calculated. The calculated multiple output simultaneity rates are arranged in chronological order to construct the output simultaneity time series of the wind farm.

[0063] Specifically, the calculation method of the output synchronization rate of the wind farm is as follows:

[0064] (1);

[0065] (2);

[0066] Among them, t 1,t represents the output synchronicity rate of the wind farm to be evaluated at the tth time point; where, when the time accuracy is 1 minute and there are 365 days in a year, the output synchronicity rate time series of the wind farm includes 525600 time points; P 1,t represents the time series of the actual active power of the wind farm to be evaluated; P N represents the installed capacity of the Nth station; T1 represents the output synchronization rate time series of the wind farm.

[0067] According to an embodiment of the present invention, the output simultaneity rate of each sequence element is extracted from the output simultaneity rate time series of the wind farm to be evaluated within the past year, and the output simultaneity rate change rate between two adjacent sequence elements is calculated, wherein the sequence elements in the output simultaneity rate time series can be represented as multiple time points.

[0068] Specifically, the calculation method of the output simultaneous rate change rate of the sequence elements in the output simultaneous rate time series is as follows:

[0069] (3);

[0070] Where, t 2,trepresents the output synchronization rate change rate of the wind farm to be evaluated at the tth time point, t 1,t-1 Indicates the output simultaneity rate at the t-1th time point.

[0071] According to an embodiment of the present invention, the calculated simultaneity rate change rate at each time point is arranged in chronological order to construct a time series of the output simultaneity rate change rate of the wind farm to be evaluated within nearly one year.

[0072] Specifically, the expression of the time series of the output synchronization rate change rate of the wind farm to be evaluated in the past year is as follows:

[0073] (4);

[0074] Where T2 represents the time series of the output synchronization rate of the wind farm station, t 2,525599 Indicates the rate of change of output simultaneity at the 525599th time point.

[0075] According to an embodiment of the present invention, the output simultaneity rate change rate time series of multiple wind farms constructed is used to obtain the average output simultaneity rate change rate of multiple wind farms in the region in the past year. Specifically, the average output simultaneity rate change rate of multiple wind farms in the past year is expressed as follows:

[0076] (5);

[0077] In the formula, It represents the average value of the output synchronization rate change rate of multiple wind farms.

[0078] According to an embodiment of the present invention, the average values ​​of the change rates of output simultaneity of multiple wind farms in the past year are sorted, for example, in ascending order, to obtain a sorted sequence of the average values ​​of the change rates of output simultaneity of multiple wind farms in the past year.

[0079] Specifically, the expression of the sorting sequence of the average values ​​of the output synchronization rate change rates of multiple wind farms in the past year is as follows:

[0080] (6);

[0081] In the formula, A sorted sequence representing the average values ​​of the output synchronisation rates of multiple wind farms. represents the average value of the output synchronization rate change rate of the wind farm to be evaluated that ranks in the jth position, that is, As the first ordinal value, it is used to indicate the relative position and average value of the wind farm to be evaluated in the average value ranking of the output simultaneity rate change rate of all wind farms in the region to which it belongs. It represents the average value of the output synchronization rate change rate of the wind farm to be evaluated that ranks at the nth place.

[0082] Based on this, an embodiment of the present invention quantifies the output simultaneity rate change rate of multiple stations in a region to evaluate the volatility and stability of the output of each station; in addition, the order of the average value of the simultaneity rate change rate of the station to be evaluated among the average values ​​of the simultaneity rate change rates of multiple stations is used to reflect the relative position of the output stability of the station to be evaluated among all stations, thereby evaluating the output stability of the station to be evaluated.

[0083] According to an embodiment of the present invention, a second sequence value is determined based on a subsequence corresponding to the first peak period in the output simultaneity time series of each of the multiple stations, including: extracting the subsequence corresponding to the first peak period from the output simultaneity time series of the station to obtain a first peak output simultaneity sequence; obtaining an average first peak output simultaneity of each of the multiple stations based on the first peak output simultaneity sequence of each of the multiple stations; and obtaining a second sequence value based on the order of the first peak output simultaneity average of the first target station among the first peak output simultaneity averages of each of the multiple second target stations.

[0084] According to an embodiment of the present invention, the output simultaneity subsequence corresponding to the first peak period of each wind farm is extracted from the output simultaneity time series of each of the multiple wind farms to obtain the first peak output simultaneity sequence. For example, the first peak period is from 0:00 to 7:00 every day within 1 year, and the first peak output simultaneity sequence obtained by extraction is expressed as follows:

[0085] (7);

[0086] In the formula, T3 represents the first peak output synchronization rate sequence of the wind farm station; since the time accuracy is 1 minute and there are 365 days in a year, the first peak output synchronization rate sequence from 0:00 to 7:00 every day in a year includes a total of 153,300 time points. Therefore, t 3,1 Indicates the first peak output simultaneous rate at the first time point, t 3,153300 It indicates the first peak output simultaneous rate of the wind farm to be evaluated at the 153300th time point.

[0087] According to an embodiment of the present invention, based on the first peak output simultaneous rate sequence, the average output simultaneous rates of multiple wind farms in the region to which the wind farm to be evaluated belongs are calculated. Specifically, the average output simultaneous rates of multiple wind farms in the first peak period are expressed as follows:

[0088] (8);

[0089] In the formula, It represents the average simultaneous output rate of multiple wind farms during the first peak period.

[0090] According to an embodiment of the present invention, the average values ​​of the simultaneous output rates of the first peak period of multiple wind farms are sorted, for example, in ascending order, to obtain a sorted sequence of the average values ​​of the simultaneous output rates of the first peak period of multiple wind farms in the past year.

[0091] Specifically, the expression of the sorting sequence of the average values ​​of the simultaneous output rates of multiple wind farms in the first peak period in the past year is as follows:

[0092] (9);

[0093] In the formula, Represents a sorted sequence of the average values ​​of the simultaneous output rates of multiple wind farms during the first peak period. It represents the average output synchronization rate of the first peak period of the nth wind farm. represents the average output simultaneous rate of the first peak period of the i-th wind farm to be evaluated, that is, As the second ordinal value, it is used to indicate the relative position and average value of the wind farm to be evaluated in the ranking of the average values ​​of the simultaneous output rates during the first peak period of all wind farms in the region to which it belongs.

[0094] Based on this, an embodiment of the present invention determines the relative position of the output simultaneity rate of the wind farm to be evaluated in the first peak period within the region to which it belongs based on the time series of the output simultaneity rates of multiple wind farms in the first peak period, thereby evaluating the output characteristics of the wind farm to be evaluated in the first peak period based on the quantized second sequence value, which helps to optimize the subsequent allocation of power resources to improve the overall efficiency of the power system.

[0095] According to an embodiment of the present invention, a third ordinal value is determined based on the sampling values ​​located in the second peak period in the output simultaneity time series of each of the multiple stations, including: extracting a subsequence corresponding to the second peak period from the output simultaneity time series of the station to obtain a second peak output simultaneity sequence; based on preset sampling points, sampling and processing the second peak output simultaneity sequences of each of the multiple stations to obtain the first output simultaneity sampling values ​​of each of the multiple stations; and obtaining the third ordinal value based on the order of the first output simultaneity sampling values ​​of the first target station among the first output simultaneity sampling values ​​of each of the multiple second target stations.

[0096] According to an embodiment of the present invention, the output simultaneous rate subsequence corresponding to the second peak period of each station is extracted from the output simultaneous rate time series of multiple wind farms to obtain the second peak output simultaneous rate sequence. For example, the second peak period is from 16:00 to 21:00 every day within 1 year, and the extracted second peak output simultaneous rate sequence is expressed as follows:

[0097] (10);

[0098] In the formula, T4 represents the second peak output rate sequence of the wind farm to be evaluated; since the time accuracy is 1 minute and there are 365 days in a year, the second peak output rate sequence from 16:00 to 21:00 every day in a year includes 109,500 time points. Therefore, t 4,1 It represents the second peak output synchronization rate of the wind farm to be evaluated at the first time point, t 4,109500 It indicates the second peak output simultaneous rate of the wind farm to be evaluated at the 109500th time point.

[0099] According to an embodiment of the present invention, the second peak output simultaneity rates of the plurality of stations are sampled based on the preset sampling points to obtain the first output simultaneity sampling values ​​of the plurality of stations in the second peak period. The preset sampling points can be set to sampling points at intervals such as every hour or every half hour.

[0100] According to an embodiment of the present invention, based on the first output simultaneity sampling value, the second peak output simultaneity sequences of multiple wind farms are sorted, for example, sorted in ascending order, to obtain the sorted sequences of the second peak output simultaneity of each of the multiple farms.

[0101] According to an embodiment of the present invention, based on the output simultaneity rate sequence located in the first 10% position of the sorting sequence, the average output simultaneity rate of the first 10% of the second peak period of each of the multiple wind farms is calculated. The average output simultaneity rate of the first 10% of the second peak period of each of the multiple wind farms is sorted, for example, in ascending order, to obtain a sorting sequence of the average output simultaneity rate of the first 10% of the second peak period of each of the multiple wind farms.

[0102] Specifically, the expression of the sorting sequence of the average values ​​of the top 10% output simultaneity rates of the second peak period of each of the multiple wind farms is as follows:

[0103] (11);

[0104] In the formula, It represents the sorted sequence of the average values ​​of the top 10% output simultaneity rates of multiple wind farms during the second peak period. It represents the average output simultaneity rate of the first 10% during the second peak period ranked at the nth position. It represents the average value of the top 10% output synchronization rate during the second peak period of the wind farm to be evaluated at the kth position, that is, As the third ordinal value, it is used to indicate the relative position and average value of the wind farm to be evaluated in the ranking of the average values ​​of the top 10% output simultaneity rates during the second peak period of all wind farms in the region to which it belongs.

[0105] Based on this, the embodiment of the present invention samples and processes the second peak output simultaneity rate sequence of each of the multiple stations through preset sampling points, so as to efficiently obtain the representative output simultaneity rate value of each station in the period, which not only reduces the complexity of data processing, but also retains key information, making the subsequent analysis more concise and efficient. In addition, based on the output simultaneity rate time series of the first 10% of the second peak period of multiple wind farms, the relative position of the output simultaneity rate of the wind farm to be evaluated in the second peak period in the region to which it belongs is determined, so as to evaluate the output characteristics of the wind farm to be evaluated in the second peak period based on the quantized third order value, which is helpful to optimize the subsequent power resource allocation to improve the overall efficiency of the power system.

[0106] Figure 3 A flow chart of a method for determining evaluation weights of respective evaluation factors in a photovoltaic power generation station according to an embodiment of the present invention is shown.

[0107] like Figure 3 As shown, the method includes operations S301 to S304.

[0108] In operation S301, based on active power data of each of the multiple stations, a time series of output simultaneity rates of each of the multiple stations is obtained.

[0109] According to an embodiment of the present invention, when the first target station includes a photovoltaic power station to be evaluated, the output simultaneity time series of each photovoltaic power station is calculated based on multiple active power data of the photovoltaic power station to be evaluated and other photovoltaic power stations in a historical period, such as nearly one year.

[0110] In operation S302, a fourth order value is determined based on a subsequence corresponding to the third peak period in the output simultaneity time series of each of the plurality of stations.

[0111] According to an embodiment of the present invention, a subsequence of the simultaneous output rate of each photovoltaic power station in the third peak period is extracted from the respective simultaneous output rate time series of multiple photovoltaic power stations. Then, the simultaneous output rate subsequences of the multiple stations in the third peak period are sorted to obtain the fourth order value of the photovoltaic power station to be evaluated.

[0112] According to an embodiment of the present invention, the third peak period may be represented as a period that meets the third power generation resource threshold, such as 12:00-16:00 every day in the past year.

[0113] According to an embodiment of the present invention, the fourth order value may be used to represent the output simultaneity value corresponding to the ranking order of the photovoltaic power plant to be evaluated in the third peak period.

[0114] In operation S303, a fifth order value is determined based on the sampling values ​​in the fourth peak period in the output simultaneity time series of each of the plurality of stations.

[0115] According to an embodiment of the present invention, the output simultaneity time series of each photovoltaic power station is sampled to extract the sampling value in the fourth peak period. Based on the sampling value in the fourth peak period, multiple photovoltaic power stations are sorted to determine the relative position of the photovoltaic power station to be evaluated among all photovoltaic power stations, and the fifth order value of the photovoltaic power station to be evaluated is obtained.

[0116] According to an embodiment of the present invention, the fourth peak period may be represented as a period that satisfies a fourth power generation resource threshold, such as 7:00-9:00 in a day.

[0117] According to an embodiment of the present invention, the fifth order value may be used to represent the output simultaneity value corresponding to the ranking order of the photovoltaic power plant to be evaluated in the fourth peak period.

[0118] In operation S304, evaluation weights of respective evaluation factors are obtained based on the fourth ordinal value and the fifth ordinal value.

[0119] According to an embodiment of the present invention, based on the fourth ordinal value and the fifth ordinal value, methods such as weighted average and median sorting are used to determine the evaluation weights of the multiple evaluation factors of the photovoltaic power station to be evaluated.

[0120] Based on this, the embodiments of the present invention can evaluate the volatility of the output power of the photovoltaic power station to be evaluated by quantifying the change rate of the output simultaneity rate, so as to ensure the operating stability of the photovoltaic power station; in addition, by calculating the output simultaneity rate subsequences and sampling values ​​of the third peak period and the fourth peak period, the power generation capacity of the photovoltaic power station to be evaluated in the critical period can be identified, thereby determining the importance of different evaluation weights in evaluating the frequency support capacity of the photovoltaic power station.

[0121] According to an embodiment of the present invention, a fourth order value is determined based on a subsequence corresponding to the third peak period in the output simultaneity time series of each of the multiple stations, including: extracting the subsequence corresponding to the third peak period from the output simultaneity time series of the station to obtain a third peak output simultaneity sequence; obtaining an average second peak output simultaneity of each of the multiple stations based on the third peak output simultaneity sequence of each of the multiple stations; and obtaining a fourth order value based on the order of the second peak output simultaneity average of the first target station among the second peak output simultaneity averages of the multiple second target stations.

[0122] According to an embodiment of the present invention, based on the actual active power and installed capacity of the photovoltaic power station to be evaluated, multiple output simultaneity rates can be calculated. The calculated multiple output simultaneity rates are arranged in chronological order to construct an output simultaneity rate time series of the photovoltaic power station.

[0123] Specifically, the calculation method of the output simultaneity rate of photovoltaic power generation stations is as follows:

[0124] (12);

[0125] (13);

[0126] Among them, t 5,t represents the output synchronicity rate of the photovoltaic power station at the tth time point; where, when the time accuracy is 1 minute and there are 365 days in a year, the output synchronicity rate time series of the photovoltaic power station includes 525600 time points; P 5,t represents the time series of the actual active power of the photovoltaic power station to be evaluated; P N represents the installed capacity of the Nth station; T5 represents the output synchronization rate time series of the photovoltaic power station.

[0127] According to an embodiment of the present invention, the output simultaneous rate subsequence corresponding to the third peak period of each photovoltaic power station is extracted from the output simultaneous rate time series of each of the multiple photovoltaic power stations to obtain the third peak output simultaneous rate sequence. For example, the third peak period is 12:00-16:00 every day within 1 year, and the representation of the extracted third peak output simultaneous rate sequence is as follows:

[0128] (14);

[0129] In the formula, T6 represents the third peak output rate sequence of the photovoltaic power station; since the time accuracy is 1 minute and there are 365 days in a year, the third peak output rate sequence from 12:00 to 16:00 every day in a year includes 87,600 time points. Therefore, t 6,1represents the third peak output synchronization rate of the photovoltaic power station at the first time point, t 6,87600 It indicates the third peak output simultaneous rate of the photovoltaic power station at the 87600th time point.

[0130] According to an embodiment of the present invention, based on the third peak output simultaneity rate sequence, the average output simultaneity rate of the third peak period of multiple photovoltaic power stations in the region to which the photovoltaic power station to be evaluated belongs is calculated. Specifically, the average output simultaneity rate of the third peak period of multiple photovoltaic power stations is expressed as follows:

[0131] (15);

[0132] In the formula, It represents the average simultaneous output rate of multiple photovoltaic power stations during the third peak period.

[0133] According to an embodiment of the present invention, the average values ​​of the simultaneous output rates during the third peak period of multiple photovoltaic power generation sites are sorted, for example, in ascending order, to obtain a sorted sequence of the average values ​​of the simultaneous output rates during the third peak period of multiple photovoltaic power generation sites in the past year.

[0134] Specifically, the expression of the sorting sequence of the average values ​​of the output synchronization rates of multiple photovoltaic power stations during the third peak period in the past year is as follows:

[0135] (16);

[0136] In the formula, Represents the sorted sequence of the average values ​​of the simultaneous output rates during the third peak period of multiple photovoltaic power stations. It represents the average output synchronization rate of the first peak period of the m-th photovoltaic power station. represents the average output simultaneous rate of the third peak period of the photovoltaic power station to be evaluated, that is, As the fourth order value, it is used to indicate the relative position and average value of the photovoltaic power station to be evaluated in the ranking of the average values ​​of the simultaneous output rates of all photovoltaic power stations in the region during the third peak period.

[0137] Based on this, an embodiment of the present invention determines the relative position of the output simultaneity rate of the photovoltaic power station to be evaluated in the third peak period within the region to which it belongs based on the time series of the output simultaneity rate of multiple photovoltaic power stations in the third peak period, thereby evaluating the output characteristics of the photovoltaic power station to be evaluated in the third peak period based on the quantized fourth-order value, which helps to optimize the subsequent power resource allocation to improve the overall efficiency of the power system.

[0138] According to an embodiment of the present invention, a fifth order value is determined based on sampling values ​​located in the fourth peak period in the output simultaneity time series of each of the multiple stations, including: extracting a subsequence corresponding to the fourth peak period from the output simultaneity time series of the station to obtain a fourth peak output simultaneity sequence; based on preset sampling points, sampling and processing the fourth peak output simultaneity sequences of each of the multiple stations to obtain second output simultaneity sampling values ​​of each of the multiple stations; and obtaining the fifth order value based on the order of the second output simultaneity sampling values ​​of the first target station among the second output simultaneity sampling values ​​of each of the multiple second target stations.

[0139] According to an embodiment of the present invention, the output simultaneous rate subsequence corresponding to the fourth peak period of each photovoltaic power station is extracted from the output simultaneous rate time series of each of the multiple photovoltaic power stations to obtain the fourth peak output simultaneous rate sequence. For example, the fourth peak period is 7:00-9:00 every day within 1 year, and the fourth peak output simultaneous rate sequence extracted is expressed as follows:

[0140] (17);

[0141] In the formula, T7 represents the fourth peak output rate sequence of the photovoltaic power station; since the time accuracy is 1 minute and there are 365 days in a year, the fourth peak output rate sequence from 7:00 to 9:00 every day in a year includes 43,800 time points. Therefore, t 7,1 represents the fourth peak output synchronization rate of the photovoltaic power plant at the first time point, t 7,43800 It indicates the fourth peak output simultaneous rate of the photovoltaic power station at the 43800th time point.

[0142] According to an embodiment of the present invention, the fourth peak output simultaneity rates of the plurality of stations are sampled based on the preset sampling points to obtain the second output simultaneity sampling values ​​of the plurality of stations in the fourth peak period. The preset sampling points can be set to sampling points for sampling every hour, every half hour, etc.

[0143] According to an embodiment of the present invention, based on the second output simultaneity rate sampling value, the fourth peak output simultaneity rate sequences of multiple photovoltaic power generation sites are sorted, for example, sorted in ascending order, to obtain the sorted sequence of the fourth peak output simultaneity rates of the multiple photovoltaic power generation sites.

[0144] According to an embodiment of the present invention, based on the output simultaneity rate sequence located in the first 10% position of the sorting sequence, the average output simultaneity rate of the first 10% of the fourth peak period of each of the multiple photovoltaic power generation sites is calculated. At the same time, the average output simultaneity rate of the first 10% of the fourth peak period of each of the multiple photovoltaic power generation sites is sorted, for example, sorted in order from small to large, to obtain the sorting sequence of the average output simultaneity rate of the first 10% of the fourth peak period of each of the multiple photovoltaic power generation sites.

[0145] Specifically, the expression of the sorting sequence of the average values ​​of the top 10% output simultaneity rates of the fourth peak period of each of the multiple photovoltaic power stations is as follows:

[0146] (18);

[0147] In the formula, Represents the sorted sequence of the average values ​​of the top 10% output simultaneity rates during the fourth peak period of multiple photovoltaic power stations. It represents the average output simultaneous rate of the top 10% in the fourth peak period ranked at the mth position. It represents the average output simultaneous rate of the first 10% of the photovoltaic power station to be evaluated during the fourth peak period, which is As the fifth order value, it is used to indicate the relative position and average value of the photovoltaic power station to be evaluated in the ranking of the average values ​​of the top 10% output simultaneity rates of all photovoltaic power stations in the region during the fourth peak period.

[0148] Based on this, the embodiment of the present invention samples and processes the fourth peak output simultaneity rate sequence of each of the multiple photovoltaic power generation stations through preset sampling points, so as to efficiently obtain the representative output simultaneity rate value of each photovoltaic power generation station in the period, which not only reduces the complexity of data processing, but also retains key information, making the subsequent analysis more concise and efficient. In addition, based on the output simultaneity rate time series of the first 10% of the fourth peak period of multiple photovoltaic power generation stations, the relative position of the output simultaneity rate of the fourth peak period of the photovoltaic power generation station to be evaluated in the region to which it belongs is determined, so as to evaluate the output characteristics of the photovoltaic power generation station to be evaluated in the fourth peak period based on the quantized fifth order value, which helps to optimize the subsequent configuration of power resources to improve the overall efficiency of the power system.

[0149] According to an embodiment of the present invention, a membership matrix of the first target site is constructed based on the test results of each of the multiple evaluation sub-factors, including: determining the probability values ​​of the evaluation sub-factors corresponding to each of the multiple evaluation levels based on the test results of the evaluation sub-factors; and constructing the membership matrix based on the probability values ​​of the evaluation sub-factors corresponding to each of the multiple evaluation levels.

[0150] According to an embodiment of the present invention, a three-level evaluation index is constructed based on the test results of each of the multiple evaluation sub-factors.

[0151] For example, if the first target site is a wind farm, the second-level evaluation factors of the wind farm are {U1, U2, U3} = {frequency adaptability, inertia response capability, frequency response capability}. The third-level evaluation sub-factors of the wind farm further refine the second-level evaluation factors. Specifically, the second-level evaluation factor frequency adaptability U1 of the wind farm includes the third-level evaluation sub-factors {U 11 , U 12 , U 13}={low-frequency ride-through capability, continuous operation capability, high-frequency ride-through capability}, the second-layer evaluation factor inertia response capability U2 of the wind farm station includes the third-layer evaluation sub-factor {U 21 , U 22}={inertia response steady-state deviation, inertia response rise time}, the second-level evaluation factor frequency response capability U3 of the wind farm station includes the third-level evaluation sub-factor {U 31 , U 32 , U 33 , U 34}={frequency response steady-state deviation, frequency response lag time, frequency response rise time, frequency response adjustment time}.

[0152] For example, if the first target site is a photovoltaic power station, the second-layer evaluation factor of the photovoltaic power station is {O1, O2} = {frequency adaptability, frequency response capability}, and the third-layer evaluation sub-factors of the photovoltaic power station further refine the second-layer evaluation factors. Specifically, the second-layer evaluation factor frequency adaptability O1 of the photovoltaic power station includes the third-layer evaluation sub-factors {O 11 , O 12 , O 13 , O 14}={low-frequency ride-through capability, continuous operation capability, high-frequency ride-through capability, rate of change ride-through capability}, the second-layer evaluation factor frequency response capability O2 of the photovoltaic power station includes the third-layer evaluation sub-factors {O 21 , O 22 , O 23 , O 24}={frequency response steady-state deviation, frequency response lag time, frequency response rise time, frequency response adjustment time}.

[0153] According to an embodiment of the present invention, a four-level comment can be constructed for the constructed three-level evaluation index. For example, the comment set E1={ε1, ε2, ε3, ε4}={excellent, good, qualified, unqualified} obtained by constructing the four-level comment has a corresponding score set E2={100, 80, 60, 40}.

[0154] According to an embodiment of the present invention, based on the test results of multiple evaluation sub-factors, the probability values ​​of each evaluation sub-factor corresponding to multiple evaluation levels are determined. The probability values ​​of each evaluation sub-factor corresponding to multiple evaluation levels are arranged in a certain format to construct a membership matrix. The probability value can be used to represent the membership, wherein the membership can be used to reflect the membership degree of multiple evaluation sub-factors relative to different evaluation levels.

[0155] According to an embodiment of the present invention, each row of the membership matrix can represent an evaluation sub-factor, each column of the membership matrix can represent an evaluation level, and the elements in the matrix represent the membership of a certain evaluation sub-factor corresponding to a certain evaluation level. Specifically, the representation of the membership matrix is ​​as follows:

[0156] (19);

[0157] In the formula, R o represents the membership matrix, q represents the level of the review, for the four-level review, q=4; r opq represents the membership degree of the third-level evaluation sub-factor of the wind farm or the third-level evaluation sub-factor of the photovoltaic power station to the qth level comment, p represents the number of the third-level evaluation sub-factors, r o Indicates the membership degree of each evaluation sub-factor in the third layer.

[0158] According to an embodiment of the present invention, the weights of the third-level evaluation sub-factors can be determined using an empirical judgment method, based on the likelihood of the events corresponding to each evaluation sub-factor occurring during the actual operation of the power system. That is, the "higher" the importance of each evaluation sub-factor to the power grid dispatching organization, the greater the weight given to the indicator.

[0159] According to a specific embodiment of the present invention, the weights of the third-level evaluation sub-factors of the wind farm station in the second-level evaluation factors may be as follows:

[0160] (20);

[0161] Where V 11 、V 12 、V 13 、V 21 、V 22 、V 31 、V 32 、V 33 、V 34 They are respectively represented as the third level evaluation sub-factors U of the wind farm station 11 , U 12 , U 13 , U 21 , U 22 , U31 , U 32 , U 33 , U 34 The weight of the second-level evaluation factors.

[0162] In this specific embodiment, based on the average value of the output simultaneity rate change rate of the wind farm to be evaluated ranked at the jth position in the above formula (6), the average value of the output simultaneity rate during the first peak period of the wind farm to be evaluated ranked at the ith position in formula (9), and the average value of the output simultaneity rate of the first 10% during the second peak period of the wind farm to be evaluated ranked at the kth position in formula (11), the weights of the second-level evaluation factors of the wind farm in the first-level evaluation indicators are constructed as follows:

[0163] (twenty one);

[0164] Where V1, V2, and V3 represent the weights of the second-layer evaluation factors U1, U2, and U3 in the first-layer evaluation indicators, respectively.

[0165] According to another specific embodiment of the present invention, the weights of the third-level evaluation sub-factors of the photovoltaic power station in the second-level evaluation factors may be as follows:

[0166] (twenty two);

[0167] Where P 11 , P 12 , P 13 , P 14 , P 21 , P 22 , P 23 , P 24 They are respectively represented as the third-level evaluation sub-factors O of photovoltaic power stations. 11 , O 12 , O 13 , O 14 , O 21 , O 22 , O 23 , O 24 The weight of .

[0168] In this specific embodiment, based on the average output simultaneity rate of the third peak period of the photovoltaic power station to be evaluated ranked at the i'th position in the above formula (16) and the average output simultaneity rate of the top 10% of the fourth peak period of the photovoltaic power station to be evaluated ranked at the k'th position in formula (18), the weight of the second-level evaluation factor of the photovoltaic power station in the first-level evaluation index is constructed as follows:

[0169] (twenty three);

[0170] Where P1 and P2 represent the weights of the second-layer evaluation factors O1 and O2 in the first-layer evaluation indicators, respectively.

[0171] In summary, the fuzzy comprehensive evaluation weights of the frequency support capability of new energy stations are shown in Table 1.

[0172] Table 1

[0173]

[0174] According to a specific embodiment of the present invention, the weight vector of the three-level evaluation index is the same as the score set of the four-level comments, that is, the weight vector W' of the three-level evaluation index E ={100, 80, 60, 40}, the weight vector of the comment set is W E= {100 / (100+80+60+40), 80 / (100+80+60+40), 60 / (100+80+60+40), 40 / (100+80+60+40)}, and the weight vector W of the comment set is calculated E ={0.36, 0.29, 0.21, 0.14}.

[0175] According to an embodiment of the present invention, based on the preset weights of each of the multiple evaluation sub-factors, the evaluation weights of each of the multiple evaluation factors and the membership matrix, a frequency support capability evaluation result of the first target station is obtained.

[0176] According to a specific embodiment of the present invention, if the first target site is a wind farm, the frequency support capability evaluation result of the first target site can be determined based on the weight of the third-level evaluation sub-factors of the wind farm in the second-level evaluation factors, the weight of the second-level evaluation factors in the first-level evaluation indicators, and the membership matrix.

[0177] Specifically, based on the above formula (19) and formula (20), the second-level evaluation factors of the wind farm are comprehensively evaluated to determine the comprehensive evaluation vector of the second-level evaluation factors of the wind farm. The specific calculation method is as follows:

[0178] (twenty four);

[0179] In the formula, B o represents the comprehensive evaluation vector of the second-level evaluation factors of the wind farm station, V oq represents the weight of the third-level evaluation sub-factor of the wind farm in the second-level evaluation factors, R o represents the membership matrix.

[0180] In a specific embodiment of the present invention, when determining the comprehensive evaluation vector of the second-level evaluation factors of the wind farm, a fuzzy comprehensive evaluation can be performed on the frequency support capability of the wind farm to be evaluated based on the above formulas (21) and (24).

[0181] Specifically, based on the comprehensive evaluation vector of the second-level evaluation factors of the wind farm and the weight of the second-level evaluation factors in the first-level evaluation indicators, the frequency support capacity evaluation result of the wind farm can be determined. The specific calculation method is as follows:

[0182] (25);

[0183] Where S represents the frequency support capability evaluation result of the wind farm station, V o It indicates the weight of the second-level evaluation factors of the wind farm station in the first-level evaluation indicators.

[0184] In a specific embodiment of the present invention, when determining the frequency support capability evaluation result of a wind farm, the comprehensive evaluation value of the wind farm can be determined based on the weight vectors of the three-layer evaluation indicators and the frequency support capability evaluation result of the wind farm. The specific calculation method is as follows:

[0185] (26);

[0186] In the formula, Indicates the comprehensive evaluation value of the wind farm.

[0187] According to another specific embodiment of the present invention, if the first target station is a photovoltaic power generation station, the frequency support capability evaluation result of the first target station can be determined based on the weight of the third-level evaluation sub-factors of the photovoltaic power generation station in the second-level evaluation factors, the weight of the second-level evaluation factors in the first-level evaluation indicators, and the membership matrix.

[0188] Specifically, based on the above formula (19) and formula (22), the second-level evaluation factors of the photovoltaic power station are comprehensively evaluated to determine the comprehensive evaluation vector of the second-level evaluation factors of the photovoltaic power station. The specific calculation method is as follows:

[0189] (27);

[0190] In the formula, B' o represents the comprehensive evaluation vector of the second-level evaluation factors of photovoltaic power stations, P oq Represents the weight of the third-level evaluation sub-factor of the photovoltaic power station in the second-level evaluation factor, R' o Represents the membership matrix of photovoltaic power generation stations.

[0191] In a specific embodiment of the present invention, when determining the comprehensive evaluation vector of the second-level evaluation factors of the photovoltaic power generation station, the frequency support capability of the photovoltaic power generation station to be evaluated can be fuzzy comprehensively evaluated based on the above formula (23) and formula (27), and the frequency support capability evaluation result of the photovoltaic power generation station can be determined based on the comprehensive evaluation vector of the second-level evaluation factors of the photovoltaic power generation station and the weight of the second-level evaluation factors in the first-level evaluation indicators. The specific calculation method is as follows:

[0192] (28);

[0193] Where S' represents the frequency support capability evaluation result of the photovoltaic power station, P o It indicates the weight of the second-level evaluation factors of photovoltaic power stations in the first-level evaluation indicators.

[0194] In a specific embodiment of the present invention, when determining the frequency support capability evaluation result of a photovoltaic power generation station, the comprehensive evaluation value of the photovoltaic power generation station can be determined based on the weight vector of the three-layer evaluation index and the frequency support capability evaluation result of the photovoltaic power generation station. The specific calculation method is as follows:

[0195] (29);

[0196] In the formula, Indicates the comprehensive evaluation value of the photovoltaic power station.

[0197] Table 2

[0198]

[0199] According to an embodiment of the present invention, in the process of constructing the evaluation index of the frequency support capability of the wind farm, the wind farm frequency adaptability evaluation factor can be configured to operate as required within the power system frequency range shown in Table 2.

[0200] According to an embodiment of the present invention, in the process of constructing an evaluation index of the frequency support capability of a wind farm, the active power change steady-state deviation evaluation sub-factor included in the inertia response capability evaluation factor can be configured as follows: when the power system frequency deviation is greater than the dead zone range and the active power of the wind farm is greater than 20% of the rated active power, the wind farm should provide an inertia response under the condition of satisfying the following formula (30), and the active power change in the inertia response capability of the wind farm should satisfy the following formula (31), with an allowable deviation of no more than ±1% of the rated active power.

[0201] (30);

[0202] (31);

[0203] In the formula, represents the frequency deviation of the power system (Hz), f represents the grid connection point frequency of the wind farm (Hz), t represents time (s), T J represents the equivalent inertia time constant of the wind farm (s), f N Indicates the rated frequency of the power system (Hz), P t1 represents the inertia response active power of the wind farm to be evaluated (MW), It indicates the change in active power of the inertia response of the wind farm to be evaluated.

[0204] According to an embodiment of the present invention, in the process of constructing the evaluation index of the frequency support capability of a wind farm, the active power variation rise time evaluation subfactor included in the inertia response capability evaluation factor may be configured to be no greater than 1 s.

[0205] According to an embodiment of the present invention, in the process of constructing an evaluation index for the frequency support capability of a wind farm, the steady-state deviation included in the frequency response capability evaluation factor can be configured as follows: when the frequency deviation of the power system is greater than the dead zone range and the active power of the wind farm is greater than 20% of the rated active power, the wind farm should have the ability to participate in the primary frequency regulation of the power system, and the frequency response active power change of the wind farm should satisfy formula (32), and the allowable deviation is not greater than ±1% of the rated active power.

[0206] (32);

[0207] In the formula, K f Indicates the active frequency modulation coefficient, f N Indicates the rated frequency of the power system (Hz), P t2 represents the frequency response active power of the wind farm to be evaluated (MW), It indicates the frequency response active power change of the wind farm to be evaluated.

[0208] According to an embodiment of the present invention, in the process of constructing the evaluation index of the frequency support capability of a wind farm station, the frequency response capability evaluation factors include that the active power change lag time is configured to be no more than 2s; the active power change rise time is configured to be no more than 9s; and the active power change adjustment time is configured to be no more than 15s.

[0209] According to an embodiment of the present invention, the present invention also proposes a method for measuring the frequency support capacity of a new energy station based on a low-frequency disturbance device. On the high-voltage side of the step-up transformer of the new energy station, a low-frequency disturbance device is used to send out excitation signals such as frequency deviation and frequency change rate, collect telemetering signals such as the operating status of the new energy station and active power change, and realize the measurement of the value of the frequency support capacity evaluation index of the new energy station.

[0210] Figure 4 A schematic diagram of a low-frequency disturbance device according to an embodiment of the present invention is shown.

[0211] like Figure 4 As shown, the input and output ends of the low-frequency disturbance device are connected between the power grid and the wind turbine or photovoltaic power generation unit through a circuit breaker. The low-frequency disturbance device is used to generate different types of frequency excitation signals on the high-voltage side of the new energy station booster station, collect signals such as the operating status of the new energy station and the active power output, and analyze the frequency support capacity of the new energy station.

[0212] According to a specific embodiment of the present invention, the new energy station operates normally and does not participate in system frequency modulation. During the test, the active power output of the new energy station should be in a stable working condition. The frequency adaptability measurement process includes:

[0213] Under the rated voltage condition, keep the power generation units of the new energy station in normal operation, adjust the test device to gradually increase the frequency from 50Hz in steps of 0.1Hz, and each step lasts for 20 seconds. When the frequency rises to 50.5Hz, the test at this point lasts for 30 minutes. During the test, if a new energy power generation unit is disconnected from the grid, record the test duration and disconnection time; if no new energy power generation unit is disconnected from the grid, continue the test.

[0214] Adjust the test device to increase the frequency from 50.5Hz to 51Hz in steps of 0.5Hz for 3 minutes. During the test, if any renewable energy power generation unit is disconnected from the grid, record the test duration and the disconnection time; if no renewable energy power generation unit is disconnected from the grid, continue the test.

[0215] Adjust the test device to increase the frequency from 51Hz to 51.5Hz in steps of 0.5Hz for 30s. During the test, if a renewable energy power generation unit is disconnected from the grid, record the test duration and the disconnection time; if no renewable energy power generation unit is disconnected from the grid, restore the frequency to 50Hz as soon as possible and continue the test.

[0216] Under the rated voltage condition, keep the power generation units of the new energy station running normally, adjust the test device to gradually reduce the frequency from 50Hz in steps of 0.5Hz, and each step lasts for 20 seconds. When the frequency drops to 48.5Hz, the test at this point lasts for 30 minutes. During the test, if a new energy power generation unit is disconnected from the grid, record the test duration and disconnection time; if no new energy power generation unit is disconnected from the grid, continue the test.

[0217] The test device was adjusted to reduce the frequency from 48.5 Hz to 48 Hz in steps of 0.5 Hz. Wind power lasted for 30 minutes (photovoltaic power lasted for 5 minutes). During the test, if any renewable energy power generation unit was disconnected from the grid, the test duration and the disconnection time were recorded. If no renewable energy power generation unit was disconnected from the grid, the test was continued.

[0218] The test device was adjusted to reduce the frequency from 48 Hz to 47.5 Hz in steps of 0.5 Hz for 60 s. During the test, if any renewable energy power generation unit was disconnected from the grid, the test duration and the disconnection time were recorded. If no renewable energy power generation unit was disconnected from the grid, the test was continued.

[0219] The test device was adjusted to reduce the frequency from 47.5 Hz to 47 Hz in steps of 0.5 Hz for 20 seconds. During the test, if any renewable energy power generation unit was disconnected from the grid, the test duration and the disconnection time were recorded. If no renewable energy power generation unit was disconnected from the grid, the test was continued.

[0220] The adjustment test device starts from 47Hz and reduces the frequency to 46.5Hz in steps of 0.5Hz for 5s. During the test, if a new energy power generation unit is disconnected from the grid, the test duration and the time of disconnection are recorded; if no new energy power generation unit is disconnected from the grid, the frequency is restored to 50Hz as soon as possible. If the new energy station is a wind farm, the frequency adaptability test ends; if the new energy station is a photovoltaic power station, the test continues.

[0221] Under the rated voltage condition, the power generation units of the photovoltaic power station are kept in normal operation, and the frequency of the test device is adjusted to drop from 50Hz to 49Hz at a frequency change rate of 2Hz / s, and the frequency is dropped to 47.5Hz at a frequency change rate of 1Hz / s as soon as possible. During the test, if a photovoltaic power generation unit is disconnected from the grid, the test duration and the time of disconnection are recorded; if no photovoltaic power generation unit is disconnected from the grid, the frequency adaptability test is completed.

[0222] According to a specific embodiment of the present invention, the inertia response capability measurement process includes:

[0223] Under rated voltage conditions, keep all power generation units in the wind farm in normal operation, adjust the output frequency of the test device from 50Hz, and increase the frequency to 50.5 Hz at a frequency change rate of 0.5Hz / s. After the frequency stabilizes, continue for 10s, and after returning to 50Hz at the same frequency change rate, maintain the test time for no less than 10s. During the test, if a power generation unit is disconnected from the grid, record the test duration and disconnection time; if no power generation unit is disconnected from the grid, record the active value before the disturbance, the measured value of the active regulation, the theoretical value of the active regulation, the rise time, and continue the test.

[0224] Under rated voltage conditions, keep all power generation units in the wind farm in normal operation, adjust the output frequency of the test device from 50Hz, reduce the frequency to 48.5Hz at a frequency change rate of 0.5Hz / s, and maintain the frequency for 10s after it stabilizes. After it returns to 50Hz at the same frequency change rate, keep the test time for no less than 10s. During the test, if a power generation unit is disconnected from the grid, record the test duration and disconnection time; if no power generation unit is disconnected from the grid, record the active value before the disturbance, the measured value of the active regulation, the theoretical value of the active regulation, and the rise time. At this point, the inertia response capability test is completed.

[0225] According to a specific embodiment of the present invention, the test process of frequency response capability should include at least two operating conditions of low load and high load operation range of the new energy station. The low load operating condition is selected between 20% and 50% of the rated active power, and the high load operating condition is selected between 65% and 100% of the rated active power. The actual measurement process of frequency response capability includes:

[0226] Under low load conditions, ensure the normal operation of each power generation unit in the wind farm under rated voltage conditions, adjust the output frequency of the test device from 50 Hz to 50.15 Hz in steps of 0.15 Hz, and the frequency difference should be maintained until the primary frequency modulation power reaches the theoretical calculated value and then restored to 50 Hz 20 seconds later. Record the active value before disturbance, the measured value of active regulation, the theoretical value of active regulation, the lag time, the rise time, the regulation time, and continue the test.

[0227] Under low load conditions, ensure the normal operation of each power generation unit in the wind farm under rated voltage conditions, adjust the output frequency of the test device from 50 Hz to 49.85 Hz in steps of 0.15 Hz, and the frequency difference should be maintained until the primary frequency modulation power reaches the theoretical calculated value and then restored to 50 Hz 20 seconds later. Record the active value before disturbance, the measured value of active regulation, the theoretical value of active regulation, the lag time, the rise time, the regulation time, and continue the test.

[0228] Under high load conditions, ensure the normal operation of each power generation unit in the wind farm under rated voltage conditions, adjust the output frequency of the test device from 50 Hz to 50.15 Hz in steps of 0.15 Hz, and the frequency difference should be maintained until the primary frequency modulation power reaches the theoretical calculated value and then restored to 50 Hz 20 seconds later. Record the active value before disturbance, the measured value of active regulation, the theoretical value of active regulation, the lag time, the rise time, the regulation time, and continue the test.

[0229] Under high load conditions, ensure that all power generation units in the wind farm operate normally under rated voltage conditions, adjust the output frequency of the test device from 50Hz to 49.85Hz in steps of 0.15Hz, and the frequency difference should be maintained until the primary frequency modulation power reaches the theoretical calculated value and then restored to 50Hz 20s later, and record the active value before disturbance, the measured value of active regulation, the theoretical value of active regulation, the lag time, the rise time, and the regulation time. At this point, the frequency response capability test is over.

[0230] According to a specific embodiment of the present invention, it is assumed that there are two wind farms, denoted as wind farm A and wind farm B, with a grid-connected voltage level of 110 kV, and a total of 50 wind farms in the region. The frequency support capability of wind farm A and wind farm B is evaluated, and the specific process is as follows: the frequency adaptability, inertia response capability, and frequency response capability of wind farm A and wind farm B are tested in turn, and the measured results are shown in Table 3.

[0231] Table 3

[0232]

[0233] In this specific embodiment, based on the measured results in Table 3, a single factor evaluation is performed on each evaluation sub-factor in the second-layer evaluation factors of the two wind farms, and the membership matrix of the two wind farms can be obtained.

[0234] Specifically, the frequency adaptability membership matrix of wind farm A and the frequency adaptability membership matrix of wind farm B are as follows:

[0235] (33);

[0236] (34);

[0237] In the formula, R 11 represents the frequency adaptability membership matrix of wind farm A; R 21 Represents the frequency adaptability membership matrix of wind farm B.

[0238] The inertia response capability membership matrix of wind farm A and the inertia response capability membership matrix of wind farm B are as follows:

[0239] (35);

[0240] (36);

[0241] In the formula, R 12 represents the inertia response capability membership matrix of wind farm A; R 22 Represents the inertia response capability membership matrix of wind farm B.

[0242] The frequency response capability membership matrix of wind farm A and the frequency response capability membership matrix of wind farm B are as follows:

[0243] (37);

[0244] (38);

[0245] In the formula, R 13 represents the frequency response capability membership matrix of wind farm A; R 23 Represents the frequency response capability membership matrix of wind farm B.

[0246] In this specific embodiment, based on the above formulas (1) to (11), and (21), the weights of the second-level evaluation factors in the first-level indicators are determined.

[0247] Specifically, by calculating the output simultaneity rate and ranking of wind farm A, it is determined that the average output simultaneity rate of wind farm A in the first peak period ranks 10th, i.e., i=10, the average output simultaneity rate change rate of wind farm A ranks 31st, i.e., j=31, and the average output simultaneity rate of the first 10% of wind farm A in the second peak period ranks 43rd, i.e., k=43. By calculating the output simultaneity rate and ranking of wind farm B, it is determined that the average output simultaneity rate of wind farm B in the first peak period ranks 33rd, i.e., i=33, the average output simultaneity rate change rate of wind farm B ranks 15th, i.e., j=15, and the average output simultaneity rate of the first 10% of wind farm B in the second peak period ranks 28th, i.e., k=28.

[0248] Based on this, the weights of the second-level evaluation factors of wind farm A and wind farm B in the first-level indicators are calculated as follows:

[0249] (39);

[0250] (40);

[0251] Where V A,1 、V A,2 、V A,3 They are respectively the weights of the second-level evaluation factors of wind farm A in the first-level indicators, V B,1 、V B,2 、V B,3 They respectively represent the weights of the second-level evaluation factors of wind farm B in the first-level indicators.

[0252] In this specific embodiment, based on the weights of the second-layer evaluation factors of wind farm A and wind farm B in the first-level index, the second-layer evaluation factors of wind farm A and wind farm B are comprehensively evaluated to obtain the comprehensive evaluation vectors of the second-layer evaluation factors of wind farm A and wind farm B:

[0253] (41);

[0254] (42);

[0255] In the formula, B A,2 represents the comprehensive evaluation vector of the second-level evaluation factors of wind farm A, B B,2 Represents the comprehensive evaluation vector of the second-level evaluation factors of wind farm B.

[0256] In this specific embodiment, the frequency support capabilities of wind farm A and wind farm B are subjected to fuzzy comprehensive evaluation, and the evaluation results of the frequency support capabilities of wind farm A and wind farm B can be obtained, which are specifically as follows:

[0257] (43);

[0258] (44);

[0259] In the formula, S A represents the frequency support capability evaluation result of wind farm A, S B It represents the frequency support capability evaluation result of wind farm B.

[0260] In this specific embodiment, based on the frequency support capability evaluation results of wind farm A and wind farm B, the comprehensive evaluation values ​​of wind farm A and wind farm B are determined, wherein the weight vector W' of the three-layer evaluation index is E ={100, 80, 60, 40}, the weight vector W of the review set E ={0.36, 0.29, 0.21, 0.14}, as shown below:

[0261] (45);

[0262] (46);

[0263] In the formula, Represents the weight vector W of wind farm A based on the comment set E The comprehensive review value of Represents the weight vector W' of wind farm A based on the three-layer evaluation index E The comprehensive review value of Represents the weight vector W of wind farm B based on the comment set E The comprehensive review value of Represents the weight vector W' of wind farm B based on the three-layer evaluation index E The comprehensive review value.

[0264] In this specific embodiment, it can be seen from the above comment values ​​that the comprehensive performance of wind farm A is better than that of wind farm B.

[0265] Figure 5 A block diagram of a device for evaluating frequency support capability of a new energy station based on output characteristics according to an embodiment of the present invention is shown.

[0266] like Figure 5 As shown, the evaluation device includes a testing module 510 , a building module 520 , a weight determination module 530 and a result determination module 540 .

[0267] The test module 510 is used to respond to a frequency support capability evaluation request for the first target station, and to perform a frequency support capability test on the first target station when the first target station does not participate in frequency modulation, so as to obtain test results of each of multiple evaluation sub-factors of the first target station.

[0268] The construction module 520 is used to construct a membership matrix of the first target site based on the test results of each of the multiple evaluation sub-factors.

[0269] The weight determination module 530 is used to obtain the evaluation weights of the multiple evaluation factors based on the active power data of the multiple stations in the historical period.

[0270] The result determination module 540 is used to obtain the frequency support capability evaluation result of the first target station based on the preset weights of each of the multiple evaluation sub-factors, the evaluation weights of each of the multiple evaluation factors and the membership matrix.

[0271] It should be noted that the new energy station frequency support capability evaluation device part in the embodiment of the present invention corresponds to the new energy station frequency support capability evaluation method part in the embodiment of the present invention. The description of the new energy station frequency support capability evaluation device part specifically refers to the new energy station frequency support capability evaluation method part, which will not be repeated here.

[0272] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. It will be appreciated by those skilled in the art that the features described in the various embodiments of the present invention may be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in the various embodiments of the present invention may be combined and / or combined in various ways. All of these combinations and / or combinations fall within the scope of the present invention.

[0273] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination advantageously. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for evaluating the frequency support capability of a new energy station based on output characteristics, characterized in that: The frequency support capability evaluation method of the new energy station includes: In response to a frequency support capability evaluation request for a first target station, when the first target station does not participate in frequency modulation, a frequency support capability test is performed on the first target station to obtain test results of each of a plurality of evaluation sub-factors of the first target station, wherein the evaluation index of the frequency support capability of the first target station includes a plurality of evaluation factors, and each evaluation factor includes a plurality of evaluation sub-factors; constructing a membership matrix of the first target site based on the test results of each of the plurality of evaluation sub-factors; Based on active power data of each of the plurality of stations in a historical period, obtaining evaluation weights of each of the plurality of evaluation factors, wherein the plurality of stations include the first target station and a plurality of second target stations, and the second target stations include new energy stations of the same type as the first target station and located in the same area; Based on the preset weights of the multiple evaluation sub-factors, the evaluation weights of the multiple evaluation factors, and the membership matrix, obtaining a frequency support capability evaluation result of the first target station; Wherein, in the case where the first target site is a wind farm, obtaining the evaluation weights of the plurality of evaluation factors based on the active power data of the plurality of sites in the historical period includes: Based on the active power data of each of the plurality of stations, obtaining a time series of output simultaneity rate of each of the plurality of stations; Determining a first sequence value based on a change rate of a sequence element in a time series of output simultaneity rates of each of the plurality of stations; Determining a second sequence value based on a subsequence corresponding to the first peak period in the output simultaneity time series of each of the plurality of stations; Determine a third order value based on the sampling values ​​in the second peak period in the output simultaneity time series of each of the plurality of stations; Based on the first ordinal value, the second ordinal value, and the third ordinal value, evaluation weights of the plurality of evaluation factors are obtained.

2. The frequency support capability evaluation method of a new energy station according to claim 1 is characterized in that: The determining of the first sequence value based on the change rate of the sequence elements in the output simultaneity time series of the plurality of stations includes: Based on the output simultaneity time series of the plurality of stations, the change rate of the sequence elements in the time series is calculated to obtain the simultaneity change rate time series of the plurality of stations; Based on the time series of the simultaneity rate change rates of the multiple stations, an average value of the simultaneity rate change rates of the multiple stations is obtained; The first order value is obtained based on the order of the average value of the simultaneity rate change rate of the first target station among the average values ​​of the simultaneity rate change rates of the plurality of second target stations.

3. The method for evaluating the frequency support capability of a new energy station according to claim 1 is characterized in that: The determining of the second sequence value based on the subsequence corresponding to the first peak period in the output simultaneity time series of each of the plurality of stations includes: Extracting a subsequence corresponding to the first peak period from the station output simultaneous rate time series to obtain a first peak output simultaneous rate sequence; Based on the respective first peak output simultaneous rate sequences of the plurality of stations, obtaining respective first peak output simultaneous rate averages of the plurality of stations; The second order value is obtained based on the order of the first peak output simultaneous rate average value of the first target station among the first peak output simultaneous rate average values ​​of the plurality of second target stations.

4. The method for evaluating the frequency support capability of a new energy station according to claim 1 is characterized in that: The determining of the third sequence value based on the sampling values ​​in the second peak period in the output simultaneity time series of the plurality of stations includes: Extracting a subsequence corresponding to the second peak period from the output simultaneity time series of the station to obtain a second peak output simultaneity sequence; Based on the preset sampling points, sampling and processing are respectively performed on the second peak output simultaneity rate sequences of the plurality of stations to obtain the first output simultaneity rate sampling values ​​of the plurality of stations; The third order value is obtained based on the order of the first output simultaneity sampling value of the first target station among the first output simultaneity sampling values ​​of the plurality of second target stations.

5. The method for evaluating the frequency support capability of a new energy station according to claim 1 is characterized in that: In the case where the first target site is a photovoltaic power generation site, obtaining the evaluation weights of the plurality of evaluation factors based on active power data of the plurality of sites in historical periods includes: Based on the active power data of each of the plurality of stations, obtaining a time series of output simultaneity rate of each of the plurality of stations; Determining a fourth order value based on a subsequence corresponding to the third peak period in the output simultaneity time series of each of the plurality of stations; Determining a fifth order value based on the sampling values ​​in the fourth peak period in the output simultaneity time series of each of the plurality of stations; Based on the fourth ordinal value and the fifth ordinal value, evaluation weights of the respective evaluation factors are obtained.

6. The method for evaluating the frequency support capability of a new energy station according to claim 5 is characterized in that: The determining of the fourth order value based on the subsequence corresponding to the third peak period in the output simultaneity time series of each of the plurality of stations comprises: Extracting a subsequence corresponding to the third peak period from the station output simultaneous rate time series to obtain a third peak output simultaneous rate sequence; Based on the respective third peak output simultaneous rate sequences of the plurality of stations, obtaining the respective second peak output simultaneous rate averages of the plurality of stations; The fourth order value is obtained based on the order of the second peak output simultaneous rate average value of the first target station among the second peak output simultaneous rate average values ​​of the plurality of second target stations.

7. The method for evaluating the frequency support capability of a new energy station according to claim 5 is characterized in that: The determining of the fifth order value based on the sampling values ​​in the fourth peak period in the output simultaneity time series of the plurality of stations includes: Extracting a subsequence corresponding to the fourth peak period from the station output simultaneous rate time series to obtain a fourth peak output simultaneous rate sequence; Based on the preset sampling points, sampling and processing are respectively performed on the respective fourth peak output simultaneity rate sequences of the plurality of stations to obtain respective second output simultaneity rate sampling values ​​of the plurality of stations; The fifth order value is obtained based on the order of the second output simultaneity sampling value of the first target station among the second output simultaneity sampling values ​​of the plurality of second target stations.

8. The method for evaluating the frequency support capability of a new energy station according to claim 1 is characterized in that: The constructing the membership matrix of the first target site based on the test results of each of the plurality of evaluation sub-factors includes: Based on the test results of the evaluation sub-factors, determining the probability values ​​of the evaluation sub-factors corresponding to the respective evaluation levels; The membership matrix is ​​constructed based on the probability values ​​of the evaluation sub-factors corresponding to the plurality of evaluation levels.

9. A device for evaluating the frequency support capability of a new energy station based on output characteristics, characterized in that: The device comprises: A testing module, configured to respond to a frequency support capability evaluation request for a first target station, and to perform a frequency support capability test on the first target station when the first target station does not participate in frequency modulation, to obtain test results of each of a plurality of evaluation sub-factors of the first target station, wherein the evaluation index of the frequency support capability of the first target station includes a plurality of evaluation factors, and each evaluation factor includes a plurality of evaluation sub-factors; A construction module, configured to construct a membership matrix of the first target site based on the test results of each of the plurality of evaluation sub-factors; a weight determination module, configured to obtain evaluation weights of the plurality of evaluation factors based on active power data of each of the plurality of stations in a historical period, wherein the plurality of stations include the first target station and a plurality of second target stations, and the second target stations include new energy stations of the same type as the first target station and located in the same area; A result determination module, configured to obtain a frequency support capability evaluation result of the first target station based on the preset weights of the plurality of evaluation sub-factors, the evaluation weights of the plurality of evaluation factors, and the membership matrix; Wherein, when the first target site is a wind farm, the weight determination module is used to: Based on the active power data of each of the plurality of stations, obtaining a time series of output simultaneity rate of each of the plurality of stations; Determining a first sequence value based on a change rate of a sequence element in a time series of output simultaneity rates of each of the plurality of stations; Determining a second sequence value based on a subsequence corresponding to the first peak period in the output simultaneity time series of each of the plurality of stations; Determine a third order value based on the sampling values ​​in the second peak period in the output simultaneity time series of each of the plurality of stations; Based on the first ordinal value, the second ordinal value, and the third ordinal value, evaluation weights of the plurality of evaluation factors are obtained.

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