Method and device for evaluating active frequency support capability of photovoltaic power station

Abstract

The present invention relates to a method and device for evaluating the frequency active support capability of a photovoltaic power station. The method comprises constructing an index system of the frequency active support capability of a photovoltaic power station according to the needs of the photovoltaic power station for the frequency active support capability; obtaining the operation data and the primary frequency modulation curve of the photovoltaic power station, and calculating each index value in the index system according to the operation data and the primary frequency modulation curve; using the Parrot optimization algorithm to obtain the index weight value of each index; calculating the frequency active support capability performance value of the photovoltaic power station according to each index value and the corresponding index weight value; the frequency active support capability performance value is used to evaluate the active support capability of the photovoltaic power station. After constructing the index system of the photovoltaic power station, the present invention calculates each index value in the index system. The present application adopts the Parrot optimization algorithm to comprehensively evaluate the frequency active support capability of the photovoltaic power station, which is more objective and reliable, and has a higher accuracy.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power market, and in particular relates to a method and device for evaluating the active frequency support capability of a photovoltaic power station. Background Art

[0002] When the frequency of the power system fluctuates, the photovoltaic power station can actively adjust its output power to maintain the stability of the system frequency. The active frequency support capability is crucial to ensure the safe and stable operation of the power system. When photovoltaic power stations are connected to the power grid on a large scale, if there is a lack of sufficient active frequency support capability, once a frequency fluctuation occurs, it may cause the power system to collapse, causing serious economic losses and social impacts. Summary of the invention

[0003] In view of this, the purpose of the present invention is to overcome the deficiencies of the prior art and to provide a method and device for evaluating the active frequency support capability of a photovoltaic power station, so as to solve the problem of lack of sufficient active frequency support capability in the prior art.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A method for evaluating the frequency active support capability of a photovoltaic power station, comprising:

[0005] According to the needs of photovoltaic power stations for active frequency support capabilities, an indicator system for active frequency support capabilities of photovoltaic power stations is established;

[0006] Acquiring operation data and a primary frequency modulation curve of the photovoltaic power station, and calculating each indicator value in the indicator system according to the operation data and the primary frequency modulation curve;

[0007] The Parrot optimization algorithm is used to obtain the indicator weight value of each indicator;

[0008] According to each indicator value and the corresponding indicator weight value, the frequency active support capability performance value of the photovoltaic power station is calculated; the frequency active support capability performance value is used to evaluate the active support capability of the photovoltaic power station.

[0009] Furthermore, the indicator system includes primary indicators and secondary indicators under the primary indicators;

[0010] The first-level indicators include: frequency support index, primary frequency modulation index and inertia response index;

[0011] The secondary indicators under the frequency support index include: frequency steady-state deviation index, frequency maximum deviation index, frequency change index, frequency qualified rate index and frequency tolerance index;

[0012] The secondary indicators under the primary frequency modulation indicator include: active power limit indicator, response lag time indicator, rise time indicator, adjustment time indicator, active power regulation deviation indicator and active power frequency modulation coefficient indicator;

[0013] The secondary indicators under the inertia response indicator include: an inertia time constant indicator, an inertia response time indicator and an active climbing rate indicator.

[0014] Furthermore, the index values ​​in the index system are calculated based on the operating data and the primary frequency modulation curve.

[0015] The frequency steady-state deviation index is calculated in the following way:

[0016] Δf s =|f st -f N |

[0017] Where Δf s is the frequency steady-state deviation index, f st is the steady-state value of the frequency after the frequency modulation is completed, f N is the system rated frequency;

[0018] The frequency maximum deviation index is calculated in the following way,

[0019] Δf max =|f t -f N |

[0020] Where Δf max is the maximum frequency deviation index, f t It is the frequency value when the frequency deviation is the largest during the frequency modulation process;

[0021] The frequency change rate indicator is calculated in the following way,

[0022]

[0023] Among them, Δf is the frequency change rate index, df is the change of system frequency within the sampling period, and dt is the sampling period;

[0024] The frequency qualification rate index is calculated in the following way:

[0025]

[0026] Among them, f p is the frequency qualification rate index, t over is the frequency limit-crossing time, t total is the total statistical running time;

[0027] The frequency tolerance capability indicator is set to have a high frequency tolerance capability with a preset frequency threshold, and the operating time at the frequency of the preset frequency threshold is higher than a preset time period.

[0028] Furthermore, the index values ​​in the index system are calculated based on the operating data and the primary frequency modulation curve.

[0029] Among them, the active power limit index is a preset value;

[0030] The response lag time index is calculated in the following way,

[0031] t d =t 1 -t 0

[0032] Among them, t d is the response lag time indicator, t 0 is the start time of the FM response, t 1 It is the moment when the active power change reaches 10% of the power target value for the first time;

[0033] The rise time specification is calculated as follows,

[0034] t r =t 2 -t 0

[0035] Among them, t r is the rise time indicator, t 2 It is the moment when the active power change reaches 90% of the power target value for the first time;

[0036] The adjustment time index is calculated in the following way,

[0037] t s =t 4 -t 0

[0038] Among them, t s To adjust the time index, t 4 It is the starting time when the active power continuously operates within ±5% of the power target value;

[0039] The active power regulation deviation index is the ratio of the difference between the steady-state power value and the target power value to the rated power value;

[0040] The active frequency modulation coefficient index is calculated in the following way:

[0041]

[0042] Where ΔP t is the active frequency modulation coefficient index, that is, the change in active power of the primary frequency modulation of the photovoltaic power station; Δf is the frequency deviation of the photovoltaic power station grid connection point; P N is the rated active power of the photovoltaic power station; K is the set value.

[0043] Furthermore, the index values ​​in the index system are calculated based on the operating data and the primary frequency modulation curve.

[0044] The inertia time constant index is calculated in the following way,

[0045]

[0046] Where ΔP I is the inertia time constant index, that is, the change in active power of the photovoltaic power station inertia response; T J is the inertia response inertia time, T J is the set value;

[0047] Among them, the inertia response time indicator has a preset time threshold;

[0048] The active power climbing rate index is calculated in the following way:

[0049]

[0050] Among them, v wp is the active power climbing rate index, P 0 and P 1 are the initial value and target of the unit respectively; t 0 and t 3 They are the moment when the unit starts regulating and the moment when the regulation target is reached.

[0051] Furthermore, it also includes:

[0052] Normalize the values ​​of each indicator in the indicator system, including:

[0053] The index value in the index system is X=(x 1 ,x 2 ,L,x 14 );

[0054] Among them, X is the indicator matrix, x 1 , …x 14 There are 14 secondary indicator values;

[0055] The following method is used to normalize the values ​​of each indicator:

[0056]

[0057] Among them, y i is the standardized value, x i is the original value, max{x} is the upper limit of the indicator, and min{x} is the lower limit of the indicator;

[0058] The following methods are used to make negative indicators more consistent:

[0059] y′ i =1-y i

[0060] Get the standardized indicator matrix;

[0061] Y=(y 1 ,y 2 ,L,y 14 )

[0062] Among them, Y is the standardized indicator matrix, y 1 ,…y 14 These are the 14 standardized secondary indicator values.

[0063] Furthermore, the Parrot optimization algorithm is used to obtain the indicator weight value of each indicator, including:

[0064] Obtain the experts' weight evaluation matrix for all indicators in the indicator system;

[0065] The Parrot optimization algorithm is used in combination with the preset objective function to solve the weight evaluation matrix and obtain the indicator weight value of each indicator.

[0066] Furthermore, the objective function is

[0067]

[0068] in, is the kth expert's evaluation index v j The weight range of are the lower and upper limits of the value, respectively, a is the number of indicators, w j is the final weight of a indicators.

[0069] Furthermore, the voltage active support performance value of the photovoltaic power station is calculated in the following way:

[0070]

[0071] Among them, S is the voltage active support performance value of the photovoltaic power station, W is the weight value of each indicator, Y is the active support performance value of each indicator, and w b is the index weight of photovoltaic power station b, δ b is the index value of photovoltaic power station b.

[0072] The embodiment of the present application provides a photovoltaic power station frequency active support capability assessment device, comprising:

[0073] A construction module is used to construct an indicator system for active frequency support capability of a photovoltaic power station according to the needs of the photovoltaic power station for active frequency support capability;

[0074] An acquisition module, used to acquire the operation data and the primary frequency modulation curve of the photovoltaic power station, and calculate the values ​​of each indicator in the indicator system according to the operation data and the primary frequency modulation curve;

[0075] The obtaining module is used to obtain the indicator weight value of each indicator using the Parrot optimization algorithm;

[0076] The calculation module is used to calculate the frequency active support capability performance value of the photovoltaic power station according to each indicator value and the corresponding indicator weight value; the frequency active support capability performance value is used to evaluate the active support capability of the photovoltaic power station.

[0077] An embodiment of the present application provides a computer device, including: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of any one of the above-mentioned methods for evaluating the active frequency support capability of a photovoltaic power station.

[0078] An embodiment of the present application also provides a computer storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of any one of the above-mentioned methods for evaluating the active frequency support capability of a photovoltaic power station.

[0079] The present invention adopts the above technical solution, and the beneficial effects that can be achieved include:

[0080] The present invention provides a method and device for evaluating the frequency active support capability of a photovoltaic power station. This application constructs an index system for the frequency active support capability of a photovoltaic power station according to the needs of the photovoltaic power station for the frequency active support capability, and then calculates the values ​​of each index in the index system according to the operation data and the primary frequency modulation curve of the photovoltaic power station, uses the Parrot optimization algorithm to obtain the index weight value of each index, and calculates the frequency active support capability performance value of the photovoltaic power station to evaluate the active support capability of the photovoltaic power station. Through evaluation, this application can timely discover the problems and deficiencies in the frequency support of the photovoltaic power station, provide guidance for improving the control strategy of the power station and improving the performance of the power station, and thus achieve efficient utilization and sustainable development of energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0082] Figure 1 A schematic diagram of the steps of the method for evaluating the frequency active support capability of a photovoltaic power station according to the present invention;

[0083] Figure 2 It is a flow chart of a method for evaluating the frequency active support capability of a photovoltaic power station according to the present invention;

[0084] Figure 3 It is a schematic diagram of the variation curve of time and system frequency of the present invention;

[0085] Figure 4 It is a schematic diagram of a curve showing the change of time and the active power change of a new energy power station according to the present invention;

[0086] Figure 5 A flowchart of the steps of the parrot optimization algorithm provided by the present invention;

[0087] Figure 6 It is a structural schematic diagram of a device for evaluating the frequency active support capability of a photovoltaic power station according to the present invention;

[0088] Figure 7 It is a structural schematic diagram of the electronic equipment involved in the method for evaluating the active frequency support capability of a photovoltaic power station of the present invention. DETAILED DESCRIPTION

[0089] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0090] A specific method and device for evaluating the frequency active support capability of a photovoltaic power station provided in an embodiment of the present application are described below in conjunction with the accompanying drawings.

[0091] like Figure 1 As shown, the method for evaluating the frequency active support capability of a photovoltaic power station provided in the embodiment of the present application includes:

[0092] S101, based on the needs of photovoltaic power stations for active frequency support capabilities, construct an indicator system for active frequency support capabilities of photovoltaic power stations;

[0093] It can be understood that in this application, the historical operating data of the photovoltaic power station is collected, and an indicator system for the active frequency support capability of the photovoltaic power station is constructed through the historical operating data. The historical operating data in this application is collected based on the active support capability requirements of the power grid, and the operating data includes the frequency data of the sampling point.

[0094] S102, obtaining operation data and a primary frequency modulation curve of the photovoltaic power station, and calculating each indicator value in the indicator system according to the operation data and the primary frequency modulation curve;

[0095] It is understandable that in this application, it is first necessary to obtain the primary frequency modulation curve of the photovoltaic power station. Frequency is an important indicator for measuring power quality. Ensuring the frequency offset of the power system is a basic task for adjusting the power system. In this application, the primary frequency modulation curve is obtained through the frequency testing system of the photovoltaic power station. Frequency modulation test refers to changing the size and frequency of the external frequency signal within a certain frequency range to observe the response of the object under test to the frequency change. In a photovoltaic power station, a primary frequency modulation test is used to test the response characteristics of the photovoltaic inverter to external frequency changes. Through the frequency modulation test, parameters such as the stability, response speed and frequency range of the inverter can be evaluated.

[0096] Primary Frequency Control refers to the regulation of generator sets through automatic generator control systems in response to instantaneous changes in the power system frequency. When the power system load changes or a generator set fails, the power system frequency will shift for a short period of time. Primary frequency control is the process of quickly responding to frequency changes by increasing or decreasing the output power of the generator set to restore the frequency stability of the power system. In short, the primary frequency control of the power system is mainly the process of the generator set automatically responding to frequency changes to restore frequency stability in a short period of time.

[0097] Primary frequency regulation, also known as quick-break frequency regulation or fast frequency regulation, is an immediate response mechanism when a sudden load change or generator failure occurs in the power system. Primary frequency regulation achieves rapid regulation of the power system frequency through the mechanical inertia of the generator set and the feedback control of the automatic voltage regulator. When the power system frequency is low, the generator set will increase the output power; conversely, when the power system frequency is high, the generator set will reduce the output power. The response of primary frequency regulation is usually completed within a few seconds, and its main purpose is to restore the stability of the power system frequency.

[0098] S103, using the Parrot optimization algorithm to obtain the indicator weight value of each indicator;

[0099] It is understandable that this application invites multiple experts to conduct weighted evaluation on the indicators of the active frequency support capability of photovoltaic power stations. Considering the complexity of the problem, experts have inconsistent opinions on the weight coefficients of the evaluation indicators and cannot give a definite value, but a value range matrix can be obtained.

[0100] According to the set objective function, this application uses the Parrot optimization algorithm to solve the preset objective function to obtain the indicator weight value of each indicator.

[0101] S104, calculating a frequency active support capability performance value of the photovoltaic power station according to each indicator value and the corresponding indicator weight value; the frequency active support capability performance value is used to evaluate the active support capability of the photovoltaic power station.

[0102] Finally, the voltage active support performance value of the photovoltaic power station is calculated according to each indicator value and the corresponding indicator weight value, and the voltage active support performance value is used to evaluate the active support capability of the photovoltaic power station.

[0103] The method for evaluating the frequency active support capability of a photovoltaic power station provided in the present application constructs an index system for the frequency active support capability of a photovoltaic power station according to the needs of the photovoltaic power station for the frequency active support capability; obtains the operating data and the primary frequency modulation curve of the photovoltaic power station, and calculates the values ​​of each index in the index system according to the operating data and the primary frequency modulation curve; uses the Parrot optimization algorithm to obtain the index weight value of each index; calculates the frequency active support capability performance value of the photovoltaic power station according to each index value and the corresponding index weight value; the frequency active support capability performance value is used to evaluate the active support capability of the photovoltaic power station. After constructing the index system of the photovoltaic power station, the present invention calculates the values ​​of each index in the index system. The present application uses the Parrot optimization algorithm to comprehensively evaluate the frequency active support capability of the photovoltaic power station, which is more objective and reliable, and has a higher accuracy.

[0104] In some optional embodiments, Figure 2 As shown, the indicator system includes primary indicators and secondary indicators under the primary indicators;

[0105] The first-level indicators include: frequency support index, primary frequency modulation index and inertia response index;

[0106] The secondary indicators under the frequency support index include: frequency steady-state deviation index, frequency maximum deviation index, frequency change index, frequency qualified rate index and frequency tolerance index;

[0107] The secondary indicators under the primary frequency modulation indicator include: active power limit indicator, response lag time indicator, rise time indicator, adjustment time indicator, active power regulation deviation indicator and active power frequency modulation coefficient indicator;

[0108] The secondary indicators under the inertia response indicator include: an inertia time constant indicator, an inertia response time indicator and an active climbing rate indicator.

[0109] Specifically, Figure 2 As shown, the index system in this application is specifically an index system for evaluating the active frequency control capability of a photovoltaic power station. The index system includes first-level indicators such as frequency support index, primary frequency modulation index and inertia response index. Among them, the frequency support index includes frequency steady-state deviation index, frequency maximum deviation index, frequency change index, frequency qualified rate index and frequency tolerance index; the primary frequency modulation index includes active power limit index, response lag time index, rise time index, adjustment time index, active regulation deviation index and active frequency modulation coefficient index; the inertia response index includes inertia time constant index, inertia response time index and active climbing rate index.

[0110] In some optional embodiments, Figure 3 The curves of time and system frequency are shown as follows: Figure 4 The figure shows the change curve of time and active power change of new energy power station.

[0111] In some optional embodiments, the index values ​​in the index system are calculated based on the operating data and the primary frequency modulation curve.

[0112] This application is based on Figure 3 The frequency steady-state deviation index is calculated in the following way:

[0113] Δf s =|f st -f N | (1)

[0114] Where Δf s is the frequency steady-state deviation index, f st is the steady-state value of the frequency after the frequency modulation is completed, f N is the system rated frequency;

[0115] It should be noted that according to national standards, the frequency deviation limit under normal operation of the power system is ±0.2Hz, so the frequency steady-state deviation index limit is 0-0.2Hz. The smaller the frequency steady-state deviation, the better the frequency modulation response of the photovoltaic power station, so the smaller the frequency steady-state deviation, the better. In this application, the frequency steady-state deviation index value is 0.12Hz.

[0116] This application is based on Figure 3 The frequency maximum deviation index is calculated in the following way,

[0117] Δf max =|f t -f N | (2)

[0118] Where Δf max is the maximum frequency deviation index, f t The frequency value when the frequency deviation is the largest during the frequency modulation process; in this application, the maximum frequency deviation index limit is taken as 0-0.5Hz. A small maximum frequency deviation indicates that the photovoltaic power station frequency modulation response transient process performance is good, so the smaller the maximum frequency deviation during the frequency transient process, the better. This application obtains a maximum frequency deviation index value of 0.148Hz.

[0119] based on Figure 3 The frequency change rate indicator is calculated in the following way,

[0120]

[0121] Among them, Δf is the frequency change rate index, df is the change of the system frequency within the sampling period, and dt is the sampling period; in this application, the frequency change rate index limit is taken as 0-0.2Hz / s. A small frequency change rate indicates that the photovoltaic power station has a strong ability to resist frequency shocks, so the smaller the frequency change rate during the frequency transient process, the better. This application obtains that the frequency change rate index extreme value is 0.112Hz / s.

[0122] The frequency qualification rate index is calculated in the following way:

[0123]

[0124] Among them, f p is the frequency qualification rate index, t over is the frequency limit-crossing time, t total is the total statistical running time;

[0125] The frequency qualification rate in this application is a method of characterizing that the grid frequency is within the limit by monitoring and counting the frequency exceeding the limit time, and the limit is 0-100%. The higher the qualification rate, the better the performance of the photovoltaic power station. The frequency qualification rate analyzed in this application is 99.6%.

[0126] The frequency tolerance index is set to a high-frequency tolerance capability with a preset frequency threshold, and the operating time at the frequency of the preset frequency threshold is higher than the preset time period. In this application, the photovoltaic power station must have a 51.5Hz high-frequency tolerance capability, and the operating time at a frequency higher than 51.5Hz is not less than 2s. This indicator is reflected by the test pass rate. In the technical solution provided in this application, based on the photovoltaic power station operation data, the photovoltaic power station has a 51.5Hz high-frequency tolerance capability. The active power limit of the photovoltaic power station is set to 20% of the rated power, which is in line with national standards.

[0127] In some optional embodiments, the index values ​​in the index system are calculated based on the operating data and the primary frequency modulation curve.

[0128] Among them, the active power limit index is a preset value;

[0129] This application is based on Figure 4 The response lag time index is calculated in the following way,

[0130] t d =t 1 -t 0 (5)

[0131] Among them, t d is the response lag time indicator, t 0 is the start time of the FM response, t 1It is the moment when the active power change reaches 10% of the power target value for the first time; it should be noted that according to national standards, the primary frequency modulation response lag time of a photovoltaic power station should not be greater than 1s, so the response lag time index limit is 0-1s, and the shorter the response lag time, the better. In this application, the response lag time index value is 0.018s.

[0132] The rise time specification is calculated as follows,

[0133] t r =t 2 -t 0 (6)

[0134] Among them, t r is the rise time indicator, t 2 It is the moment when the active power change reaches 90% of the power target value for the first time; it should be noted that according to national standards, the frequency modulation rise time of a photovoltaic power station should not exceed 5s, so the rise time index limit is 0-5s, and the shorter the rise time, the better. The response lag time index value obtained in this application is 0.077s.

[0135] The adjustment time index is calculated in the following way,

[0136] t s =t 4 -t 0 (7)

[0137] Among them, t s To adjust the time index, t 4 It is the starting time when the active power continuously runs within ±5% of the power target value; it should be noted that according to national standards, the frequency regulation time of a photovoltaic power station should not exceed 15s, so the regulation time index limit is 0-15s, and the shorter the regulation time, the better. The response lag time index value obtained in this application is 9.008s.

[0138] Among them, it should be noted that the active regulation deviation index is the ratio of the difference between the steady-state power value and the target power value to the rated power value; according to national standards, the active regulation deviation of a photovoltaic power station is defined as the ratio of the difference between the steady-state power value and the target power value to the rated power value when performing power regulation, expressed as a percentage. The regulation time of a photovoltaic power station is no more than 15s. The photovoltaic power station should reach the steady-state power value within 15s. The steady-state power value and the target power value at 15s after the frequency modulation response occurs can be obtained to calculate the power control deviation. The active regulation deviation index limit is 0% to ±1%. The closer the regulation deviation is to 0%, the stronger the power regulation capability of the photovoltaic power station. In this application, according to Figure 4 The power response curve of the photovoltaic power station shows that the active power regulation deviation is 0.005%.

[0139] The active frequency modulation coefficient index is calculated in the following way:

[0140]

[0141] Where ΔP t is the active frequency modulation coefficient index, that is, the change in active power of the primary frequency modulation of the photovoltaic power station; Δf is the frequency deviation of the photovoltaic power station grid connection point; P N is the rated active power of the photovoltaic power station; K is the set value. It should be noted that according to national standards, the active frequency modulation coefficient of the photovoltaic power station ranges from 10 to 50, so the limit range is 10 to 50. From the perspective of frequency support capability, the larger the active frequency modulation coefficient, the better. In this application, the active frequency modulation coefficient index is the station set value of 50. The inertia time constant index is the station set value of 8s.

[0142] In some optional embodiments, the index values ​​in the index system are calculated based on the operating data and the primary frequency modulation curve.

[0143] The inertia time constant index is calculated in the following way,

[0144]

[0145] Where ΔP I is the inertia time constant index, that is, the change in active power of the photovoltaic power station inertia response; T J is the inertia response inertia time, T J is the set value; according to national standards, the inertia time constant of the inertia response of a photovoltaic power station is generally set to 3s to 12s. From the perspective of frequency support capability, the larger the inertia time constant, the better.

[0146] Among them, the inertia response time indicator has a preset time threshold; for the inertia response time indicator, according to the national standard photovoltaic power station inertia response, the active power change provided should not be less than 0.1P N ; When the frequency exceeds the limit, the initial df / dt value is relatively large, so the power change provided by the inertia response is greater than 0.1P N Meets the requirements; when the frequency approaches the lowest point, the frequency change slows down, and the power change rate provided by the inertia response is less than 0.1P N , it can be considered that the effect of inertia response is reduced and the inertia response gradually exits. Limit the frequency to the point where the power change rate provided by the inertia response is less than 0.1P N The time of this process is recorded as the inertia response time. The inertia response time index is 0 to 500ms, and the shorter the inertia response time, the better. Figure 4 It can be seen that the inertia response time index obtained from the power response curve of the photovoltaic power station is 340ms.

[0147] The active power climbing rate index is calculated in the following way:

[0148]

[0149] Among them, v wp is the active power climbing rate index, P 0 and P 1 are the initial value and target of the unit respectively; t 0 and t 3 They are the moment when the unit starts regulating and the moment when the regulation target is reached. In this application, the active climbing rate index limit is 0-0.2pu / s. A large active climbing rate indicates that the photovoltaic power station has a fast power regulation speed and a strong ability to cope with frequency shocks. Therefore, the larger the active climbing rate, the better. In this application, the response lag time index value is 0.068pu / s.

[0150] In some optional embodiments, the method for evaluating the frequency active support capability of a photovoltaic power station provided by the present application further includes: normalizing each indicator value in the indicator system, specifically including:

[0151] The index value in the index system is X=(x 1 ,x 2 ,L,x 14 );

[0152] Among them, x 1 , …x 14 There are 14 secondary indicator values; for example, x 1 is the frequency steady-state deviation index, x 2 is the maximum frequency deviation index, x 3 is the frequency change rate index, x 4 is the frequency qualification rate index, x 5 is the frequency tolerance index; x 6 is the active power limit index, x 7 is the response lag time indicator, x 8 is the rise time indicator, x 9 To adjust the time index, x 10 is the active power regulation deviation index, x 11 is the active frequency modulation coefficient index, x 12 is the inertia time constant index, x 13 is the inertia response time index and x 14 is the active power ramp rate index. The indexes obtained from different sampling points are integrated to obtain the index matrix.

[0153] The following method is used to normalize the values ​​of each indicator:

[0154]

[0155] Among them, y i is the standardized value, x i is the original value, max{x} is the upper limit of the indicator, and min{x} is the lower limit of the indicator;

[0156] The following methods are used to make negative indicators more consistent:

[0157] y′ i =1-y i (12)

[0158] Get the standardized indicator matrix;

[0159] Y=(y 1 ,y 2 ,L,y 14 ) (13)

[0160] Among them, Y is the standardized indicator matrix, y1,…y14 are 14 standardized secondary indicator values.

[0161] Specifically, the maximum and minimum normalization and isotropic normalization methods are used in this application for standardization. For example, the values ​​of each indicator after standardization are:

[0162] Y=(0.4,0.704,0.44,0.996,1,1,0.982,0.9846,0.399,0.995,1,0.56,0.32,0.34) (14)

[0163] In some optional embodiments, the Parrot optimization algorithm is used to obtain the indicator weight value of each indicator, including:

[0164] Obtain the experts' weight evaluation matrix for all indicators in the indicator system;

[0165] The Parrot optimization algorithm is used in combination with the preset objective function to solve the weight evaluation matrix and obtain the indicator weight value of each indicator.

[0166] In one embodiment, 20 experts are invited to evaluate the weights of 14 indicators of the active frequency support capability of photovoltaic power stations. Considering the complexity of the problem, experts have inconsistent opinions on the weight coefficients of the 14 evaluation indicators and cannot give a definite value, but a value range matrix B is given:

[0167]

[0168] Consider the objective function comprehensively:

[0169]

[0170] Specifically, Figure 5As shown, the process of using the parrot algorithm in this application is:

[0171] First, consider the population size as N, the maximum number of iterations as Max_iter, and the upper and lower limits of the search space as ub and lb. The parrot algorithm can be initialized as:

[0172]

[0173] Among them, rand(0,1) generates a random number between 0 and 1; is the initial position of the i-th parrot.

[0174] Consider the foraging behavior of parrots, they estimate the approximate location of food mainly by observing the location of the food or considering the location of the owner, and then fly to the corresponding location. Therefore, the position movement follows the following formula:

[0175]

[0176] In the formula, Represents the updated position; Represents the current position; X best represents the best position searched, Levy(dim) represents Levy distribution; Represents the average position of the population.

[0177] The Levy calculation formula is:

[0178]

[0179] The calculation formula is:

[0180]

[0181] Consider the parrot's perching behavior, which is mainly manifested by suddenly flying to any part of the owner's body and staying there for a period of time. This process can be expressed as:

[0182]

[0183] Where ones(1,dim) represents a vector of all 1s of dimension dim.

[0184] Consider the communication behavior of parrots, which are naturally social animals characterized by close communication in groups. This communication behavior includes flying toward the flock and not flying toward the flock. Assuming that the probability of these two behaviors is equal, this process can be expressed as:

[0185]

[0186] Where P is a random number in the range of (0,1).

[0187] Consider the fearful behavior of parrots towards strangers. Generally speaking, birds show an innate fear of strangers, and parrots are no exception. They keep their distance from strange individuals and seek a safe environment with their owners:

[0188]

[0189] Assume that there are n experts p 1 ,p 2 ,…,p n The weight evaluation of m (m=14) indicators of the active frequency support capability of photovoltaic power stations is carried out, and the evaluation weight matrix is:

[0190]

[0191] Considering the complexity of the problem, experts have inconsistent opinions on the weight coefficients of the m evaluation indicators. It is impossible to give a definite value, but a range of values ​​can be given. is the kth expert's evaluation index v j The weight range of are the lower and upper limits of the values ​​respectively. Now we need to obtain the final weight w of the m indicators through negotiation j , and minimize the objections of each expert, so as to solve the objective function and obtain the weight value of each indicator:

[0192] W=[w 1 w 2 L m ] (twenty four)

[0193] In some optional embodiments, the voltage active support performance value of the photovoltaic power station is calculated in the following manner:

[0194]

[0195] Among them, S is the voltage active support performance value of the photovoltaic power station, W is the weight value of each indicator, Y is the active support performance value of each indicator, and w b is the index weight of photovoltaic power station b, δ b is the index value of photovoltaic power station b.

[0196] This application breaks down the active frequency support capability of photovoltaic stations into 14 detailed indicators such as frequency steady-state deviation to construct an evaluation index system, which can reflect the active support capability of photovoltaic power stations; this application uses the Parrot optimization algorithm to solve the possible problem of inconsistent opinions among evaluators, and the resulting index weights are more objective and reliable; the final evaluation results are presented in the form of evaluation values, which are highly intuitive.

[0197] like Figure 6As shown, the embodiment of the present application provides a photovoltaic power station frequency active support capability evaluation device, comprising:

[0198] A construction module 601 is used to construct an indicator system of the active frequency support capability of a photovoltaic power station according to the needs of the photovoltaic power station for the active frequency support capability;

[0199] An acquisition module 602 is used to acquire the operation data and the primary frequency modulation curve of the photovoltaic power station, and calculate the value of each indicator in the indicator system according to the operation data and the primary frequency modulation curve;

[0200] The obtaining module 603 is used to obtain the indicator weight value of each indicator by using the Parrot optimization algorithm;

[0201] The calculation module 604 is used to calculate the frequency active support capability performance value of the photovoltaic power station according to each indicator value and the corresponding indicator weight value; the frequency active support capability performance value is used to evaluate the active support capability of the photovoltaic power station.

[0202] The photovoltaic power station frequency active support capability evaluation device provided in the present application comprises a construction module 601 that constructs an index system for the photovoltaic power station frequency active support capability according to the photovoltaic power station's need for frequency active support capability; an acquisition module 602 that acquires the operating data and the primary frequency modulation curve of the photovoltaic power station, and calculates each index value in the index system according to the operating data and the primary frequency modulation curve; a calculation module 603 that uses the Parrot optimization algorithm to calculate the index weight value of each index; a calculation module 604 that calculates the performance value of the photovoltaic power station frequency active support capability according to each index value and the corresponding index weight value; the frequency active support capability performance value is used to evaluate the photovoltaic power station's active support capability.

[0203] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.

[0204] Figure 7 A schematic block diagram of an example electronic device 700 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0205] like Figure 7As shown, the device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0206] A number of components in the device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0207] The computing unit 701 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 701 performs the various methods and processes described above, such as a method for evaluating the frequency active support capability of a photovoltaic power station. For example, in some embodiments, the method for evaluating the frequency active support capability of a photovoltaic power station may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the method for evaluating the frequency active support capability of a photovoltaic power station described above may be performed. Alternatively, in other embodiments, the calculation unit 701 may be configured to execute the method for evaluating the active frequency support capability of a photovoltaic power station in any other appropriate manner (for example, by means of firmware).

[0208] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0209] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0210] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0211] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0212] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0213] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0214] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0215] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0216] The above is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for evaluating the frequency active support capability of a photovoltaic power station, characterized in that: include: According to the needs of photovoltaic power stations for active frequency support capabilities, an indicator system for active frequency support capabilities of photovoltaic power stations is established; Acquiring operation data and a primary frequency modulation curve of the photovoltaic power station, and calculating each indicator value in the indicator system according to the operation data and the primary frequency modulation curve; The Parrot optimization algorithm is used to obtain the indicator weight value of each indicator; According to the values ​​of each indicator and the corresponding indicator weight values, the performance value of the frequency active support capability of the photovoltaic power station is calculated; The frequency active support capability performance value is used to evaluate the active support capability of the photovoltaic power station; The indicator system includes primary indicators and secondary indicators under the primary indicators; The first-level indicators include: frequency support index, primary frequency modulation index and inertia response index; The secondary indicators under the frequency support index include: frequency steady-state deviation index, frequency maximum deviation index, frequency change index, frequency qualified rate index and frequency tolerance index; The secondary indicators under the primary frequency modulation indicator include: active power limit indicator, response lag time indicator, rise time indicator, adjustment time indicator, active power regulation deviation indicator and active power frequency modulation coefficient indicator; The secondary indicators under the inertia response indicator include: inertia time constant indicator, inertia response time indicator and active climbing rate indicator; The index values ​​in the index system are calculated based on the operation data and the primary frequency modulation curve. The frequency steady-state deviation index is calculated in the following way: Δf s =f st -f N Where Δf s is the frequency steady-state deviation index, f st is the steady-state value of the frequency after the frequency modulation is completed, f N is the system rated frequency; The frequency maximum deviation index is calculated in the following way, Δf max =f t -f N Where Δf max is the maximum frequency deviation index, f t It is the frequency value when the frequency deviation is the largest during the frequency modulation process; The frequency change rate indicator is calculated in the following way, Among them, Δf is the frequency change rate index, df is the change of system frequency within the sampling period, and dt is the sampling period; The frequency qualification rate index is calculated in the following way: Among them, f p is the frequency qualification rate index, t over is the frequency limit-crossing time, t total is the total statistical running time; The frequency tolerance capability indicator is set to have a high frequency tolerance capability with a preset frequency threshold, and the operating time at the frequency of the preset frequency threshold is higher than a preset time period; The index values ​​in the index system are calculated based on the operation data and the primary frequency modulation curve. Among them, the active power limit index is a preset value; The response lag time index is calculated in the following way, t d =t1-t0 Among them, t d is the response lag time indicator, t0 is the start time of frequency modulation response, and t1 is the time when the active power change reaches 10% of the power target value for the first time; The rise time specification is calculated as follows, t r =t2-t0 Among them, t r is the rise time indicator, t2 is the moment when the active power change reaches 90% of the power target value for the first time; The adjustment time index is calculated in the following way, t s =t4-t0 Among them, t s To adjust the time index, t4 is the start time when the active power continuously operates within ±5% of the power target value; The active power regulation deviation index is the ratio of the difference between the steady-state power value and the target power value to the rated power value; The active frequency modulation coefficient index is calculated in the following way: Where ΔP t is the active frequency modulation coefficient index, that is, the change in active power of the primary frequency modulation of the photovoltaic power station; Δf is the frequency deviation of the photovoltaic power station grid connection point; P N is the rated active power of the photovoltaic power station; K is the set value; The index values ​​in the index system are calculated based on the operation data and the primary frequency modulation curve. The inertia time constant index is calculated in the following way, Among them, ΔP I is the inertia time constant index, that is, the change in active power of the photovoltaic power station inertia response; T J is the inertia response inertia time, T J is the set value; Among them, the inertia response time indicator has a preset time threshold; The active power climbing rate index is calculated in the following way: Among them, v wp is the active power climbing rate indicator, P0 and P1 are the initial value and target of the unit respectively; t0 and t3 are the time when the unit starts to adjust and the time when it reaches the adjustment target respectively.

2. The method according to claim 1, characterized in that Also includes: Normalize the values ​​of each indicator in the indicator system, including: The index values ​​in the index system are X=(x1,x2,L,x 14 ); Among them, X is the indicator matrix, x 1， …x 14 There are 14 secondary indicator values; The following method is used to normalize the values ​​of each indicator: Among them, y i is the standardized value, x i is the original value, max{x} is the upper limit of the indicator, and min{x} is the lower limit of the indicator; The following methods are used to make negative indicators more consistent: and' i =1-y i Get the standardized indicator matrix; Y=(y1,y2,L,y 14 ) Among them, Y is the standardized indicator matrix, y 1， …y 14 These are the 14 standardized secondary indicator values.

3. The method according to claim 1, characterized in that The Parrot optimization algorithm is used to obtain the indicator weight value of each indicator, including: Obtain the experts' weight evaluation matrix for all indicators in the indicator system; The Parrot optimization algorithm is used in combination with the preset objective function to solve the weight evaluation matrix and obtain the indicator weight value of each indicator.

4. The method according to claim 3, characterized in that The objective function is in, is the kth expert's evaluation index v j The weight range of are the lower and upper limits of the value, respectively, a is the number of indicators, w j is the final weight of a indicators.

5. The method according to claim 1, characterized in that The voltage active support performance value of the photovoltaic power station is calculated in the following way: Among them, S is the voltage active support performance value of the photovoltaic power station, W is the weight value of each indicator, Y is the active support performance value of each indicator, and w b is the index weight of photovoltaic power station b, δ b is the index value of photovoltaic power station b.

6. A photovoltaic power station frequency active support capability assessment device, characterized in that: include: A construction module is used to construct an indicator system for active frequency support capability of a photovoltaic power station according to the needs of the photovoltaic power station for active frequency support capability; An acquisition module, used to acquire the operation data and the primary frequency modulation curve of the photovoltaic power station, and calculate the values ​​of each indicator in the indicator system according to the operation data and the primary frequency modulation curve; The obtaining module is used to obtain the indicator weight value of each indicator using the Parrot optimization algorithm; A calculation module, used to calculate the frequency active support capability performance value of the photovoltaic power station according to each indicator value and the corresponding indicator weight value; The frequency active support capability performance value is used to evaluate the active support capability of the photovoltaic power station; The indicator system includes primary indicators and secondary indicators under the primary indicators; The first-level indicators include: frequency support index, primary frequency modulation index and inertia response index; The secondary indicators under the frequency support index include: frequency steady-state deviation index, frequency maximum deviation index, frequency change index, frequency qualified rate index and frequency tolerance index; The secondary indicators under the primary frequency modulation indicator include: active power limit indicator, response lag time indicator, rise time indicator, adjustment time indicator, active power regulation deviation indicator and active power frequency modulation coefficient indicator; The secondary indicators under the inertia response indicator include: inertia time constant indicator, inertia response time indicator and active climbing rate indicator; The index values ​​in the index system are calculated based on the operation data and the primary frequency modulation curve. The frequency steady-state deviation index is calculated in the following way: Δf s =f st -f N Where Δf s is the frequency steady-state deviation index, f st is the steady-state value of the frequency after the frequency modulation is completed, f N is the system rated frequency; The frequency maximum deviation index is calculated in the following way, Δf max =f t -f N Where Δf max is the maximum frequency deviation index, f t It is the frequency value when the frequency deviation is the largest during the frequency modulation process; The frequency change rate indicator is calculated in the following way, Among them, Δf is the frequency change rate index, df is the change of system frequency within the sampling period, and dt is the sampling period; The frequency qualification rate index is calculated in the following way: Among them, f p is the frequency qualification rate index, t over is the frequency limit-crossing time, t total is the total statistical running time; The frequency tolerance capability indicator is set to have a high frequency tolerance capability with a preset frequency threshold, and the operating time at the frequency of the preset frequency threshold is higher than a preset time period; The index values ​​in the index system are calculated based on the operation data and the primary frequency modulation curve. Among them, the active power limit index is a preset value; The response lag time index is calculated in the following way, t d =t1-t0 Among them, t d is the response lag time indicator, t0 is the start time of frequency modulation response, and t1 is the time when the active power change reaches 10% of the power target value for the first time; The rise time specification is calculated as follows, t r =t2-t0 Among them, t r is the rise time indicator, t2 is the moment when the active power change reaches 90% of the power target value for the first time; The adjustment time index is calculated in the following way, t s =t4-t0 Among them, t s To adjust the time index, t4 is the start time when the active power continuously operates within ±5% of the power target value; The active power regulation deviation index is the ratio of the difference between the steady-state power value and the target power value to the rated power value; The active frequency modulation coefficient index is calculated in the following way: Among them, ΔP t is the active frequency modulation coefficient index, that is, the change in active power of the primary frequency modulation of the photovoltaic power station; Δf is the frequency deviation of the photovoltaic power station grid connection point; P N is the rated active power of the photovoltaic power station; K is the set value; The index values ​​in the index system are calculated based on the operation data and the primary frequency modulation curve. The inertia time constant index is calculated in the following way, Among them, ΔP I is the inertia time constant index, that is, the change in active power of the photovoltaic power station inertia response; T J is the inertia response inertia time, T J is the set value; Among them, the inertia response time indicator has a preset time threshold; The active power climbing rate index is calculated in the following way: Among them, v wp is the active power climbing rate indicator, P0 and P1 are the initial value and target of the unit respectively; t0 and t3 are the time when the unit starts to adjust and the time when it reaches the adjustment target respectively.

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