AGC (Automatic Generation Control) optimization regulation and control method considering differential response capability of photovoltaic station inverter

Abstract

The embodiment of the invention discloses an AGC optimization regulation and control method considering the differential response capability of a photovoltaic station inverter, and belongs to the technical field of photovoltaic power generation system control and optimization. According to the method, on the basis of a photovoltaic field station mathematical model considering equivalent resistance loss in a field station, according to data such as a prediction system and real-time weather, in combination with the real-time operation states of the inverters, the inverters capable of being counted into AGC adjusting capacity are screened according to the health degree, and the scheduling accuracy is improved; on the basis, the inverters are classified by taking the adjusting speed as a standard, and active power constraint conditions are set, so that the inverters are quickly adjusted to act in advance, and the power generation efficiency of the photovoltaic field station is improved to the maximum extent while reasonable power distribution of the inverters in the field station is realized. The method can be applied to a large-scale photovoltaic power generation grid-connected system, the accuracy of a photovoltaic power station in power dispatching can be improved, and the economical efficiency and stability of system operation are improved.

Description

Technical Field

[0001] The present application relates to an AGC optimization control method that takes into account the differentiated response capabilities of photovoltaic station inverters, and belongs to the technical field of photovoltaic power generation system control and optimization. Background Art

[0002] Photovoltaic power generation, as a green and renewable energy source, has been widely used in recent years. With the continuous expansion of the scale of photovoltaic stations, how to efficiently, safely and stably regulate the power output of photovoltaic stations has become an important issue in the operation of power systems. AGC technology automatically adjusts the output power of the unit to balance the difference between power generation and load, and improves the stability of the system to a certain extent. It has become an important technical means for large-scale power networks and renewable energy access systems. For photovoltaic stations, the traditional scheduling method is to divide each inverter into equal values. The response speed and regulation ability of each inverter will be affected by factors such as solar irradiance and temperature, which will cause differences in the response ability of the inverter, making it impossible for the traditional AGC method to fully utilize the regulation potential of photovoltaic stations.

[0003] Domestic and foreign scholars have conducted extensive research on the differentiated response capabilities of photovoltaic station inverters and AGC optimization and control methods. In terms of the differentiated response capabilities of photovoltaic station inverters, the response characteristics of each inverter are analyzed, and its dynamic response capabilities are integrated into the AGC optimization algorithm to cooperate with the coordinated control of photovoltaic stations and power grids; in terms of AGC optimization and control, by establishing a power generation prediction model, a power grid load prediction model, and an inverter response model, an AGC dynamic optimization and control strategy that considers constraints and target settings is proposed based on big data analysis and real-time data feedback. Due to the wide variety of inverter models and large differences in technical levels, the output uncertainty of photovoltaic stations is strong. Therefore, it is necessary to evaluate the active output of photovoltaic stations and design an optimization and control method that considers the response speed and regulation capability of the inverter to avoid photovoltaic abandonment, improve the adaptability and accuracy of photovoltaic power stations in power dispatching, and improve the economy and stability of system operation. Summary of the invention

[0004] In order to solve the above-mentioned technical problems, the embodiments of the present application provide an AGC optimization and control method that takes into account the differentiated response capabilities of photovoltaic station inverters, so as to solve the following technical problems: the traditional method is to equally divide the power of each inverter in the photovoltaic station on the basis of analyzing and calculating the active power demand of the power grid, without considering the differences in the specific working points of each converter, resulting in poor active power tracking effect; if the power processing of the photovoltaic station is limited and cannot be adjusted to the maximum allowable value, it will lead to abandoned light losses.

[0005] Specifically, this application analyzes the differences in response speed and regulation capability of each inverter in the photovoltaic station, and finally forms a complete set of AGC optimization control methods that consider the differentiated response capability of photovoltaic station inverters. This method can evaluate the active output of photovoltaic stations, reasonably allocate the power required by each inverter, and improve the stability and economy of the system. In terms of photovoltaic station modeling, the loss caused by the equivalent resistance is taken into account, the maximum active power that can be output by the station is solved, and a mathematical model of the active power and efficiency of the inverter is constructed; in terms of the evaluation of the active output of photovoltaic stations, according to the real-time operating status of each inverter, combined with the inverters in the station, the prediction system, the real-time meteorological data, etc., the inverters that can be included in the AGC regulation capability calculation are screened and verified; in terms of the power distribution of the inverter, by setting a model inverter, other inverters are classified according to the regulation speed, and the fast-adjusting inverter is switched first, so as to achieve rapid regulation and reasonable distribution of active power.

[0006] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0007] According to one aspect of an embodiment of the present application, an AGC optimization control method considering differentiated response capabilities of photovoltaic station inverters is provided, the method comprising:

[0008] According to the dynamic operation of photovoltaic stations, a mathematical model of photovoltaic stations is established;

[0009] Based on the mathematical model of the photovoltaic station and according to the actual operating conditions of the inverter, an inverter with a characteristic correlation greater than a set threshold is calculated as a model inverter, and the model inverter is screened, and the AGC regulation capability of the photovoltaic power station is calculated and verified according to the screening results;

[0010] Power allocation is performed based on the differentiated response capabilities of inverters.

[0011] Furthermore, according to the dynamic operation of the photovoltaic station, a mathematical model of the photovoltaic station is established, including:

[0012] According to the set ideal factor, the current flowing through the photovoltaic station is obtained by the following formula:

[0013]

[0014] Where: I is the current flowing through the photovoltaic station, I PV is the photocurrent; I 0 is the saturation current; n is the ideal factor; T cell is the battery temperature; V is the terminal voltage; R s and R sh are series resistance and parallel resistance respectively; q is the charge number; e is the exponential function; k is the number of batteries;

[0015] According to the ambient temperature and solar radiation, the operating temperature of the module is determined by the following formula:

[0016]

[0017] Where: T CELL is the operating temperature of the component; T amb is the ambient temperature; G is the solar radiation terminal voltage; T NOCT is the test temperature of the component;

[0018] Based on the fill factor, the short-circuit current and open-circuit voltage are obtained by the following formula:

[0019]

[0020] Where: FF CELL I is the conversion efficiency of the battery's theoretical power; MPP and V MPP are the theoretical values ​​of current and voltage respectively; I SC 、V OC are short-circuit current and open-circuit voltage respectively; I OC.moment , U OC.moment are the current and voltage corresponding to the start of iteration respectively; FF 0 is the initial filling factor; P Nom is the input power of the battery;

[0021] At the open circuit point, the I and V values ​​are iteratively generated using formula (1-1), and the maximum power output of the photovoltaic station is obtained as follows:

[0022] P DCmax =max(I,V) (1-4)

[0023] Where: P DCmax is the maximum power output by the photovoltaic station; V is the voltage of the photovoltaic station; I is the current flowing through the photovoltaic station;

[0024] Active resistance is used to characterize the loss at the connection between the generator and the inverter in the photovoltaic power station; wherein the expression for the loss at the connection between the generator and the inverter in the photovoltaic power station is:

[0025] ΔP DC.CAB =RI 2 (1-5)

[0026] Where: ΔP DC.CAB is the loss at the connection between the generator and the inverter in the photovoltaic power station; R is the equivalent active resistance;

[0027] With the inverter as the intermediary between the photovoltaic power station and the power grid, the relationship between the inverter output power and efficiency is obtained through the following formula:

[0028] y=a 1 x n +a 2 x n-1 +K+a n x+a n+1 (1-6)

[0029] Where: x is the inverter output power; y is the inverter efficiency; a 1 、a 2 、a n 、a n+1 are the coefficients of the inverter output power respectively; n is the power of the inverter output power.

[0030] Furthermore, the sample inverter is screened, and the AGC regulation capability of the photovoltaic power station is calculated and verified according to the screening result, including:

[0031] By gathering the inverters, forecasting systems, and real-time meteorological data in the photovoltaic station, the real-time operating status of each inverter in the photovoltaic station is obtained based on comprehensive analysis of big data; wherein the real-time operating status includes free power generation status, planned maintenance status, unplanned shutdown status, standby status, and communication interruption status;

[0032] According to the real-time operating status of the inverter, the number of interruptions of the inverter is determined as the health degree;

[0033] Based on the preset health degree, the inverters having a health degree greater than the preset health degree are screened out as the screening result;

[0034] The AGC regulation capability of the photovoltaic power station is calculated and verified based on the screening results.

[0035] Furthermore, the AGC regulation capability of the photovoltaic power station is calculated and verified based on the screening results, including:

[0036] The upper limit of the active power adjustable of the photovoltaic power station is used as an indicator for verifying the AGC adjustment capability of the photovoltaic power station; wherein, the calculation formula of the upper limit of the active power adjustable of the photovoltaic power station is:

[0037] P max =P t N (2-1)

[0038] Where: P max P is the upper limit of the active power adjustable of the photovoltaic power station; t is the instantaneous active power of the inverter model; N is the total number of inverters in the photovoltaic power station.

[0039] Furthermore, power allocation is performed based on the differentiated response capability of the inverter, including:

[0040] According to the operating characteristics and adjustment speeds of the screened inverters, the inverters are divided into Class 1 inverters and Class 2 inverters; by determining the input sequence of each inverter and the power value allocated to it, the output power of the photovoltaic station meets the active power instruction within the set time, and power balance is performed on inverters with different adjustment speeds.

[0041] Furthermore, according to the operating characteristics and adjustment speeds of the screened inverters, the inverters are divided into Class 1 inverters and Class 2 inverters; by determining the order of input of each inverter and the power value allocated, the output power of the photovoltaic station meets the active power instruction within the set time, and the power balance of inverters with different adjustment speeds is performed, including:

[0042] Comparing the response time and control adjustment time of the screened inverters, the inverters are divided into a first-category inverter and a second-category inverter; wherein the adjustment speed of the first-category inverter is less than the adjustment speed of the second-category inverter;

[0043] The time taken to execute a distribution strategy during the active power regulation process is determined by the following formula as the total inverter output power for one regulation cycle:

[0044]

[0045] Where: P j P is the total output power of the j-th inverter in the previous regulation cycle; ji N is the output power of the i-th inverter of type j put into operation in the last regulation cycle; um_j is the number of j-th inverters put into operation; i represents the serial number of the inverter, j represents the category of the inverter, j=1, 2, when j=1, it means the inverter is a first-category inverter, when j=2, it means the inverter is a second-category inverter;

[0046] The active power reference value of the i-th inverter is determined by the following formula:

[0047] P i_min ≤P i_ref ≤P i_fore (3-2)

[0048] Where: P i_min is the minimum starting power; P i_fore is the maximum predicted power generation; P i_ref is the active power reference value of the i-th inverter;

[0049] Taking the sample inverter as the standard, let P i_fore =P miv_max , P i_min =P miv_min , transform formula (3-2) into:

[0050] P miv_min ≤P i_ref ≤P miv_max (3-3)

[0051] Where: P miv_min and P miv_fore They are the minimum starting power and maximum predicted power of the sample inverter respectively;

[0052] When the currently running inverter cannot meet the power regulation instruction, the second-class inverter is switched on and off first. The active power reference value of the second-class inverter is:

[0053]

[0054] Where: P ref The active power regulation command received by the photovoltaic power station; ΔP ref P is the power regulation task undertaken by the inverters other than the sample inverter in the current regulation cycle; pref The active power reference value of the Category 2 inverter planned to be put into operation in the current regulation cycle; P 1 The power borne by the first category inverter; N 2 The number of Category 2 inverters planned to be put into operation for the current regulation cycle;

[0055] In the power regulation process, the power reference values ​​of the two types of inverters are the same, and P 1i =P 2i , while achieving fast power regulation, retaining the regulation capability of the second type inverter and allowing the first type inverter to participate in power regulation:

[0056] When ΔP 2 <P 2_min When the power is fully borne by the first-class inverter, that is:

[0057]

[0058] Where: P 1i_rw N is the regulation task assigned to the i-th inverter of the first category in the current regulation cycle; um_1_1 is the number of inverters of type 1; ΔP 2 The power regulation target value of the Class 2 inverter planned to be put into operation in the current regulation cycle; P 2_min The minimum power value that can be provided by a Category 2 inverter;

[0059] During the power regulation process, the power regulation target value P of the i-th inverter of the first category in the current regulation cycle is 1i_ref for:

[0060]

[0061] Where: P 1i_ref P is the power regulation target value of the i-th inverter of the first category planned to be put into use in the current regulation cycle; 1i_rw The regulation task assigned to the i-th inverter of category 1 in the current regulation cycle.

[0062] According to one aspect of an embodiment of the present application, an AGC optimization control device considering the differentiated response capability of a photovoltaic station inverter is provided, comprising:

[0063] A model building module is configured to build a mathematical model of the photovoltaic station according to the photovoltaic station in operation dynamics;

[0064] The evaluation and analysis module is configured to calculate, based on the mathematical model of the photovoltaic station and according to the actual operating conditions of the inverter, inverters with characteristic correlation greater than a set threshold as sample inverters, screen the sample inverters, and calculate and verify the AGC regulation capability of the photovoltaic power station according to the screening results;

[0065] The power distribution module is configured to distribute power based on the differentiated response capabilities of the inverters.

[0066] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: a controller; and a memory for storing one or more programs, wherein when the one or more programs are executed by the controller, the controller implements the above-mentioned AGC optimization control method that takes into account the differentiated response capabilities of photovoltaic station inverters.

[0067] According to one aspect of an embodiment of the present application, a computer-readable storage medium is also provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer executes the above-mentioned AGC optimization and control method that takes into account the differentiated response capabilities of photovoltaic station inverters.

[0068] According to one aspect of the embodiments of the present application, a computer program product or a computer program is also provided, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the above-mentioned AGC optimization control method considering the differentiated response capability of the photovoltaic station inverter.

[0069] The technical solution provided in the embodiments of the present application has at least the following advantages:

[0070] This application makes full use of the AGC regulation capability while achieving reasonable distribution of power to each inverter. On the basis of calculating the AGC regulation capability, the response speed of the inverter is considered, and it is classified and the fast-regulating inverter is switched on first to achieve the output power of the photovoltaic power station to meet the active power instruction in a short time, and the power is distributed to other inverters, thereby improving the accuracy and rapidity of the power regulation of the photovoltaic power station and enhancing the regulation capacity of the photovoltaic power station.

[0071] The present application can be applied to large-scale photovoltaic power generation grid-connected systems, which can improve the adaptability and accuracy of photovoltaic power stations in power dispatching, and enhance the economy and stability of system operation.

[0072] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0074] Figure 1 It is an overall flow chart of an AGC optimization control method considering the differentiated response capability of photovoltaic station inverters shown in an exemplary embodiment of the present application;

[0075] Figure 2 It is a structural diagram of an AGC optimization and control device that takes into account the differentiated response capabilities of photovoltaic station inverters, shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0076] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims.

[0077] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0078] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0079] The term "multiple" as used in this application refers to two or more than two. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0080] One aspect of the present application provides an AGC optimization control method that takes into account the differentiated response capabilities of photovoltaic station inverters, fully considers the losses caused by the equivalent resistance in the station, and constructs the relationship between the inverter output power and efficiency. In terms of the active output evaluation of photovoltaic stations, according to the real-time operating status of each inverter, and combined with the inverters in the station, prediction systems, real-time meteorological and other data, the inverters that can be included in the AGC regulation capacity calculation are screened according to the health level and verified to improve the accuracy of scheduling; in terms of the power distribution of the inverter, by setting a model inverter, other inverters are classified according to the adjustment speed, and the fast-adjusting inverter is switched on first, so as to achieve rapid adjustment and reasonable distribution of active power, thereby improving the regulation capacity to a certain extent. The present invention effectively improves the power generation efficiency of photovoltaic stations, realizes the reasonable distribution of power, and further improves the economy and stability of system operation. Specifically, please refer to Figure 1 , Figure 1 This is an overall flow chart of an AGC optimization control method considering the differentiated response capability of photovoltaic station inverters shown in an exemplary embodiment of the present application. The method includes steps S100 to S300, which are described in detail as follows.

[0081] S100: Establishing a mathematical model of the photovoltaic station according to the photovoltaic station in operation dynamics.

[0082] In this embodiment, the purpose of step S100 is to implement mathematical modeling of a photovoltaic station taking into account the operation dynamics.

[0083] In an exemplary embodiment, step S100 specifically includes: according to a predefined ideal factor, taking into account the loss of equipment in the station, using solar radiation and ambient temperature as input parameters to calculate the maximum power value of component temperature, photovoltaic voltage, current and power, and establishing a mathematical model of the photovoltaic station.

[0084] Specifically,

[0085] According to the predefined ideal factor, the current I flowing through the photovoltaic station can be obtained as:

[0086]

[0087] Where: I PV is the photocurrent; I 0 is the saturation current; n is the ideal factor (between 1.3 and 1.35); T cell is the battery temperature; V is the terminal voltage; R s and R sh are series resistance and parallel resistance respectively; q is the charge number; e is the exponential function; k is the number of batteries;

[0088] Component operating temperature T CELL It is determined by the ambient temperature and solar radiation, and its expression is:

[0089]

[0090] Where: T amb is the ambient temperature; G is the solar radiation terminal voltage; T NOCT is the test temperature of the component;

[0091] To calculate the series resistance R s In this way, the power loss is solved, the fill factor (indicating the degree of utilization of theoretical power) FF is defined, and the short-circuit current I is obtained accordingly. SC and open circuit voltage V OC , the expression is:

[0092]

[0093] Where: FF CELL I is the conversion efficiency of the battery's theoretical power; MPP and V MPP are the theoretical values ​​of current and voltage respectively; I SC 、V OC are short-circuit current and open-circuit voltage respectively; I OC.moment , U OC.moment are the current and voltage corresponding to the start of iteration respectively; FF 0 is the initial filling factor; P Nom is the input power of the battery;

[0094] By iteratively generating I and V values ​​at the open circuit point (using formula (1-1)), the maximum power output of the photovoltaic station is obtained as:

[0095] P DCmax =max(I,V) (1-4)

[0096] Where: V is the voltage of the photovoltaic station; I is the current flowing through the photovoltaic station.

[0097] Here, the active resistor represents the loss at the connection between the generator and the inverter in the photovoltaic power station, and its specific expression is:

[0098] ΔP DC.CAB =RI 2 (1-5)

[0099] Where: R is the equivalent active resistance; I is the current flowing through the photovoltaic station.

[0100] The inverter is the intermediary between the photovoltaic power station and the power grid. The relationship between the inverter output power and efficiency is obtained using formula (1-6):

[0101] y=a 1 x n +a 2 x n-1 +K+a n x+a n+1 (1-6)

[0102] Where: x is the inverter output power; y is the inverter efficiency; a 1 、a 2 、a n 、a n+1 are the coefficients of the inverter output power respectively; n is the power of the inverter output power.

[0103] S200: Based on the mathematical model of the photovoltaic station and according to the actual operating conditions of the inverter, the inverters with characteristic correlation greater than the set threshold are calculated as model inverters, and the model inverters are screened. The AGC regulation capability of the photovoltaic power station is calculated and verified according to the screening results.

[0104] In this embodiment, the purpose of step S200 is to evaluate the active output of the photovoltaic station and analyze its influencing factors. On the basis of step S100, considering the actual operating conditions of the inverter, the feature selection algorithm of correlation is applied to calculate the inverter with high feature correlation as the model inverter; and the inverter that can be included in the AGC regulation capacity calculation is selected according to the actual operating status, that is, the preset rules, and the AGC regulation capacity of the photovoltaic power station is calculated and verified according to the screening results.

[0105] It should be noted that, in the process of applying the correlation feature selection algorithm to calculate the inverter with high feature correlation as the model inverter, the feature correlation threshold can be set according to the selected correlation feature selection algorithm, and the inverter with a feature correlation threshold higher than the set feature correlation threshold can be used as the model inverter. Alternatively, the inverter with the highest feature correlation can be used as the model inverter. Among them, the correlation feature selection algorithm includes but is not limited to the variance selection method, the correlation coefficient method, the recursive feature elimination algorithm, and the feature selection algorithm based on the tree model.

[0106] In an exemplary embodiment, the actual power generation capacity of each photovoltaic array is affected by the operating status of the inverter, geographical location, irradiation intensity, etc., resulting in a large error between the Pmax calculated by the traditional AGC regulation capacity and the actual value. In order to achieve precise control, by gathering data such as inverters, prediction systems, and real-time meteorological data in the station, based on comprehensive analysis of big data, the real-time operating status of each inverter in the photovoltaic station is obtained (divided into free power generation status, planned maintenance status, unplanned shutdown status, standby status, and communication interruption status). Finally, according to the number of interruptions of the inverter (defined as health), the inverter with a preset health greater than 7 is included in the AGC regulation capacity calculation range, and the result is output after a verification.

[0107] In this embodiment, the upper limit of the active power adjustable of the photovoltaic power station is used as an indicator for verifying the AGC adjustment capability of the photovoltaic power station; wherein, the calculation formula of the upper limit of the active power adjustable of the photovoltaic power station is:

[0108] P max =P t N (2-1)

[0109] Where: P max P is the upper limit of the active power adjustable of the photovoltaic power station; t is the instantaneous active power of the inverter model; N is the total number of inverters in the photovoltaic power station.

[0110] S300: Power allocation based on the differentiated response capabilities of inverters.

[0111] In this embodiment, step S300 divides the inverter into a slow-adjusting inverter (first-class inverter) and a fast-adjusting inverter (second-class inverter) based on step S200 and in combination with the operating characteristics and adjustment speed of the inverter. By determining the order of input of each inverter and the power value allocated to it, the output power of the photovoltaic station meets the active power instruction in a short time, and the power of inverters with different adjustment speeds is balanced, so as to achieve fast and accurate adjustment of the photovoltaic power station while improving its adjustment capacity.

[0112] In an exemplary embodiment, step S300 may be implemented by the following method to achieve power allocation:

[0113] By comparing the response time and control adjustment time, the inverters are divided into slow-adjusting inverters (category 1 inverters) and fast-adjusting inverters (category 2 inverters).

[0114] Exemplarily, the sum or weighted sum of the response time and control adjustment time of the inverter is calculated; the sum or weighted sum is sorted according to the size of the sum or weighted sum, and based on the set classification threshold, the inverter corresponding to the sum or weighted sum greater than the classification threshold is classified as Class 1 inverter, and the inverter corresponding to the sum or weighted sum less than or equal to the classification threshold is classified as Class 2 inverter, thereby realizing the classification of inverters. It should be noted that the classification thresholds corresponding to the sum or weighted sum of the response time and control adjustment time of the inverter are usually not equal. For example, the classification threshold corresponding to the sum of the response time and control adjustment time of the inverter is the first threshold, and the classification threshold corresponding to the weighted sum of the response time and control adjustment time of the inverter is the second threshold, and the second threshold is not equal to the first threshold.

[0115] Assuming that the time taken to execute a distribution strategy during the active power regulation process is one regulation cycle, the total output power of the inverter is:

[0116]

[0117] Where: P j P is the total output power of the j-th inverter in the previous regulation cycle, j = 1, 2; ji N is the output power of the i-th inverter of type j put into operation in the last regulation cycle; um_j is the number of inverters of type j put into operation.

[0118] Active power reference value P of the i-th inverter i_ref for:

[0119] P i_min ≤P i_ref ≤P i_fore (3-2)

[0120] Where: P i_min is the minimum starting power, i_fore is the maximum predicted power generation.

[0121] Taking the sample inverter as the standard, it is considered that P i_fore =P miv_max , P i_min =P miv_min , formula (3-2) can be transformed into:

[0122] P miv_min ≤P i_ref ≤P miv_max (3-3)

[0123] Where: P miv_min and P miv_fore are the minimum starting power and maximum predicted power of the sample inverter.

[0124] Since the first type of inverter has a slow adjustment speed, it is considered to be in operation all the time; when the currently running inverter cannot meet the power adjustment instruction, the second type of inverter is switched on and off first, and its active power reference value P ref for:

[0125]

[0126] Where: P ref The active power regulation command received by the photovoltaic power station; ΔP ref P is the power regulation task undertaken by the inverters other than the sample inverter in the current regulation cycle; pref The reference value of the Class 2 inverter planned to be put into operation in the current regulation cycle; P 1 The power borne by the first category inverter; N 2 The number of class 2 inverters planned to be put into operation for the current regulation cycle.

[0127] During the power regulation process, the power reference values ​​of the two types of inverters are the same, P 1i_ref =P 2i_ref =P pref When the steady state is reached, P 1i =P 2i , while achieving rapid power regulation, the regulation capability of the second type inverter is retained, and the first type inverter is allowed to participate in power regulation, thereby improving the regulation capacity of the photovoltaic power station.

[0128] When ΔP 2 <P 2_min When the power is fully borne by the first-class inverter, that is:

[0129]

[0130] Where: P 1i_rw N is the regulation task assigned to the i-th inverter of the first category in the current regulation cycle; um_1_1 is the number of Class 1 inverters.

[0131] During the power regulation process, the P of the i-th inverter in the first category is 1i_ref for:

[0132]

[0133] Where: P 1i_ref P is the power regulation target value of the i-th inverter of the first category planned to be put into use in the current regulation cycle; 1i_rw The regulation task assigned to the i-th inverter of category 1 in the current regulation cycle.

[0134] In summary, the AGC optimization control method that considers the differentiated response capabilities of photovoltaic station inverters proposed in the embodiment of the present application is based on the mathematical model of the photovoltaic station that takes into account the equivalent resistance loss in the station, and according to the prediction system, real-time meteorological and other data, and combined with the real-time operating status of the inverter, the inverter that can be included in the AGC regulation capability is screened according to the health degree to improve the accuracy of scheduling. On this basis, the inverters are classified according to the adjustment speed as the standard, and by setting the active power constraint conditions, the reasonable distribution of the power of each inverter in the station is achieved while maximizing the power generation efficiency of the photovoltaic station. The present application can be applied to large-scale photovoltaic power generation grid-connected systems, which can improve the adaptability and accuracy of photovoltaic power stations in power dispatching, and improve the economy and stability of system operation.

[0135] See also Figure 2 , Figure 2 It is a structural diagram of an AGC optimization control device considering the differentiated response capability of a photovoltaic station inverter shown in an exemplary embodiment of the present application. Another aspect of the embodiment of the present invention further provides an AGC optimization control device considering the differentiated response capability of a photovoltaic station inverter, the device comprising:

[0136] The model building module 201 is configured to build a mathematical model of the photovoltaic station according to the photovoltaic station in operation;

[0137] The evaluation and analysis module 202 is configured to calculate the inverters with characteristic correlation greater than a set threshold as model inverters based on the mathematical model of the photovoltaic station and the actual operating conditions of the inverters, and screen the model inverters, and calculate and verify the AGC regulation capability of the photovoltaic power station based on the screening results;

[0138] The power allocation module 203 is configured to perform power allocation based on the differentiated response capabilities of the inverters.

[0139] In some embodiments, the model building module is further configured to:

[0140] According to the set ideal factor, the current flowing through the photovoltaic station is obtained by the following formula:

[0141]

[0142] Where: I is the current flowing through the photovoltaic station, I PV is the photocurrent; I 0 is the saturation current; n is the ideal factor; T cell is the battery temperature; V is the terminal voltage; R s and R sh are series resistance and parallel resistance respectively; q is the charge number; e is the exponential function; k is the number of batteries;

[0143] According to the ambient temperature and solar radiation, the operating temperature of the module is determined by the following formula:

[0144]

[0145] Where: T CELL is the operating temperature of the component; T amb is the ambient temperature; G is the solar radiation terminal voltage; T NOCT is the test temperature of the component;

[0146] Based on the fill factor, the short-circuit current and open-circuit voltage are obtained by the following formula:

[0147]

[0148] Where: FF CELL I is the conversion efficiency of the battery's theoretical power; MPP and V MPP are the theoretical values ​​of current and voltage respectively; I SC 、V OC are short-circuit current and open-circuit voltage respectively; I OC.moment , U OC.moment are the current and voltage corresponding to the start of iteration respectively; FF 0 is the initial filling factor; P Nom is the input power of the battery;

[0149] At the open circuit point, the I and V values ​​are iteratively generated using formula (1-1), and the maximum power output of the photovoltaic station is obtained as follows:

[0150] P D C max =max(I,V) (1-4)

[0151] Where: P DCmax is the maximum power output by the photovoltaic station; V is the voltage of the photovoltaic station; I is the current flowing through the photovoltaic station;

[0152] Active resistance is used to characterize the loss at the connection between the generator and the inverter in the photovoltaic power station; wherein the expression for the loss at the connection between the generator and the inverter in the photovoltaic power station is:

[0153] ΔP DC.CAB =RI 2 (1-5)

[0154] Where: ΔP DC.CAB is the loss at the connection between the generator and the inverter in the photovoltaic power station; R is the equivalent active resistance;

[0155] With the inverter as the intermediary between the photovoltaic power station and the power grid, the relationship between the inverter output power and efficiency is obtained through the following formula:

[0156] y=a 1 x n +a 2 x n-1 +K+a n x+a n+1 (1-6)

[0157] Where: x is the inverter output power; y is the inverter efficiency; a 1 、a 2 、a n 、a n+1 are the coefficients of the inverter output power respectively; n is the power of the inverter output power.

[0158] In some embodiments, the evaluation and analysis module is further configured to:

[0159] By gathering the inverters, forecasting systems, and real-time meteorological data in the photovoltaic station, the real-time operating status of each inverter in the photovoltaic station is obtained based on comprehensive analysis of big data; wherein the real-time operating status includes free power generation status, planned maintenance status, unplanned shutdown status, standby status, and communication interruption status;

[0160] According to the real-time operating status of the inverter, the number of interruptions of the inverter is determined as the health degree;

[0161] Based on the preset health degree, the inverters having a health degree greater than the preset health degree are screened out as the screening result;

[0162] The AGC regulation capability of the photovoltaic power station is calculated and verified based on the screening results.

[0163] In some embodiments, the evaluation and analysis module is further configured to:

[0164] The upper limit of the active power adjustable of the photovoltaic power station is used as an indicator for verifying the AGC adjustment capability of the photovoltaic power station; wherein, the calculation formula of the upper limit of the active power adjustable of the photovoltaic power station is:

[0165] P max =P t N (2-1)

[0166] Where: P max P is the upper limit of the active power adjustable of the photovoltaic power station; t is the instantaneous active power of the inverter model; N is the total number of inverters in the photovoltaic power station.

[0167] In some embodiments, the power distribution module is further configured to:

[0168] According to the operating characteristics and adjustment speeds of the screened inverters, the inverters are divided into Class 1 inverters and Class 2 inverters; by determining the input sequence of each inverter and the power value allocated to it, the output power of the photovoltaic station meets the active power instruction within the set time, and power balance is performed on inverters with different adjustment speeds.

[0169] In some embodiments, the power distribution module is further configured to:

[0170] Comparing the response time and control adjustment time of the screened inverters, the inverters are divided into a first-category inverter and a second-category inverter; wherein the adjustment speed of the first-category inverter is less than the adjustment speed of the second-category inverter;

[0171] The time taken to execute a distribution strategy during the active power regulation process is determined by the following formula as the total inverter output power for one regulation cycle:

[0172]

[0173] Where: P j P is the total output power of the j-th inverter in the previous regulation cycle; ji N is the output power of the i-th inverter of type j put into operation in the last regulation cycle; um_j is the number of j-th inverters put into operation; i represents the serial number of the inverter, j represents the category of the inverter, j=1, 2, when j=1, it means the inverter is a first-category inverter, when j=2, it means the inverter is a second-category inverter;

[0174] The active power reference value of the i-th inverter is determined by the following formula:

[0175] P i_min ≤P i_ref ≤P i_fore (3-2)

[0176] Where: P i_min is the minimum starting power; P i_fore is the maximum predicted power generation; P i_ref is the active power reference value of the i-th inverter;

[0177] Taking the sample inverter as the standard, let P i_fore =P miv_max , P i_min =P miv_min , transform formula (3-2) into:

[0178] P miv_min ≤P i_ref ≤P miv_max (3-3)

[0179] Where: P miv_min and P miv_fore They are the minimum starting power and maximum predicted power of the sample inverter respectively;

[0180] When the currently running inverter cannot meet the power regulation instruction, the second-class inverter is switched on and off first. The active power reference value of the second-class inverter is:

[0181]

[0182] Where: P ref The active power regulation command received by the photovoltaic power station; ΔP ref P is the power regulation task undertaken by the inverters other than the sample inverter in the current regulation cycle; pref The active power reference value of the Category 2 inverter planned to be put into operation in the current regulation cycle; P 1 The power borne by the first category inverter; N 2 The number of Category 2 inverters planned to be put into operation for the current regulation cycle;

[0183] In the power regulation process, the power reference values ​​of the two types of inverters are the same, and P 1i =P 2i , while achieving fast power regulation, retaining the regulation capability of the second type inverter and allowing the first type inverter to participate in power regulation:

[0184] When ΔP 2 <P 2_min When the power is fully borne by the first-class inverter, that is:

[0185]

[0186] Where: P 1i_rw N is the regulation task assigned to the i-th inverter of the first category in the current regulation cycle; um_1_1 is the number of inverters of type 1; ΔP 2 The power regulation target value of the Class 2 inverter planned to be put into operation in the current regulation cycle; P 2_min The minimum power value that can be provided by a Category 2 inverter;

[0187] During the power regulation process, the power regulation target value P of the i-th inverter of the first category in the current regulation cycle is 1i_ref for:

[0188]

[0189] Where: P 1i_ref P is the power regulation target value of the i-th inverter of the first category planned to be put into use in the current regulation cycle; 1i_rwThe regulation task assigned to the i-th inverter of category 1 in the current regulation cycle.

[0190] It should be noted that the AGC optimization and control device for considering the differentiated response capabilities of photovoltaic station inverters provided in the above-mentioned embodiments and the AGC optimization and control method for considering the differentiated response capabilities of photovoltaic station inverters provided in the above-mentioned embodiments belong to the same concept, and the specific manner of executing the step operations has been described in detail in the method embodiments and will not be repeated here.

[0191] Another aspect of the present application provides an electronic device, including: a controller; a memory for storing one or more programs, which, when executed by the controller, executes the AGC optimization control method considering the differentiated response capabilities of photovoltaic station inverters in the above-mentioned embodiments.

[0192] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU) 701, various functions defined in the system of the present application are executed.

[0193] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a 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 above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0194] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0195] The modules / units involved in the embodiments described in this application may be implemented by software or hardware, and the described units may also be set in a processor. The names of these modules / units do not, in some cases, constitute limitations on the modules / units themselves.

[0196] Another aspect of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the AGC optimization control method considering the differentiated response capability of the photovoltaic station inverter as described above. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.

[0197] Another aspect of the present application also provides a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the AGC optimization control method considering the differentiated response capability of the photovoltaic station inverter provided in the above-mentioned various embodiments.

[0198] According to one aspect of an embodiment of the present application, a computer system is also provided, including a central processing unit (CPU), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage portion into a random access memory (RAM), such as executing the method in the above embodiment. In RAM, various programs and data required for system operation are also stored. CPU, ROM and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0199] The following components are connected to the I / O interface: an input part including a keyboard, a mouse, etc.; an output part including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage part including a hard disk, etc.; and a communication part including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication part performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface as needed. Removable media, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., are installed on the drive as needed so that the computer program read therefrom is installed into the storage part as needed.

[0200] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. A person skilled in the art can easily make corresponding changes or modifications based on the main concept and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.

Claims

1. An AGC optimization control method considering the differentiated response capability of photovoltaic station inverters, characterized in that: The method comprises: According to the dynamic operation of photovoltaic stations, a mathematical model of photovoltaic stations is established; Based on the mathematical model of the photovoltaic station and according to the actual operating conditions of the inverter, an inverter with a characteristic correlation greater than a set threshold is calculated as a model inverter, and the model inverter is screened, and the AGC regulation capability of the photovoltaic power station is calculated and verified according to the screening results; Power allocation is performed based on the differentiated response capabilities of inverters.

2. The AGC optimization control method considering the differentiated response capability of photovoltaic station inverters according to claim 1 is characterized in that: According to the dynamic operation of photovoltaic stations, a mathematical model of photovoltaic stations is established, including: According to the set ideal factor, the current flowing through the photovoltaic station is obtained by the following formula: Where: I is the current flowing through the photovoltaic station, I PV is the photocurrent; I0 ​​is the saturation current; n is the ideal factor; T cell is the battery temperature; V is the terminal voltage; R s and R sh are series resistance and parallel resistance respectively; q is the charge number; e is the exponential function; k is the number of batteries; According to the ambient temperature and solar radiation, the operating temperature of the module is determined by the following formula: Where: T CELL is the operating temperature of the component; T amb is the ambient temperature; G is the solar radiation terminal voltage; T NOCT is the test temperature of the component; Based on the fill factor, the short-circuit current and open-circuit voltage are obtained by the following formula: Where: FF CELL I is the conversion efficiency of the battery's theoretical power; MPP and V MPP are the theoretical values ​​of current and voltage respectively; I SC 、V OC are short-circuit current and open-circuit voltage respectively; I OC.moment , U OC.moment are the current and voltage corresponding to the start of iteration respectively; FF0 is the initial filling factor; P Nom is the input power of the battery; At the open circuit point, the I and V values ​​are iteratively generated using formula (1-1), and the maximum power output of the photovoltaic station is obtained as follows: P DCmax =max(I,V) (1-4) Where: P DCmax is the maximum power output by the photovoltaic station; V is the voltage of the photovoltaic station; I is the current flowing through the photovoltaic station; Active resistance is used to characterize the loss at the connection between the generator and the inverter in the photovoltaic power station; wherein the expression for the loss at the connection between the generator and the inverter in the photovoltaic power station is: ΔP DC.CAB =R.I 2 (1-5) Where: ΔP DC.CAB is the loss at the connection between the generator and the inverter in the photovoltaic power station; R is the equivalent active resistance; With the inverter as the intermediary between the photovoltaic power station and the power grid, the relationship between the inverter output power and efficiency is obtained through the following formula: y=a1x n +a2x n-1 +K+a n x+a n+1 (1-6) Where: x is the inverter output power; y is the inverter efficiency; a1, a2, a n 、a n+1 are the coefficients of the inverter output power respectively; n is the power of the inverter output power.

3. The AGC optimization control method considering the differentiated response capability of photovoltaic station inverters according to claim 2 is characterized in that: The sample inverter is screened, and the AGC regulation capability of the photovoltaic power station is calculated and verified according to the screening results, including: By gathering the inverters, forecasting systems, and real-time meteorological data in the photovoltaic station, the real-time operating status of each inverter in the photovoltaic station is obtained based on comprehensive analysis of big data; wherein the real-time operating status includes free power generation status, planned maintenance status, unplanned shutdown status, standby status, and communication interruption status; According to the real-time operating status of the inverter, the number of interruptions of the inverter is determined as the health degree; Based on the preset health degree, the inverters having a health degree greater than the preset health degree are screened out as the screening result; The AGC regulation capability of the photovoltaic power station is calculated and verified based on the screening results.

4. The AGC optimization control method considering the differentiated response capability of photovoltaic station inverters according to claim 3 is characterized in that: Based on the screening results, the AGC regulation capability of the photovoltaic power station is calculated and verified, including: The upper limit of the active power adjustable of the photovoltaic power station is used as an indicator for verifying the AGC adjustment capability of the photovoltaic power station; wherein, the calculation formula of the upper limit of the active power adjustable of the photovoltaic power station is: P max =P t N (2-1) Where: P max P is the upper limit of the active power adjustable of the photovoltaic power station; t is the instantaneous active power of the inverter model; N is the total number of inverters in the photovoltaic power station.

5. The AGC optimization control method considering the differentiated response capability of photovoltaic station inverters according to claim 1 is characterized in that: Power allocation based on inverter differentiated response capabilities, including: According to the operating characteristics and adjustment speeds of the screened inverters, the inverters are divided into Class 1 inverters and Class 2 inverters; by determining the input sequence of each inverter and the power value allocated to it, the output power of the photovoltaic station meets the active power instruction within the set time, and power balance is performed on inverters with different adjustment speeds.

6. The AGC optimization control method considering the differentiated response capability of photovoltaic station inverters according to claim 5 is characterized in that: According to the operating characteristics and adjustment speed of the screened inverters, the inverters are divided into Class 1 inverters and Class 2 inverters; by determining the order of input of each inverter and the power value allocated, the output power of the photovoltaic station meets the active power instruction within the set time, and the power balance of inverters with different adjustment speeds is performed, including: Comparing the response time and control adjustment time of the screened inverters, the inverters are divided into a first-category inverter and a second-category inverter; wherein the adjustment speed of the first-category inverter is less than the adjustment speed of the second-category inverter; The time taken to execute a distribution strategy during the active power regulation process is determined by the following formula as the total inverter output power for one regulation cycle: Where: P j P is the total output power of the j-th inverter in the previous regulation cycle; ji N is the output power of the i-th inverter of type j put into operation in the last regulation cycle; um_j is the number of j-th inverters put into operation; i represents the serial number of the inverter, j represents the category of the inverter, j=1, 2, when j=1, it means the inverter is a first-category inverter, when j=2, it means the inverter is a second-category inverter; The active power reference value of the i-th inverter is determined by the following formula: P i_min ≤P i_ref ≤P i_fore (3-2) Where: P i_min is the minimum starting power; P i_fore is the maximum predicted power generation; P i_ref is the active power reference value of the i-th inverter; Taking the sample inverter as the standard, let P i_fore =P miv_max , P i_min =P miv_min , transform formula (3-2) into: P miv_min ≤P i_ref ≤P miv_max (3-3) Where: P miv_min and P miv_fore They are the minimum starting power and maximum predicted power of the sample inverter respectively; When the currently running inverter cannot meet the power regulation instruction, the second-class inverter is switched on and off first. The active power reference value of the second-class inverter is: Where: P ref The active power regulation command received by the photovoltaic power station; ΔP ref P is the power regulation task undertaken by the inverters other than the sample inverter in the current regulation cycle; pref is the active power reference value of the second-category inverter planned to be put into operation in the current regulation cycle; P1 is the power borne by the first-category inverter; N2 is the number of the second-category inverter planned to be put into operation in the current regulation cycle; In the power regulation process, the power reference values ​​of the two types of inverters are the same, and P 1i =P 2i , while achieving fast power regulation, retaining the regulation capability of the second type inverter and allowing the first type inverter to participate in power regulation: When ΔP2<P 2_min When the power is fully borne by the first-class inverter, that is: Where: P 1i_rw N is the regulation task assigned to the i-th inverter of the first category in the current regulation cycle; um_1_1 is the number of Class 1 inverters; ΔP2 is the power regulation target value of Class 2 inverters planned to be put into operation in the current regulation cycle; P 2_min The minimum power value that can be provided by a Category 2 inverter; During the power regulation process, the power regulation target value P of the i-th inverter of the first category in the current regulation cycle is 1i_ref for: Where: P 1i_ref P is the power regulation target value of the i-th inverter of the first category planned to be put into use in the current regulation cycle; 1i_rw The regulation task assigned to the i-th inverter of category 1 in the current regulation cycle.

7. An AGC optimization control device considering the differentiated response capability of photovoltaic station inverters, characterized in that: The device comprises: A model building module is configured to build a mathematical model of the photovoltaic station according to the photovoltaic station in operation dynamics; The evaluation and analysis module is configured to calculate, based on the mathematical model of the photovoltaic station and according to the actual operating conditions of the inverter, inverters with characteristic correlation greater than a set threshold as sample inverters, screen the sample inverters, and calculate and verify the AGC regulation capability of the photovoltaic power station according to the screening results; The power distribution module is configured to distribute power based on the differentiated response capabilities of the inverters.

8. The AGC optimization control device considering the differentiated response capability of photovoltaic station inverters according to claim 7 is characterized in that: The power distribution module is further configured as follows: Comparing the response time and control adjustment time of the screened inverters, the inverters are divided into a first-category inverter and a second-category inverter; wherein the adjustment speed of the first-category inverter is less than the adjustment speed of the second-category inverter; The time taken to execute a distribution strategy during the active power regulation process is determined by the following formula as the total inverter output power for one regulation cycle: Where: P j P is the total output power of the j-th inverter in the previous regulation cycle; ji N is the output power of the i-th inverter of type j put into operation in the last regulation cycle; um_j is the number of j-th inverters put into operation; i represents the serial number of the inverter, j represents the category of the inverter, j=1, 2, when j=1, it means the inverter is a first-category inverter, when j=2, it means the inverter is a second-category inverter; The active power reference value of the i-th inverter is determined by the following formula: P i_min ≤P i_ref ≤P i_fore (3-2) Where: P i_min is the minimum starting power; P i_fore is the maximum predicted power generation; P i_ref is the active power reference value of the i-th inverter; Taking the sample inverter as the standard, let P i_fore =P miv_max , P i_min =P miv_min , transform formula (3-2) into: P miv_min ≤P i_ref ≤P miv_max (3-3) Where: P miv_min and P miv_fore They are the minimum starting power and maximum predicted power of the sample inverter respectively; When the currently running inverter cannot meet the power regulation instruction, the second-class inverter is switched on and off first. The active power reference value of the second-class inverter is: Where: P ref The active power regulation command received by the photovoltaic power station; ΔP ref P is the power regulation task undertaken by the inverters other than the sample inverter in the current regulation cycle; pref is the active power reference value of the second-category inverter planned to be put into operation in the current regulation cycle; P1 is the power borne by the first-category inverter; N2 is the number of the second-category inverter planned to be put into operation in the current regulation cycle; In the power regulation process, the power reference values ​​of the two types of inverters are the same, and P 1i =P 2i , while achieving fast power regulation, retaining the regulation capability of the second type inverter and allowing the first type inverter to participate in power regulation: When ΔP2<P 2_min When the power is fully borne by the first-class inverter, that is: Where: P 1i_rw N is the regulation task assigned to the i-th inverter of the first category in the current regulation cycle; um_1_1 is the number of Class 1 inverters; ΔP2 is the power regulation target value of Class 2 inverters planned to be put into operation in the current regulation cycle; P 2_min The minimum power value that can be provided by a Category 2 inverter; During the power regulation process, the power regulation target value P of the i-th inverter of the first category in the current regulation cycle is 1i_ref for: Where: P 1i_ref P is the power regulation target value of the i-th inverter of the first category planned to be put into use in the current regulation cycle; 1i_rw The regulation task assigned to the i-th inverter of category 1 in the current regulation cycle.

9. An electronic device, characterized in that: include: Controller; A memory for storing one or more programs, which, when executed by the controller, enables the controller to implement the AGC optimization control method according to any one of claims 1 to 6 that takes into account the differentiated response capabilities of photovoltaic station inverters.

10. A computer-readable storage medium, characterized in that: Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the AGC optimization control method considering the differentiated response capabilities of photovoltaic station inverters as described in any one of claims 1 to 6.

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