AGC comprehensive frequency modulation performance index control method and system based on response demand

Abstract

The invention belongs to the technical field of power control, and discloses an AGC comprehensive frequency modulation performance index control method and system based on response demand, and the method comprises the steps: obtaining power grid frequency modulation demand characteristics based on power grid frequency data and regional power balance data collected in real time, and building a power grid frequency modulation demand prediction model through multi-dimensional time sequence analysis, outputting a short-term power grid frequency modulation demand prediction value; calculating a comprehensive frequency modulation performance index of each unit according to the short-term power grid frequency modulation demand prediction value in combination with the real-time state data of various units; and based on the comprehensive frequency modulation performance index of each unit, generating a dynamic frequency modulation task allocation strategy of each unit through a multi-objective optimization algorithm, and adjusting an AGC control signal in real time according to the dynamic frequency modulation task allocation strategy of each unit. According to the method, accurate adjustment of the AGC control instruction is realized through the prediction model, the performance index and optimal distribution, and the frequency adjustment quality of the power grid is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power control, and in particular to an AGC comprehensive frequency modulation performance index control method and system based on response demand. Background Art

[0002] With the continuous expansion of the scale of power systems and the large-scale access of new energy sources, the difficulty of regulating the frequency of power grids is increasing. In order to ensure the safe and stable operation of the power grid, the automatic generation control (AGC) system plays an increasingly important role in the power system. The AGC system achieves stable control and economic dispatch of the power grid frequency by adjusting the output of the generator set. However, due to the frequent changes in the load instructions of the power grid and the influence of factors such as coal quality and actuators, the AGC performance of thermal power units generally declines, affecting the overall frequency regulation capability of the power grid.

[0003] At present, common AGC control methods mainly include proportional integral (PI) control, fuzzy control, adaptive control, etc. These methods can adjust the output of the generator set in real time by adjusting the control parameters. At the same time, some researchers have proposed AGC control strategies based on predictive control and intelligent optimization algorithms to improve the dynamic response performance of the system; in addition, some scholars have explored the AGC performance evaluation method and proposed a comprehensive evaluation system based on indicators such as adjustment rate, response time and adjustment accuracy.

[0004] However, the existing AGC control methods and evaluation systems still have some shortcomings. First, most methods fail to fully consider the actual needs of the power grid and the characteristics of different types of units, making it difficult to achieve optimal resource allocation; second, the existing performance evaluation indicators are often static and cannot reflect the real-time performance changes of the AGC system in the dynamic process; third, the existing technology lacks a dynamic frequency regulation task allocation mechanism based on the comprehensive performance of the unit, making it difficult to achieve precise adjustment of the AGC control instructions.

[0005] Therefore, how to provide an AGC control method that can comprehensively consider multiple performance indicators based on response requirements has become a problem that needs to be solved urgently. Summary of the invention

[0006] The embodiments of the present invention provide an AGC comprehensive frequency regulation performance index control method and system based on response demand to solve the problems in the prior art of failing to fully consider the actual needs of the power grid and the characteristics of different types of units, lacking a dynamic performance evaluation mechanism, and lacking a dynamic frequency regulation task allocation mechanism based on the comprehensive performance of the units.

[0007] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not a general review, nor is it intended to identify key / important components or to describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0008] According to a first aspect of an embodiment of the present invention, a method for controlling an AGC comprehensive frequency modulation performance index based on response demand is provided.

[0009] In one embodiment, the AGC comprehensive frequency modulation performance index control method based on response demand includes:

[0010] Based on the collected grid frequency data and regional power balance data, the grid frequency regulation demand characteristics are obtained, and through multi-dimensional time series analysis, a grid frequency regulation demand prediction model is established to output the short-term grid frequency regulation demand prediction value;

[0011] According to the short-term grid frequency regulation demand forecast value, combined with the real-time status data of various units that can currently participate in AGC frequency regulation, the unit AGC performance parameters are solved, and the comprehensive frequency regulation performance index of each unit is calculated;

[0012] Based on the comprehensive frequency regulation performance indicators of each unit, a dynamic frequency regulation task allocation strategy for each unit is generated through a multi-objective optimization algorithm, and the AGC control signal is adjusted in real time according to the dynamic frequency regulation task allocation strategy of each unit.

[0013] In one embodiment, based on the collected grid frequency data and regional power balance data, the grid frequency regulation demand characteristics are obtained, and a grid frequency regulation demand prediction model is established through multi-dimensional time series analysis. The output of the short-term grid frequency regulation demand prediction value includes:

[0014] Calculate the grid frequency regulation demand characteristics based on the collected grid frequency data and regional power balance data;

[0015] By using the characteristics of power grid frequency regulation demand, a power grid frequency regulation demand prediction model is established through time series decomposition and autoregressive moving average analysis.

[0016] Based on the power grid frequency regulation demand prediction model, the real-time power grid frequency regulation demand characteristics are input and the short-term power grid frequency regulation demand prediction value is output.

[0017] In one embodiment, the grid frequency data includes the sampling frequency and the grid rated frequency; the regional power balance data includes the regional total power generation and the regional total load; the grid frequency regulation demand characteristics include the frequency deviation mean and the power imbalance; the short-term grid frequency regulation demand forecast value includes the AGC command change, the AGC target value and the grid required response time.

[0018] In one embodiment, the expression of the frequency deviation mean is:

[0019] ;

[0020] Where Δf avg is the mean frequency deviation, n is the number of sampling points in the sliding window, f i is the sampling frequency of the ith sampling point, f nom is the rated frequency of the power grid;

[0021] The expression of power imbalance is:

[0022] ;

[0023] Where ΔP S is the power imbalance, P gen is the total power generation in the region, P load is the total regional load.

[0024] In one embodiment, the real-time status data of various types of units include the actual output of the unit, the rated capacity of the unit and the actual response time of the unit; the AGC performance parameters of the unit include the adjustment speed, adjustment accuracy and response time.

[0025] In one embodiment, according to the short-term grid frequency regulation demand forecast value, combined with the real-time status data of various units that can currently participate in AGC frequency regulation, the unit AGC performance parameters are solved, and the comprehensive frequency regulation performance index of each unit is calculated, including:

[0026] Obtain the regulation speed based on the AGC command change, response time, and rated capacity of the unit;

[0027] Using the actual output of the unit and the AGC target value, the regulation accuracy is solved;

[0028] Analyze the response time based on the actual response time of the unit and the response time required by the power grid;

[0029] The comprehensive frequency regulation performance index of each unit is obtained by weighted fusion of regulation speed, regulation accuracy and response time.

[0030] In one embodiment, the expression for adjusting the speed is:

[0031] ;

[0032] In the formula, K1 is the adjustment speed, ΔP AGC is the AGC command change, Δt is the response time, P rated Rated capacity of the unit:

[0033] The expression of adjustment accuracy is:

[0034] ;

[0035] In the formula, K2 is the adjustment accuracy, P actual is the actual output of the unit, P target is the AGC target value;

[0036] The expression for response time is:

[0037] ;

[0038] Where K3 is the response time, t response is the actual response time of the unit, t required Require response time for the grid;

[0039] The expression of comprehensive frequency modulation performance index is:

[0040] ;

[0041] In the formula, K p is a comprehensive frequency modulation performance index, w1, w2 and w3 are the adjustment speed weight coefficient, adjustment accuracy weight coefficient and response time weight coefficient respectively, and w1+w2+w3=1.

[0042] In one embodiment, based on the comprehensive frequency regulation performance index of each unit, a dynamic frequency regulation task allocation strategy for each unit is generated through a multi-objective optimization algorithm, and the AGC control signal is adjusted in real time according to the dynamic frequency regulation task allocation strategy of each unit, including:

[0043] Using the comprehensive frequency regulation performance index of each unit and the control deviation requirements of the power grid area, a multi-objective optimization model including objective functions and constraints is established;

[0044] By solving the multi-objective optimization model, the dynamic frequency regulation task allocation strategy of each unit is obtained, and the real-time dynamic qualified rate of primary frequency regulation of each unit is calculated;

[0045] According to the real-time dynamic pass rate of primary frequency regulation of each unit, the AGC signal is dynamically corrected and adjusted, and the AGC control command is issued.

[0046] In one embodiment, the objective function is expressed as:

[0047] ;

[0048] In the formula, λ is the regional control deviation optimization weight coefficient, T is the total number of sampling points in the time window, t is the sampling time sequence number, ACE t is the regional control deviation at the t-th sampling moment, μ is the unit performance optimization weight coefficient, m is the total number of units participating in AGC frequency regulation, Kpj is the comprehensive frequency regulation performance index of the jth unit;

[0049] The constraint expression is:

[0050] ;

[0051] Where, ΔPAGC j is the AGC instruction change of the jth unit, ΔP S is the power imbalance, ΔPAGC min is the minimum AGC command change limit, ΔPAGC max is the maximum AGC instruction change limit, ACE max It is the maximum value allowed for the regional control deviation.

[0052] According to a second aspect of an embodiment of the present invention, an AGC comprehensive frequency modulation performance index control system based on response demand is provided.

[0053] In one embodiment, the AGC comprehensive frequency modulation performance index control system based on response demand includes:

[0054] The frequency regulation demand forecasting module is used to obtain the characteristics of the power grid frequency regulation demand based on the collected power grid frequency data and regional power balance data, and to establish a power grid frequency regulation demand forecasting model through multi-dimensional time series analysis, and output the short-term power grid frequency regulation demand forecast value;

[0055] The performance evaluation module is used to solve the unit AGC performance parameters and calculate the comprehensive frequency regulation performance index of each unit based on the short-term grid frequency regulation demand forecast value and the real-time status data of various units that can currently participate in AGC frequency regulation;

[0056] The task allocation module is used to generate a dynamic frequency regulation task allocation strategy for each unit based on the comprehensive frequency regulation performance indicators of each unit through a multi-objective optimization algorithm, and adjust the AGC control signal in real time according to the dynamic frequency regulation task allocation strategy of each unit.

[0057] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0058] In one embodiment, the computer device includes a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps of the above method when executing the computer program.

[0059] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0060] In one embodiment, the computer-readable storage medium stores a computer program, which implements the steps of the above method when executed by a processor.

[0061] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0062] (1) The AGC comprehensive frequency regulation performance index control method based on response demand proposed in the present invention establishes the grid frequency regulation demand characteristics including the frequency deviation mean and the power imbalance, and combines time series decomposition and autoregressive moving average analysis to achieve accurate prediction of the AGC command change, AGC target value and grid required response time. At the same time, the present invention establishes a comprehensive frequency regulation performance index through weighted fusion of the three performance parameters of adjustment speed, adjustment accuracy and response time, thus achieving a comprehensive evaluation of the unit's AGC frequency regulation capability and providing a quantitative basis for dynamic frequency regulation task allocation.

[0063] (2) The present invention uses the comprehensive frequency regulation performance index of the unit to establish a multi-objective optimization model with the goals of minimizing regional control deviation and optimizing unit performance. By solving the model, the dynamic frequency regulation task allocation strategy of each unit is obtained. In addition, by calculating the real-time dynamic pass rate of frequency regulation and performing dynamic correction of AGC signals, precise adjustment of AGC control instructions is achieved. This optimization allocation method based on performance indicators not only ensures that the regional control deviation of the power grid is within the allowable range, but also gives full play to the frequency regulation capability of each unit, effectively improving the frequency regulation quality of the power grid.

[0064] 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 invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0066] Figure 1 is a flow chart of a method for controlling an AGC comprehensive frequency modulation performance index based on a response requirement according to an exemplary embodiment;

[0067] Figure 2 is a structural block diagram of an AGC comprehensive frequency modulation performance index control system based on response demand according to an exemplary embodiment;

[0068] Figure 3 The diagram is a schematic structural diagram of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0069] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0070] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0071] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0072] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0073] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0074] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0075] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above modules.

[0076] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0077] Figure 1 An embodiment of the AGC comprehensive frequency modulation performance index control method based on response demand of the present invention is shown.

[0078] In this optional embodiment, the AGC comprehensive frequency modulation performance index control method based on response demand includes:

[0079] Step S101: Based on the collected power grid frequency data and regional power balance data, the power grid frequency regulation demand characteristics are obtained, and a power grid frequency regulation demand prediction model is established through multi-dimensional time series analysis to output a short-term power grid frequency regulation demand prediction value;

[0080] Step S102: according to the short-term grid frequency regulation demand forecast value, combined with the real-time status data of various units that can currently participate in AGC frequency regulation, solve the unit AGC performance parameters and calculate the comprehensive frequency regulation performance index of each unit;

[0081] Step S103: Based on the comprehensive frequency regulation performance index of each unit, a dynamic frequency regulation task allocation strategy for each unit is generated through a multi-objective optimization algorithm, and the AGC control signal is adjusted in real time according to the dynamic frequency regulation task allocation strategy for each unit.

[0082] In this optional embodiment, based on the collected grid frequency data and regional power balance data, the grid frequency regulation demand characteristics are obtained, and through multi-dimensional time series analysis, a grid frequency regulation demand prediction model is established, and the output of the short-term grid frequency regulation demand prediction value includes:

[0083] Step S1011, calculating the grid frequency regulation demand characteristics according to the collected grid frequency data and regional power balance data;

[0084] Step S1012: using the power grid frequency regulation demand characteristics, through time series decomposition and autoregressive moving average analysis, establish a power grid frequency regulation demand prediction model;

[0085] Specifically, the time series decomposition and autoregressive moving average analysis are based on the classic ARIMA (differential autoregressive moving average) model. First, the characteristic data of power grid frequency regulation demand are processed by sliding window, and the window length is set to 15 minutes and the sliding step is 1 minute. Then, the seasonal trend decomposition method (STL decomposition) based on local weighted regression is used to decompose the time series data into long-term trend change items (reflecting the basic trend of power grid load), periodic change items (reflecting the periodic fluctuation of intraday load) and random fluctuation items (characterizing short-term load disturbance). ARIMA models are established for each decomposed item, in which the trend item uses the ARIMA (1, 1, 1) model to capture the long-term change characteristics, the periodic item uses the SARIMA model to describe the recurring periodic pattern, and the random item uses the ARIMA (2, 0, 2) model to characterize the short-term random fluctuation. Finally, the least squares method is used to estimate the parameters of each model, and the prediction results of the three sub-models are weighted and combined to construct a complete power grid frequency regulation demand prediction model.

[0086] Step S1013: Based on the power grid frequency regulation demand prediction model, the real-time power grid frequency regulation demand characteristics are input, and the short-term power grid frequency regulation demand prediction value is output.

[0087] In this optional embodiment, the grid frequency data includes the sampling frequency and the grid rated frequency; the regional power balance data includes the regional total power generation and the regional total load; the grid frequency regulation demand characteristics include the frequency deviation mean and the power imbalance; the short-term grid frequency regulation demand forecast value includes the AGC command change, the AGC target value and the grid required response time.

[0088] In this optional embodiment, the expression of the frequency deviation mean is:

[0089] ;

[0090] Where Δf avg is the mean frequency deviation, n is the number of sampling points in the sliding window, f i is the sampling frequency of the ith sampling point, f nom is the rated frequency of the power grid;

[0091] The expression of power imbalance is:

[0092] ;

[0093] Where ΔP S is the power imbalance, P gen is the total power generation in the region, P load is the total regional load.

[0094] In this optional embodiment, the real-time status data of various types of units include the actual output of the unit, the rated capacity of the unit and the actual response time of the unit; the AGC performance parameters of the unit include the adjustment speed, adjustment accuracy and response time.

[0095] In this optional embodiment, according to the short-term grid frequency regulation demand forecast value, combined with the real-time status data of various units that can currently participate in AGC frequency regulation, the unit AGC performance parameters are solved, and the comprehensive frequency regulation performance index of each unit is calculated, including:

[0096] Step S1021, obtaining the adjustment speed based on the AGC command change, response time and unit rated capacity;

[0097] Step S1022, using the actual output of the unit and the AGC target value to solve the regulation accuracy;

[0098] Step S1023, analyzing the response time according to the actual response time of the unit and the response time required by the power grid;

[0099] Step S1024: Obtain the comprehensive frequency regulation performance index of each unit by weighted fusion of regulation speed, regulation accuracy and response time.

[0100] In this optional embodiment, the expression for adjusting the speed is:

[0101] ;

[0102] In the formula, K1 is the adjustment speed, ΔP AGC is the AGC command change, Δt is the response time, P rated Rated capacity of the unit:

[0103] The expression of adjustment accuracy is:

[0104] ;

[0105] In the formula, K2 is the adjustment accuracy, P actual is the actual output of the unit, P target is the AGC target value;

[0106] The expression for response time is:

[0107] ;

[0108] Where K3 is the response time, tresponse is the actual response time of the unit, t required Require response time for the grid;

[0109] The expression of comprehensive frequency modulation performance index is:

[0110] ;

[0111] In the formula, K p is a comprehensive frequency modulation performance index, w1, w2 and w3 are the adjustment speed weight coefficient, adjustment accuracy weight coefficient and response time weight coefficient respectively, and w1+w2+w3=1.

[0112] In this optional embodiment, based on the comprehensive frequency regulation performance index of each unit, a dynamic frequency regulation task allocation strategy for each unit is generated through a multi-objective optimization algorithm, and according to the dynamic frequency regulation task allocation strategy for each unit, the AGC control signal is adjusted in real time, including:

[0113] Step S1031, using the comprehensive frequency regulation performance index of each unit and combining the control deviation requirements of the power grid area, a multi-objective optimization model including objective functions and constraints is established;

[0114] Step S1032: by solving the multi-objective optimization model, the dynamic frequency regulation task allocation strategy of each unit is obtained, and the real-time dynamic qualified rate of the primary frequency regulation of each unit is calculated;

[0115] Specifically, the calculation of the real-time dynamic qualified rate of the primary frequency regulation is based on the sliding time window method and the statistical analysis method. First, a 30-minute sliding time window is set, and the window slides forward once every minute. In each time window, the actual response time series of the unit is continuously collected, and the sampling frequency is once per second. Then, the actual response time collected is compared with the response time required by the power grid. By calculating the proportion of the number of sampling points whose actual response time is less than the required response time of the power grid to the total number of sampling points, the dynamic qualified rate in the time window is obtained. When the statistical proportion exceeds the preset threshold (set to 90% in this embodiment), it is determined that the primary frequency regulation dynamic response of the unit in this time window is qualified. This real-time calculation method based on the sliding window can dynamically reflect the changes in the frequency regulation performance of the unit, provide timely and accurate basis for subsequent AGC signal adjustment, and effectively improve the real-time and adaptability of frequency regulation control.

[0116] Step S1033: According to the real-time dynamic qualified rate of primary frequency regulation of each unit, the AGC signal is dynamically corrected and adjusted, and an AGC control instruction is issued.

[0117] Specifically, the dynamic correction adjustment of the AGC signal adopts a method based on fuzzy adaptive PID control. The method first establishes a fuzzy rule base with the real-time dynamic qualified rate of the primary frequency modulation as the input variable, and divides the variation range of the qualified rate into three fuzzy subsets of low, medium and high, corresponding to [0, 60%], [40%, 80%] and [60%, 100%] respectively. Then, the parameters of the PID controller are adjusted online based on the fuzzy rules: when the qualified rate is at a low level, the response speed of the unit is improved by increasing the proportional coefficient (adjusted in the range of 0.8-1.2 in this embodiment); when the qualified rate is at a medium level, the proportional coefficient and the integral time constant are adjusted at the same time to balance the response speed and stability; when the qualified rate is close to 100%, the integral time constant is appropriately increased (in the range of 10-30 seconds in this embodiment) to improve the system stability, and the differential time constant is reduced to suppress high-frequency oscillation. This PID parameter tuning method based on fuzzy adaptation can dynamically optimize the control effect according to the real-time response characteristics of the unit, and effectively improve the accuracy and reliability of AGC frequency modulation.

[0118] In this optional embodiment, the expression of the objective function is:

[0119] ;

[0120] In the formula, λ is the regional control deviation optimization weight coefficient, T is the total number of sampling points in the time window, t is the sampling time sequence number, ACE t is the regional control deviation at the t-th sampling moment, μ is the unit performance optimization weight coefficient, m is the total number of units participating in AGC frequency regulation, K pj is the comprehensive frequency regulation performance index of the jth unit;

[0121] The constraint expression is:

[0122] ;

[0123] Where, ΔPAGC j is the AGC instruction change of the jth unit, ΔP S is the power imbalance, ΔPAGC min is the minimum AGC command change limit, ΔPAGC max is the maximum AGC instruction change limit, ACE max It is the maximum value allowed for the regional control deviation.

[0124] Figure 2 An embodiment of the AGC comprehensive frequency modulation performance index control system based on response demand of the present invention is shown.

[0125] In this optional embodiment, the AGC comprehensive frequency modulation performance index control system based on response demand includes:

[0126] The frequency regulation demand prediction module 201 is used to obtain the characteristics of the power grid frequency regulation demand based on the collected power grid frequency data and regional power balance data, and establish a power grid frequency regulation demand prediction model through multi-dimensional time series analysis to output a short-term power grid frequency regulation demand prediction value;

[0127] The performance evaluation module 202 is used to solve the unit AGC performance parameters and calculate the comprehensive frequency regulation performance index of each unit based on the short-term power grid frequency regulation demand forecast value and the real-time status data of various units that can currently participate in AGC frequency regulation;

[0128] The task allocation module 203 is used to generate a dynamic frequency regulation task allocation strategy for each unit based on the comprehensive frequency regulation performance index of each unit through a multi-objective optimization algorithm, and adjust the AGC control signal in real time according to the dynamic frequency regulation task allocation strategy of each unit.

[0129] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0130] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0131] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0132] In addition, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0133] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0134] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. AGC comprehensive frequency modulation performance index control method based on response demand, characterized in that: The AGC comprehensive frequency modulation performance index control method based on response demand includes: Based on the collected grid frequency data and regional power balance data, the grid frequency regulation demand characteristics are obtained, and through multi-dimensional time series analysis, a grid frequency regulation demand prediction model is established to output the short-term grid frequency regulation demand prediction value; According to the short-term grid frequency regulation demand forecast value, combined with the real-time status data of various units that can currently participate in AGC frequency regulation, the unit AGC performance parameters are solved, and the comprehensive frequency regulation performance index of each unit is calculated; Based on the comprehensive frequency regulation performance indicators of each unit, a dynamic frequency regulation task allocation strategy for each unit is generated through a multi-objective optimization algorithm, and the AGC control signal is adjusted in real time according to the dynamic frequency regulation task allocation strategy of each unit.

2. The AGC comprehensive frequency modulation performance index control method based on response demand according to claim 1 is characterized in that: The method of obtaining the grid frequency regulation demand characteristics based on the collected grid frequency data and regional power balance data, and establishing a grid frequency regulation demand prediction model through multi-dimensional time series analysis, and outputting the short-term grid frequency regulation demand prediction value includes: Calculate the grid frequency regulation demand characteristics based on the collected grid frequency data and regional power balance data; By using the characteristics of power grid frequency regulation demand, a power grid frequency regulation demand prediction model is established through time series decomposition and autoregressive moving average analysis. Based on the power grid frequency regulation demand prediction model, the real-time power grid frequency regulation demand characteristics are input and the short-term power grid frequency regulation demand prediction value is output.

3. The AGC comprehensive frequency modulation performance index control method based on response demand according to claim 2 is characterized in that: The grid frequency data includes sampling frequency and grid rated frequency; The regional power balance data includes the regional total power generation and the regional total load; The grid frequency regulation demand characteristics include frequency deviation mean and power imbalance; The short-term power grid frequency regulation demand forecast value includes the AGC instruction change, the AGC target value and the power grid required response time.

4. The AGC comprehensive frequency modulation performance index control method based on response demand according to claim 3 is characterized in that: The expression of the frequency deviation mean is: ； Where Δf avg is the mean frequency deviation, n is the number of sampling points in the sliding window, f i is the sampling frequency of the ith sampling point, f nom is the rated frequency of the power grid; The expression of the power imbalance is: ； In the formula, ΔP S is the power imbalance, P gen is the total power generation in the region, P load is the total regional load.

5. The AGC comprehensive frequency modulation performance index control method based on response demand according to claim 3 is characterized in that: The real-time status data of various units include actual output of the unit, rated capacity of the unit and actual response time of the unit; The unit AGC performance parameters include regulation speed, regulation accuracy and response time.

6. The AGC comprehensive frequency modulation performance index control method based on response demand according to claim 5 is characterized in that: According to the short-term grid frequency regulation demand forecast value, combined with the real-time status data of various units that can currently participate in AGC frequency regulation, the unit AGC performance parameters are solved, and the comprehensive frequency regulation performance indicators of each unit are calculated, including: Obtain the regulation speed based on the AGC command change, response time, and rated capacity of the unit; Using the actual output of the unit and the AGC target value, the regulation accuracy is solved; Analyze the response time based on the actual response time of the unit and the response time required by the power grid; The comprehensive frequency regulation performance index of each unit is obtained by weighted fusion of regulation speed, regulation accuracy and response time.

7. The AGC comprehensive frequency modulation performance index control method based on response demand according to claim 6 is characterized in that: The expression of the adjustment speed is: ； In the formula, K1 is the adjustment speed, ΔP AGC is the AGC command change, Δt is the response time, P rated Rated capacity of the unit: The expression of the adjustment accuracy is: ； In the formula, K2 is the adjustment accuracy, P actual is the actual output of the unit, P target is the AGC target value; The expression of the response time is: ； Where K3 is the response time, t response is the actual response time of the unit, t required Require response time for the grid; The expression of the comprehensive frequency modulation performance index is: ； In the formula, K p is a comprehensive frequency modulation performance index, w1, w2 and w3 are the adjustment speed weight coefficient, adjustment accuracy weight coefficient and response time weight coefficient respectively, and w1+w2+w3=1.

8. The AGC comprehensive frequency modulation performance index control method based on response demand according to claim 1 is characterized in that: The method of generating a dynamic frequency regulation task allocation strategy for each unit based on the comprehensive frequency regulation performance index of each unit through a multi-objective optimization algorithm, and adjusting the AGC control signal in real time according to the dynamic frequency regulation task allocation strategy of each unit includes: Using the comprehensive frequency regulation performance index of each unit and the control deviation requirements of the power grid area, a multi-objective optimization model including objective functions and constraints is established; By solving the multi-objective optimization model, the dynamic frequency regulation task allocation strategy of each unit is obtained, and the real-time dynamic qualified rate of primary frequency regulation of each unit is calculated; According to the real-time dynamic pass rate of primary frequency regulation of each unit, the AGC signal is dynamically corrected and adjusted, and the AGC control command is issued.

9. The AGC comprehensive frequency modulation performance index control method based on response demand according to claim 8, characterized in that: The expression of the objective function is: ； In the formula, λ is the regional control deviation optimization weight coefficient, T is the total number of sampling points in the time window, t is the sampling time sequence number, ACE t is the regional control deviation at the t-th sampling moment, μ is the unit performance optimization weight coefficient, m is the total number of units participating in AGC frequency regulation, K pj is the comprehensive frequency regulation performance index of the jth unit; The constraint condition is expressed as: ； Where, ΔPAGC j is the AGC instruction change of the jth unit, ΔP S is the power imbalance, ΔPAGC min is the minimum AGC command change limit, ΔPAGC max is the maximum AGC instruction change limit, ACE max It is the maximum value allowed for the regional control deviation.

10. AGC comprehensive frequency modulation performance index control system based on response demand, characterized in that: The AGC comprehensive frequency modulation performance index control system based on response demand includes: The frequency regulation demand forecasting module is used to obtain the characteristics of the power grid frequency regulation demand based on the collected power grid frequency data and regional power balance data, and to establish a power grid frequency regulation demand forecasting model through multi-dimensional time series analysis, and output the short-term power grid frequency regulation demand forecast value; The performance evaluation module is used to solve the unit AGC performance parameters and calculate the comprehensive frequency regulation performance index of each unit based on the short-term grid frequency regulation demand forecast value and the real-time status data of various units that can currently participate in AGC frequency regulation; The task allocation module is used to generate a dynamic frequency regulation task allocation strategy for each unit based on the comprehensive frequency regulation performance indicators of each unit through a multi-objective optimization algorithm, and adjust the AGC control signal in real time according to the dynamic frequency regulation task allocation strategy of each unit.

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