Large disturbance adaptive adjustment control method for primary frequency regulation of thermal power units under extreme operating conditions

Abstract

The present invention relates to the technical field of thermal power unit control, and discloses a thermal power unit primary frequency modulation large disturbance adaptive adjustment control method under extreme working conditions, the method comprising: using a sensor to collect the operating status data of the thermal power unit in real time, and performing denoising on the collected data; monitoring the power grid frequency disturbance, constructing an adaptive control model, and solving the adaptive control model to obtain the thermal power unit primary frequency modulation control strategy; and adaptively and robustly optimizing the thermal power unit primary frequency modulation control strategy. The present invention uses the correlation between the current period operating status data and the lag period operating status data as the abnormality of the thermal power unit operating state, realizes the power grid frequency disturbance monitoring, solves the adaptive control model, obtains the thermal power unit primary frequency modulation control strategy that prevents the power grid frequency deviation from further expanding, and combines the overall power grid frequency disturbance information to perform adaptive robust optimization to realize the thermal power unit primary frequency modulation adaptive adjustment control.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal power unit control, and in particular to a large disturbance adaptive adjustment control method for primary frequency modulation of a thermal power unit under extreme working conditions. Background Art

[0002] During the operation of a thermal power unit, it may face various extreme conditions, such as sudden load fluctuations, external interference, etc. These extreme conditions may cause large disturbances in the primary frequency regulation system of the thermal power unit. The primary frequency regulation system refers to the system that controls the output frequency of the thermal power unit. Its stability and response speed are crucial to maintaining the stability of the power grid frequency. Under extreme conditions, the primary frequency regulation system may fail or become unstable, affecting the safe and stable operation of the thermal power unit and even having an adverse effect on the power grid. To address this problem, the present invention proposes a large-disturbance adaptive adjustment control method for the primary frequency regulation of a thermal power unit under extreme conditions, which improves the response speed and energy utilization efficiency of the thermal power unit through adaptive adjustment control and reduces operating costs. Summary of the invention

[0003] In view of this, the present invention provides a method for adaptively adjusting and controlling a large disturbance of primary frequency modulation of a thermal power unit under extreme working conditions, the purpose of which is to: 1) collect status data of operating status indicators of different thermal power units, and perform filtering and denoising processing in combination with the frequency of the status data, and calculate the abnormality of the operating status of the thermal power unit according to the correlation between the operating status data of the current period and the operating status data of the lag period in the operating status data of the thermal power unit after denoising, and obtain the power grid frequency disturbance monitoring result at the current moment, so as to realize the power grid frequency disturbance monitoring under extreme working conditions. If the power grid frequency disturbance monitoring result exceeds the preset threshold, it means that a large disturbance under extreme working conditions is monitored, and then adaptively adjusting and controlling a large disturbance of primary frequency modulation is performed; 2) construct an adaptive control model, wherein the adaptive control model includes a control objective function and control constraints, the variables in the control objective function are the speed control amount and the temperature control amount of the thermal power unit, the control constraints are to make the speed and temperature of the thermal power unit after control within the preset control range, the function value of the control objective function represents the difference between the grid frequency after control and the standard grid frequency, the adaptive control model is solved to obtain the speed control amount and the temperature control amount of the thermal power unit that prevent the grid frequency deviation from further expanding, the speed control amount and the temperature control amount of the thermal power unit obtained by the solution are used as the primary frequency regulation control strategy of the thermal power unit, and the current primary frequency regulation control strategy results of multiple thermal power units are combined for adaptive robust weighted processing, to obtain the primary frequency regulation control strategy of the thermal power unit optimized in combination with the overall disturbance information of the grid frequency, and to adjust and control the thermal power unit.

[0004] To achieve the above object, the present invention provides a method for adaptively adjusting and controlling a large disturbance of primary frequency modulation of a thermal power unit under extreme working conditions, comprising the following steps:

[0005] S1: using sensors to collect the operating status data of the thermal power unit in real time, wherein the operating status data of the thermal power unit includes the speed, temperature, pressure parameters and grid frequency data of the thermal power unit, and performing denoising processing on the collected data to obtain the denoised operating status data of the thermal power unit, wherein Butterworth filtering is the main implementation method of the denoising processing;

[0006] S2: Monitor the grid frequency disturbance based on the denoised thermal power unit operating status data, and build an adaptive control model, which uses the grid frequency disturbance monitoring results and the denoised thermal power unit operating status data as input variables, and uses the primary frequency regulation control strategy of the thermal power unit as the model solution result;

[0007] S3: Solve the adaptive control model to obtain the primary frequency regulation control strategy of the thermal power unit;

[0008] S4: Adaptively and robustly optimize the primary frequency regulation control strategy of the thermal power unit, obtain the primary frequency regulation control strategy of the thermal power unit after adaptive robust optimization, and adjust and control the thermal power unit.

[0009] As a further improvement method of the present invention:

[0010] Optionally, in step S1, using sensors to collect the operating status data of the thermal power unit in real time includes:

[0011] The sensors are used to collect the operating status data of the thermal power unit in real time, where the operating status data of the thermal power unit includes the speed, temperature, pressure parameters and grid frequency data of the thermal power unit. The operating status data of the thermal power unit collected at the current time t is:

[0012] { x i t =( x i (tN), x i (t-N+1),..., x i (tn)..., x i (t-2), x i (t-1), x i (t))|i∈[1,4]} ;

[0013] in:

[0014] represents the state data of the operating state index of the i-th thermal power unit collected at the current time t, i∈[1,4] ,The 1st to 4th types of thermal power unit operating status indicators are the speed, temperature, pressure parameter indicators of the thermal power unit and the grid frequency indicator;

[0015] It represents the index data of the thermal power unit under the operating status index of the i-th thermal power unit at time t; It represents the index data of the thermal power unit under the operating status index of the i-th thermal power unit at time tN; the time interval between adjacent moments is In the embodiment of the present invention, Set to 5 seconds;

[0016] Compared with the indicator data N groups of historical indicator data, n ∈ [1,N] ; In the embodiment of the present invention, N is set to 12;

[0017] The data collected at the current time t is denoised to obtain the denoised operating status data of the thermal power unit.

[0018] Optionally, the denoising process is performed on the data collected at the current time t to obtain the denoised operating status data of the thermal power unit, including:

[0019] The data collected at the current time t is denoised to obtain the denoised operating status data of the thermal power unit, wherein the denoising process is as follows:

[0020] S11: Building a denoising filter ;

[0021] S12: De-noising the state data of the operating state indicators of different thermal power units using a de-noising filter, wherein the de-noising filter based on Status data The denoising formula is:

[0022] ;

[0023] ;

[0024] ;

[0025] in:

[0026] Represents status data The denoising result is Indicates indicator data The filtering result of

[0027] Denotes the denoising filter The cut-off frequency, Represents status data The frequency of L represents the denoising filter In the embodiment of the present invention, the denoising filter The order of ;

[0028] S13: Construct the de-noised thermal power unit operation status data:

[0029] { X i t =( X i (tN), X i (t-N+1),..., X i (tn)..., X i (t-2), X i (t-1), X i (t))|i∈[1,4]} ;

[0030] in:

[0031] Represents status data The denoising result.

[0032] Optionally, in step S2, monitoring the grid frequency disturbance based on the de-noised thermal power unit operating status data includes:

[0033] The grid frequency disturbance is monitored based on the de-noised thermal power unit operating status data, where the grid frequency disturbance monitoring process at the current time t is:

[0034] S21: Obtaining the de-noised operating status data of the thermal power unit;

[0035] S22: Calculate the abnormality of the thermal power unit operation status at the current time t:

[0036] ;

[0037] ;

[0038] in:

[0039] Indicates the abnormality of the operating status of the thermal power unit at the current time t;

[0040] It represents the similarity of the operating status of the thermal power unit under the operating status index of the jth thermal power unit at the current time t, ;

[0041] Indicates the de-noised thermal power unit operating status data The mean of the data;

[0042] represents the hysteresis factor, Set to 2;

[0043] S23: Calculate and obtain the power grid frequency disturbance monitoring result at the current time t:

[0044] ;

[0045] in:

[0046] Indicates the power grid frequency disturbance monitoring result at the current time t;

[0047] An adaptive control model is constructed, which takes the grid frequency disturbance monitoring results and the denoised thermal power unit operating status data as input variables, and takes the primary frequency regulation control strategy of the thermal power unit as the model solution result.

[0048] Optionally, the constructing of the adaptive control model includes:

[0049] Construct an adaptive control model, wherein the adaptive control model includes a control objective function and control constraints, the variables in the control objective function are the speed control amount and the temperature control amount of the thermal power unit, the control constraints are to make the speed and temperature of the thermal power unit after control within a preset control range, the function value of the control objective function represents the difference between the grid frequency after control and the standard grid frequency, the adaptive control model is solved to obtain the speed control amount and the temperature control amount of the thermal power unit that prevent the grid frequency deviation from further expanding, and the solved speed control amount and the temperature control amount of the thermal power unit are used as the primary frequency regulation control strategy of the thermal power unit;

[0050] The control objective function in the adaptive control model is:

[0051] F( i t )=min| W t [ X 1 t + i t 1 , X 2 t + i t 2 ]- fresh standard | ;

[0052] W t = argmin w ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | ;

[0053] in:

[0054] represents the control objective function in the adaptive control model, Represents the control objective function The variables in i t =[ i t 1 , i t 2 ] , represents the speed control value of the thermal power unit at the current time t, Indicates the temperature control value of the thermal power unit at the current time t;

[0055] represents the control parameter at the current time t, Indicates standard grid frequency;

[0056] | W t [ X 1 t + i t 1 , X 2 t + i t 2 ]- fresh standard | Indicates the difference between the grid frequency after regulation and the standard grid frequency at the current time t;

[0057] argmin w ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | Indicates that the selection makes ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | The minimum w is obtained as output;

[0058] The constraints in the adaptive control model are:

[0059] ;

[0060] ;

[0061] in:

[0062] Indicates the minimum value of the speed of the thermal power unit. Indicates the maximum speed of the thermal power unit;

[0063] Indicates the minimum temperature of the thermal power unit. Indicates the maximum temperature of the thermal power unit.

[0064] Optionally, in step S3, solving the adaptive control model to obtain a primary frequency regulation control strategy for the thermal power unit includes:

[0065] The adaptive control model is solved to obtain the primary frequency regulation control strategy of the thermal power unit. The solution process of the adaptive control model is as follows:

[0066] S31: The adaptive control model receives the grid frequency disturbance monitoring results And the denoised thermal power unit operating status data, if the grid frequency disturbance monitoring results If it is higher than the preset threshold, it indicates that there is a grid frequency disturbance at the current time t, and the process goes to step S32; otherwise, the process returns to step S1 to collect the operating status data of the thermal power unit at time t+1 for real-time regulation;

[0067] S32: Construct the control objective function at the current time t and constraints;

[0068] S33: Initialize and generate the position coordinates of U jackals, wherein the position coordinates of each jackal correspond to the speed control amount of the thermal power unit and the temperature control amount of the thermal power unit, wherein the position coordinates of the u-th jackal generated by initialization are:

[0069] ;

[0070] in:

[0071] represents the position coordinates of the u-th jackal generated by initialization, where Corresponding to the speed control amount of the thermal power unit, Corresponding to the temperature control amount of thermal power units, u ∈ [1,U] ;

[0072] The position coordinates of each jackal generated by initialization satisfy the following constraints:

[0073] i minutes 1 ≤ X 1 t + location u 0 (1) ≤ i max 1 ,u ∈ [1,U] ;

[0074] i minutes 2 ≤ X 2 t + location u 0 (2) ≤ i max 2 ,u ∈ [1,U] ;

[0075] S34: Set the current iteration number of the jackal position coordinates to d, and the maximum iteration number to Max, then the d-th iteration result of the u-th jackal position coordinates is , the initial value of d is 0;

[0076] S35: Calculate the escape energy factor of the prey after the dth iteration of the jackal's position coordinates:

[0077] ;

[0078] in:

[0079] represents the escape energy factor of the prey after the dth iteration of the jackal's position coordinates;

[0080] Indicates the preset maximum escape energy factor, Indicates the preset minimum escape energy factor;

[0081] S36: Iterate the jackal position coordinates, wherein the iteration formula of the u-th jackal position coordinates is:

[0082] ;

[0083] ;

[0084] ;

[0085] in:

[0086] represents the random step size, represents a normal distribution, represents the gamma function, represents the exponential adjustment coefficient, Set to 2;

[0087] Indicates that it follows a normal distribution A random number;

[0088] Indicates that it follows a normal distribution A random number;

[0089] It means that the position coordinates of the U jackals after the dth iteration are used as the input of the control objective function, so that the control objective function reaches the minimum position coordinate;

[0090] S37: Let d=d+1, return to step S35, iterate the position coordinates of U jackals until the maximum number of iterations is reached, and select the position coordinates of U jackals after the Max-th iteration as the input of the control objective function, and take the minimum position coordinate that satisfies the constraint condition and makes the control objective function reach the minimum as the primary frequency regulation control strategy of the thermal power unit .

[0091] Optionally, in step S4, adaptive robust optimization is performed on the primary frequency regulation control strategy of the thermal power unit, and adjustment control is performed on the thermal power unit, including:

[0092] The primary frequency regulation control strategy of the thermal power unit is adaptively and robustly optimized to obtain the primary frequency regulation control strategy of the thermal power unit after adaptive and robust optimization. The adaptive robust optimization process is:

[0093] S41: Obtain the primary frequency regulation control strategy of all thermal power units at the current time t. If the thermal power unit does not generate the primary frequency regulation control strategy of the thermal power unit at the current time t, set the primary frequency regulation control strategy of the thermal power unit at the current time t to [0,0] ;

[0094] S42: Calculate the primary frequency control strategy of thermal power units The robustness weight :

[0095] ;

[0096] in:

[0097] Q represents the set of primary frequency regulation control strategies of all thermal power units at the current time t. , Representing a collection A primary frequency regulation control strategy for any group of thermal power units;

[0098] S43: Primary frequency control strategy for thermal power units Robust optimization is performed, and the primary frequency regulation control strategy of the thermal power unit after robust optimization is ;

[0099] Primary frequency regulation control strategy of thermal power units after robust optimization Primary frequency control strategy for thermal power units The corresponding thermal power units are adjusted and controlled.

[0100] In order to solve the above problems, the present invention provides a large disturbance adaptive adjustment control system for primary frequency modulation of a thermal power unit, characterized in that the system comprises:

[0101] The data acquisition module is used to collect the operating status data of the thermal power unit in real time using sensors, and to perform denoising on the collected data to obtain the denoised operating status data of the thermal power unit;

[0102] The disturbance monitoring module is used to monitor the grid frequency disturbance based on the de-noised thermal power unit operation status data;

[0103] The adaptive control device is used to construct an adaptive control model, solve the adaptive control model, obtain the primary frequency regulation control strategy of the thermal power unit, perform adaptive robust optimization on the primary frequency regulation control strategy of the thermal power unit, obtain the primary frequency regulation control strategy of the thermal power unit after adaptive robust optimization, and adjust and control the thermal power unit.

[0104] In order to solve the above problem, the present invention provides an electronic device, the electronic device comprising:

[0105] A memory storing at least one instruction;

[0106] Communication interface, enabling electronic equipment to communicate; and

[0107] The processor executes the instructions stored in the memory to implement the above-mentioned large disturbance adaptive adjustment control method for primary frequency modulation of thermal power units under extreme working conditions.

[0108] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned method for adaptively adjusting the large disturbance of primary frequency modulation of a thermal power unit under extreme working conditions.

[0109] Compared with the prior art, the present invention proposes a large disturbance adaptive adjustment control method for primary frequency modulation of thermal power units under extreme working conditions. The technology has the following advantages:

[0110] First, this scheme proposes a grid frequency disturbance monitoring under extreme working conditions, denoises the data collected at the current time t, and obtains the denoised thermal power unit operating status data. The denoising process is as follows: Construct a denoising filter ; The state data of the operating state indicators of different thermal power units are denoised by using denoising filters. Status data The denoising formula is:

[0111] ;

[0112] ;

[0113] ;

[0114] in: Represents status data The denoising result is Indicates indicator data The filtering result of Denotes the denoising filter The cut-off frequency, Represents status data The frequency of L represents the denoising filter The order of; constitutes the denoised thermal power unit operating status data:

[0115] { X i t =( X i (tN), X i (t-N+1),..., X i (tn)..., X i (t-2), X i (t-1), X i (t))|i∈[1,4]}

[0116] in: Represents status data The denoising result. The grid frequency disturbance is monitored based on the denoised operating status data of the thermal power unit. The monitoring process of the grid frequency disturbance at the current time t is as follows: obtain the denoised operating status data of the thermal power unit; calculate the abnormality of the operating status of the thermal power unit at the current time t:

[0117] ;

[0118] ;

[0119] in: Indicates the abnormality of the operating status of the thermal power unit at the current time t; It represents the similarity of the operating status of the thermal power unit under the operating status index of the jth thermal power unit at the current time t, ; Indicates the de-noised thermal power unit operating status data The mean of the data; represents the hysteresis factor, Set to 2; calculate the power grid frequency disturbance monitoring result at the current time t:

[0120] ;

[0121] in: Indicates the grid frequency disturbance monitoring result at the current moment t. This scheme collects the status data of the operating status indicators of different thermal power units, and performs filtering and denoising processing based on the frequency of the status data to remove the white noise in the data collection process. According to the correlation between the operating status data of the current period and the operating status data of the lag period in the operating status data of the thermal power unit after denoising, the abnormality of the operating status of the thermal power unit is calculated, and the grid frequency disturbance monitoring result at the current moment is obtained, so as to realize the grid frequency disturbance monitoring under extreme working conditions. If the grid frequency disturbance monitoring result exceeds the preset threshold, it means that a large disturbance under extreme working conditions is monitored, and then a frequency modulation large disturbance adaptive adjustment control is performed.

[0122] At the same time, this scheme proposes a method for generating a primary frequency regulation control strategy, constructs an adaptive regulation model, wherein the adaptive regulation model includes a regulation objective function and a regulation constraint condition, the variables in the regulation objective function are the speed regulation amount and the temperature regulation amount of the thermal power unit, the regulation constraint condition is to make the speed and temperature of the thermal power unit after regulation within the preset regulation range, the function value of the regulation objective function represents the difference between the grid frequency after regulation and the standard grid frequency, the adaptive regulation model is solved, and the speed regulation amount and the temperature regulation amount of the thermal power unit that prevent the grid frequency deviation from further expanding are obtained, and the speed regulation amount and the temperature regulation amount of the thermal power unit obtained by the solution are used as the primary frequency regulation control strategy of the thermal power unit; the regulation objective function in the adaptive regulation model is:

[0123] F( i t )=min| W t [ X 1 t + i t 1 , X 2 t + i t 2 ]- fresh standard | ;

[0124] W t = argmin w ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | ;

[0125] in: represents the control objective function in the adaptive control model, Represents the control objective function The variables in i t =[ i t 1 , i t 2 ] , represents the speed control value of the thermal power unit at the current time t, Indicates the temperature control value of the thermal power unit at the current time t; represents the control parameter at the current time t, Indicates standard grid frequency; | W t [ X 1 t + i t 1 , X 2 t + i t 2 ]- fresh standard | Indicates the difference between the grid frequency after regulation and the standard grid frequency at the current time t; argmin w ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | Indicates that the selection makes ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | The minimum w is taken as the output; the constraints in the adaptive control model are:

[0126] ;

[0127] ;

[0128] in: Indicates the minimum value of the speed of the thermal power unit. Indicates the maximum speed of the thermal power unit; Indicates the minimum temperature of the thermal power unit. Represents the maximum value of the temperature of the thermal power unit. The primary frequency regulation control strategy of the thermal power unit is adaptively and robustly optimized to obtain the primary frequency regulation control strategy of the thermal power unit after adaptive and robust optimization. The adaptive robust optimization process is as follows: obtain the primary frequency regulation control strategy of all thermal power units at the current time t. If the thermal power unit does not generate the primary frequency regulation control strategy of the thermal power unit at the current time t, then set the primary frequency regulation control strategy of the thermal power unit at the current time t to [0,0] ; Calculate the primary frequency control strategy of thermal power units The robustness weight :

[0129] ;

[0130] Where: Q represents the set of primary frequency regulation control strategies of all thermal power units at the current time t, , Representing a collection A frequency regulation control strategy for any group of thermal power units in the Robust optimization is performed, and the primary frequency regulation control strategy of the thermal power unit after robust optimization is ;Use the robust optimized primary frequency control strategy of thermal power units Primary frequency control strategy for thermal power units The corresponding thermal power units are adjusted and controlled. This scheme combines the results of the current primary frequency regulation control strategies of multiple thermal power units for adaptive robust weighted processing, obtains the primary frequency regulation control strategy of the thermal power units optimized in combination with the overall disturbance information of the power grid frequency, and adjusts and controls the thermal power units. BRIEF DESCRIPTION OF THE DRAWINGS

[0131] Figure 1 A schematic flow chart of a method for adaptively adjusting and controlling a large disturbance of primary frequency modulation of a thermal power unit under extreme working conditions provided by an embodiment of the present invention;

[0132] Figure 2 A functional module diagram of a large disturbance adaptive adjustment control system for primary frequency modulation of a thermal power unit provided by an embodiment of the present invention;

[0133] Figure 2 In: 100 large disturbance adaptive adjustment control system for primary frequency regulation of thermal power units, 101 data acquisition module, 102 disturbance monitoring module, 103 adaptive control device;

[0134] Figure 3 A schematic diagram of the structure of an electronic device for implementing a large disturbance adaptive adjustment control method for primary frequency modulation of a thermal power unit under extreme working conditions provided by an embodiment of the present invention.

[0135] Figure 3In: 1 electronic device, 10 processor, 11 memory, 12 program, 13 communication interface.

[0136] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0137] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0138] The embodiment of the present application provides a method for adaptively adjusting and controlling a large disturbance of primary frequency modulation of a thermal power unit under extreme working conditions. The execution subject of the method for adaptively adjusting and controlling a large disturbance of primary frequency modulation of a thermal power unit under extreme working conditions includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for adaptively adjusting and controlling a large disturbance of primary frequency modulation of a thermal power unit under extreme working conditions can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0139] Embodiment 1:

[0140] S1: Using sensors to collect the operating status data of the thermal power unit in real time, where the operating status data of the thermal power unit includes the speed, temperature, pressure parameters of the thermal power unit and the grid frequency data, and performing denoising on the collected data to obtain the denoised operating status data of the thermal power unit.

[0141] In step S1, sensors are used to collect the operating status data of the thermal power unit in real time, including:

[0142] The sensors are used to collect the operating status data of the thermal power unit in real time, where the operating status data of the thermal power unit includes the speed, temperature, pressure parameters and grid frequency data of the thermal power unit. The operating status data of the thermal power unit collected at the current time t is:

[0143] { x i t =( x i (tN), x i (t-N+1),..., x i (tn)..., x i (t-2), x i (t-1), x i (t))|i∈[1,4]} ;

[0144] in:

[0145] represents the state data of the operating state index of the i-th thermal power unit collected at the current time t, i∈[1,4] ,The 1st to 4th types of thermal power unit operating status indicators are the speed, temperature, pressure parameter indicators of the thermal power unit and the grid frequency indicator;

[0146] It represents the index data of the thermal power unit under the operating status index of the i-th thermal power unit at time t; It represents the index data of the thermal power unit under the operating status index of the i-th thermal power unit at time tN; the time interval between adjacent moments is In the embodiment of the present invention, Set to 5 seconds;

[0147] Compared with the indicator data N groups of historical indicator data, n ∈ [1,N] ; In the embodiment of the present invention, N is set to 12;

[0148] The data collected at the current time t is denoised to obtain the denoised operating status data of the thermal power unit.

[0149] The denoising process is performed on the data collected at the current time t to obtain the denoised operating status data of the thermal power unit, including:

[0150] The data collected at the current time t is denoised to obtain the denoised operating status data of the thermal power unit, wherein the denoising process is as follows:

[0151] S11: Building a denoising filter ;

[0152] S12: De-noising the state data of the operating state indicators of different thermal power units using a de-noising filter, wherein the de-noising filter based on Status data The denoising formula is:

[0153] ;

[0154] ;

[0155] ;

[0156] in:

[0157] Represents status data The denoising result is Indicates indicator data The filtering result of

[0158] Denotes the denoising filter The cut-off frequency, Represents status data The frequency of L represents the denoising filter In the embodiment of the present invention, the denoising filter The order of ;

[0159] S13: Construct the de-noised thermal power unit operation status data:

[0160] { X i t =( X i (tN), X i (t-N+1),..., X i (tn)..., X i (t-2), X i (t-1), X i (t))|i∈[1,4]} ;

[0161] in:

[0162] Represents status data The denoising result.

[0163] S2: Monitor the grid frequency disturbance based on the denoised operating status data of the thermal power units, and build an adaptive control model. The adaptive control model uses the grid frequency disturbance monitoring results and the denoised operating status data of the thermal power units as input variables, and uses the primary frequency regulation control strategy of the thermal power units as the model solution result.

[0164] In the step S2, the power grid frequency disturbance is monitored based on the de-noised thermal power unit operation status data, including:

[0165] The grid frequency disturbance is monitored based on the de-noised thermal power unit operating status data, where the grid frequency disturbance monitoring process at the current time t is:

[0166] S21: Obtaining the de-noised operating status data of the thermal power unit;

[0167] S22: Calculate the abnormality of the operating state of the thermal power unit at the current time t:

[0168] ;

[0169] ;

[0170] in:

[0171] Indicates the abnormality of the operating status of the thermal power unit at the current time t;

[0172] It represents the similarity of the operating status of the thermal power unit under the operating status index of the jth thermal power unit at the current time t, ;

[0173] Indicates the de-noised thermal power unit operating status data The mean of the data;

[0174] represents the hysteresis factor, Set to 2;

[0175] S23: Calculate and obtain the power grid frequency disturbance monitoring result at the current time t:

[0176] ;

[0177] in:

[0178] Indicates the power grid frequency disturbance monitoring result at the current time t;

[0179] An adaptive control model is constructed, which takes the grid frequency disturbance monitoring results and the denoised thermal power unit operating status data as input variables, and takes the primary frequency regulation control strategy of the thermal power unit as the model solution result.

[0180] The constructing of the adaptive control model comprises:

[0181] Construct an adaptive control model, wherein the adaptive control model includes a control objective function and control constraints, the variables in the control objective function are the speed control amount and the temperature control amount of the thermal power unit, the control constraints are to make the speed and temperature of the thermal power unit after control within a preset control range, the function value of the control objective function represents the difference between the grid frequency after control and the standard grid frequency, the adaptive control model is solved to obtain the speed control amount and the temperature control amount of the thermal power unit that prevent the grid frequency deviation from further expanding, and the solved speed control amount and the temperature control amount of the thermal power unit are used as the primary frequency regulation control strategy of the thermal power unit;

[0182] The control objective function in the adaptive control model is:

[0183] F( i t )=min| W t [ X 1 t + i t 1 , X 2 t + i t 2 ]- fresh standard | ;

[0184] W t = argmin w ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | ;

[0185] in:

[0186] represents the control objective function in the adaptive control model, Represents the control objective function The variables in i t =[ i t 1 , i t 2 ] , represents the speed control value of the thermal power unit at the current time t, Indicates the temperature control value of the thermal power unit at the current time t;

[0187] represents the control parameter at the current time t, Indicates standard grid frequency;

[0188] | W t [ X 1 t + i t 1 , X 2 t + i t 2 ]- fresh standard | Indicates the difference between the grid frequency after regulation and the standard grid frequency at the current time t;

[0189] argmin w ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | Indicates that the selection makes ∑ n=1 N |w[ X 1 (tn), X 2 (tn) ]- X 4 (tn) | The minimum w is obtained as output;

[0190] The constraints in the adaptive control model are:

[0191] ;

[0192] ;

[0193] in:

[0194] Indicates the minimum value of the speed of the thermal power unit. Indicates the maximum speed of the thermal power unit;

[0195] Indicates the minimum temperature of the thermal power unit. Indicates the maximum temperature of the thermal power unit.

[0196] S3: Solve the adaptive control model to obtain the primary frequency regulation control strategy of the thermal power unit.

[0197] In the step S3, the adaptive control model is solved to obtain the primary frequency regulation control strategy of the thermal power unit, including:

[0198] The adaptive control model is solved to obtain the primary frequency regulation control strategy of the thermal power unit. The solution process of the adaptive control model is as follows:

[0199] S31: The adaptive control model receives the grid frequency disturbance monitoring results And the denoised thermal power unit operating status data, if the grid frequency disturbance monitoring results If it is higher than the preset threshold, it indicates that there is a grid frequency disturbance at the current time t, and the process goes to step S32; otherwise, the process returns to step S1 to collect the operating status data of the thermal power unit at time t+1 for real-time regulation;

[0200] S32: Construct the control objective function at the current time t and constraints;

[0201] S33: Initialize and generate the position coordinates of U jackals, wherein the position coordinates of each jackal correspond to the speed control amount of the thermal power unit and the temperature control amount of the thermal power unit, wherein the position coordinates of the u-th jackal generated by initialization are:

[0202] ;

[0203] in:

[0204] represents the position coordinates of the u-th jackal generated by initialization, where Corresponding to the speed control amount of the thermal power unit, Corresponding to the temperature control amount of thermal power units, u ∈ [1,U] ;

[0205] The position coordinates of each jackal generated by initialization satisfy the following constraints:

[0206] i minutes 1 ≤ X 1 t + location u 0 (1) ≤ i max 1 ,u ∈ [1,U] ;

[0207] i minutes 2 ≤ X 2 t + location u 0 (2) ≤ i max 2 ,u ∈ [1,U] ;

[0208] S34: Set the current iteration number of the jackal position coordinates to d, and the maximum iteration number to Max, then the d-th iteration result of the u-th jackal position coordinates is , the initial value of d is 0;

[0209] S35: Calculate the escape energy factor of the prey after the dth iteration of the jackal's position coordinates:

[0210] ;

[0211] in:

[0212] represents the escape energy factor of the prey after the dth iteration of the jackal's position coordinates;

[0213] Indicates the preset maximum escape energy factor, Indicates the preset minimum escape energy factor;

[0214] S36: Iterate the jackal position coordinates, wherein the iteration formula of the u-th jackal position coordinates is:

[0215] ;

[0216] ;

[0217] ;

[0218] in:

[0219] represents the random step size, represents a normal distribution, represents the gamma function, represents the exponential adjustment coefficient, Set to 2;

[0220] Indicates that it follows a normal distribution A random number;

[0221] Indicates that it follows a normal distribution A random number;

[0222] It means that the position coordinates of the U jackals after the dth iteration are used as the input of the control objective function, so that the control objective function reaches the minimum position coordinate;

[0223] S37: Let d=d+1, return to step S35, iterate the position coordinates of U jackals until the maximum number of iterations is reached, and select the position coordinates of U jackals after the Max-th iteration as the input of the control objective function, and take the minimum position coordinate that satisfies the constraint condition and makes the control objective function reach the minimum as the primary frequency regulation control strategy of the thermal power unit .

[0224] S4: Adaptively and robustly optimize the primary frequency regulation control strategy of the thermal power unit, obtain the primary frequency regulation control strategy of the thermal power unit after adaptive robust optimization, and adjust and control the thermal power unit.

[0225] In the step S4, the primary frequency regulation control strategy of the thermal power unit is adaptively and robustly optimized, and the thermal power unit is adjusted and controlled, including:

[0226] The primary frequency regulation control strategy of the thermal power unit is adaptively and robustly optimized to obtain the primary frequency regulation control strategy of the thermal power unit after adaptive and robust optimization. The adaptive robust optimization process is:

[0227] S41: Obtain the primary frequency regulation control strategy of all thermal power units at the current time t. If the thermal power unit does not generate the primary frequency regulation control strategy of the thermal power unit at the current time t, set the primary frequency regulation control strategy of the thermal power unit at the current time t to [0,0] ;

[0228] S42: Calculate the primary frequency control strategy of thermal power units The robustness weight :

[0229] ;

[0230] in:

[0231] Q represents the set of primary frequency regulation control strategies of all thermal power units at the current time t. , Representing a collection A primary frequency regulation control strategy for any group of thermal power units;

[0232] S43: Primary frequency control strategy for thermal power units Robust optimization is performed, and the primary frequency regulation control strategy of the thermal power unit after robust optimization is ;

[0233] Primary frequency regulation control strategy of thermal power units after robust optimization Primary frequency control strategy for thermal power units The corresponding thermal power units are adjusted and controlled.

[0234] Embodiment 2:

[0235] like Figure 2 , is a functional module diagram of a large-disturbance adaptive adjustment control system for primary frequency modulation of a thermal power unit provided by an embodiment of the present invention, which can implement the large-disturbance adaptive adjustment control method for primary frequency modulation of a thermal power unit in Example 1.

[0236] The large disturbance adaptive adjustment control system 100 for primary frequency modulation of thermal power units of the present invention can be installed in an electronic device. According to the functions to be implemented, the large disturbance adaptive adjustment control system for primary frequency modulation of thermal power units can include a data acquisition module 101, a disturbance monitoring module 102 and an adaptive control device 103. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, which are stored in the memory of the electronic device.

[0237] The data acquisition module 101 is used to collect the operating status data of the thermal power unit in real time using sensors, and to perform denoising on the collected data to obtain the denoised operating status data of the thermal power unit;

[0238] A disturbance monitoring module 102 is used to monitor the frequency disturbance of the power grid based on the de-noised operating status data of the thermal power unit;

[0239] The adaptive control device 103 is used to construct an adaptive control model, solve the adaptive control model, obtain the primary frequency regulation control strategy of the thermal power unit, perform adaptive robust optimization on the primary frequency regulation control strategy of the thermal power unit, obtain the primary frequency regulation control strategy of the thermal power unit after adaptive robust optimization, and adjust and control the thermal power unit.

[0240] In detail, the modules in the large disturbance adaptive adjustment control system 100 of the primary frequency modulation of the thermal power unit in the embodiment of the present invention are used in the same manner as described above. Figure 1 The same technical means are used as the large disturbance adaptive adjustment control method for primary frequency modulation of thermal power units described in , and can produce the same technical effects, so they will not be repeated here.

[0241] Embodiment 3:

[0242] like Figure 3 , which is a schematic diagram of the structure of an electronic device for implementing a large disturbance adaptive adjustment control method for primary frequency modulation of a thermal power unit under extreme working conditions, provided by an embodiment of the present invention.

[0243] The electronic device 1 may include a processor 10 , a memory 11 , a communication interface 13 and a bus, and may also include a computer program stored in the memory 11 and executable on the processor 10 , such as a program 12 .

[0244] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 may not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the program 12, etc., but also be used to temporarily store data that has been output or is to be output.

[0245] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (a program 12 for realizing adaptive adjustment control of large disturbances of primary frequency modulation of thermal power units under extreme working conditions, etc.), and calls data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0246] The communication interface 13 may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices, and to achieve connection and communication between internal components of the electronic device.

[0247] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0248] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0249] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0250] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0251] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0252] It should be noted that the serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. And the terms "including", "comprising" or any other variants thereof in this article are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "including a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0253] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0254] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A large disturbance adaptive adjustment control method for primary frequency modulation of thermal power units under extreme working conditions, characterized in that: The method comprises: S1: using sensors to collect the operating status data of the thermal power unit in real time, where the operating status data of the thermal power unit includes the speed, temperature, pressure parameters of the thermal power unit and the grid frequency data, and performing denoising on the collected data to obtain the denoised operating status data of the thermal power unit; S2: Monitor the grid frequency disturbance based on the denoised thermal power unit operating status data, and build an adaptive control model, which uses the grid frequency disturbance monitoring results and the denoised thermal power unit operating status data as input variables, and uses the primary frequency regulation control strategy of the thermal power unit as the model solution result; The constructing of the adaptive control model comprises: Construct an adaptive control model, wherein the adaptive control model includes a control objective function and control constraints, the variables in the control objective function are the speed control amount and the temperature control amount of the thermal power unit, the control constraints are to make the speed and temperature of the thermal power unit after control within a preset control range, the function value of the control objective function represents the difference between the grid frequency after control and the standard grid frequency, the adaptive control model is solved to obtain the speed control amount and the temperature control amount of the thermal power unit that prevent the grid frequency deviation from further expanding, and the solved speed control amount and the temperature control amount of the thermal power unit are used as the primary frequency regulation control strategy of the thermal power unit; The control objective function in the adaptive control model is: in: F(θ t ) represents the control objective function in the adaptive control model, θ t represents the control objective function F(θ t ), represents the speed control value of the thermal power unit at the current time t, Indicates the temperature control value of the thermal power unit at the current time t; W t represents the control parameter at the current time t, fre std Indicates standard grid frequency; Indicates the difference between the grid frequency after regulation and the standard grid frequency at the current time t; Indicates that the selection makes The minimum w is obtained as output; The constraints in the adaptive control model are: in: Indicates the minimum value of the speed of the thermal power unit. Indicates the maximum speed of the thermal power unit; Indicates the minimum temperature of the thermal power unit. Indicates the maximum temperature of the thermal power unit; S3: Solve the adaptive control model to obtain the primary frequency regulation control strategy of the thermal power unit; The solution process of the adaptive control model is: S31: The adaptive control model receives the grid frequency disturbance monitoring result ε t As well as the denoised thermal power unit operating status data, if the grid frequency disturbance monitoring result ε t If it is higher than the preset threshold, it indicates that there is a grid frequency disturbance at the current time t, and the process goes to step S32; otherwise, the process returns to step S1 to collect the operating status data of the thermal power unit at time t+1 for real-time regulation; S32: Construct the control objective function F(θ t ) and constraints; S33: Initialize and generate the position coordinates of U jackals, wherein the position coordinates of each jackal correspond to the speed control amount of the thermal power unit and the temperature control amount of the thermal power unit, wherein the position coordinates of the u-th jackal generated by initialization are: in: represents the position coordinates of the u-th jackal generated by initialization, where Corresponding to the speed control amount of the thermal power unit, Corresponding to the temperature control value of the thermal power unit, u∈[1,U]; The position coordinates of each jackal generated by initialization satisfy the following constraints: S34: Set the current iteration number of the jackal position coordinates to d, and the maximum iteration number to Max, then the d-th iteration result of the u-th jackal position coordinates is The initial value of d is 0; S35: Calculate the escape energy factor of the prey after the dth iteration of the jackal's position coordinates: in: E d represents the escape energy factor of the prey after the dth iteration of the jackal's position coordinates; E max Indicates the preset maximum escape energy factor, E min Indicates the preset minimum escape energy factor; S36: Iterate the jackal position coordinates; S37: Let d=d+1, return to step S35, iterate the position coordinates of U jackals until the maximum number of iterations is reached, and select the position coordinates of U jackals after the Max-th iteration as the input of the control objective function, and take the minimum position coordinate that satisfies the constraint condition and makes the control objective function reach the minimum as the primary frequency regulation control strategy of the thermal power unit Iterate over the jackal position coordinates, including: The iterative formula for the position coordinates of the u-th jackal is: in: ρ represents the random step size, Norm(·) represents the normal distribution, Γ(·) represents the gamma function, β represents the exponential adjustment coefficient, and β is set to 2; ρ2 represents a random number that follows the normal distribution Norm(0,1); ρ1 means it follows a normal distribution A random number; It means that the position coordinates of the U jackals after the dth iteration are used as the input of the control objective function, so that the control objective function reaches the minimum position coordinate; S4: Adaptively and robustly optimize the primary frequency regulation control strategy of the thermal power unit, obtain the primary frequency regulation control strategy of the thermal power unit after adaptive robust optimization, and adjust and control the thermal power unit.

2. The large disturbance adaptive adjustment control method for primary frequency modulation of thermal power units under extreme working conditions as claimed in claim 1 is characterized in that: In step S1, sensors are used to collect the operating status data of the thermal power unit in real time, including: The sensors are used to collect the operating status data of the thermal power unit in real time, where the operating status data of the thermal power unit includes the speed, temperature, pressure parameters and grid frequency data of the thermal power unit. The operating status data of the thermal power unit collected at the current time t is: in: represents the state data of the operating state index of the i-th thermal power unit collected at the current time t, i∈[1,4], and the operating state indexes of the 1st to 4th thermal power units are the speed, temperature, pressure parameter index and grid frequency index of the thermal power unit respectively; x i (t) represents the index data of the thermal power unit under the operating status index of the i-th thermal power unit at time t; x i (tN) represents the index data of the thermal power unit under the operating status index of the i-th thermal power unit at time tN; wherein the time interval between adjacent moments is Δ; x i (tN),x i (t-N+1),...,x i (tn)...,x i (t-2),x i (t-1) indicates that compared with the index data x i (t) N sets of historical indicator data, n∈[1,N]; The data collected at the current time t is denoised to obtain the denoised operating status data of the thermal power unit.

3. The large disturbance adaptive adjustment control method for primary frequency modulation of thermal power units under extreme working conditions as claimed in claim 2 is characterized in that: The denoising process is performed on the data collected at the current time t to obtain the denoised operating status data of the thermal power unit, including: The data collected at the current time t is denoised to obtain the denoised operating status data of the thermal power unit, wherein the denoising process is as follows: S11: construct a denoising filter G(·); S12: De-noising the state data of the operating state indicators of different thermal power units using a de-noising filter, wherein the state data based on the de-noising filter G(·) The denoising formula is: in: Represents status data The denoising result, X i (tn) represents the indicator data x i The filtering result of (tn); f c represents the cutoff frequency of the denoising filter G(·), Represents status data The frequency of, L represents the order of the denoising filter G(·); S13: Construct the de-noised thermal power unit operation status data: in: Represents status data The denoising result.

4. The large disturbance adaptive adjustment control method for primary frequency modulation of a thermal power unit under extreme working conditions as claimed in claim 3 is characterized in that: In the step S2, the power grid frequency disturbance is monitored based on the de-noised thermal power unit operation status data, including: The grid frequency disturbance is monitored based on the de-noised thermal power unit operating status data, where the grid frequency disturbance monitoring process at the current time t is: S21: Obtaining the de-noised operating status data of the thermal power unit; S22: Calculate the abnormality of the operating state of the thermal power unit at the current time t: in: Indicates the abnormality of the operating status of the thermal power unit at the current time t; represents the similarity of the operating status of the thermal power unit under the jth thermal power unit operating status indicator at the current time t, j = 1, 2, 3; Indicates the de-noised thermal power unit operating status data The mean of the data; τ represents the hysteresis factor, and τ is set to 2; S23: Calculate and obtain the power grid frequency disturbance monitoring result at the current time t: in: ε t Indicates the power grid frequency disturbance monitoring result at the current time t; An adaptive control model is constructed, which takes the grid frequency disturbance monitoring results and the denoised thermal power unit operating status data as input variables, and takes the primary frequency regulation control strategy of the thermal power unit as the model solution result.

5. The large disturbance adaptive adjustment control method for primary frequency modulation of thermal power units under extreme working conditions as claimed in claim 1 is characterized in that: In the step S4, the primary frequency regulation control strategy of the thermal power unit is adaptively and robustly optimized to obtain the primary frequency regulation control strategy of the thermal power unit after adaptive and robust optimization, and the thermal power unit is adjusted and controlled, including: The primary frequency regulation control strategy of the thermal power unit is adaptively and robustly optimized to obtain the primary frequency regulation control strategy of the thermal power unit after adaptive and robust optimization. The adaptive robust optimization process is: S41: Obtain the primary frequency regulation control strategy of all thermal power units at the current time t. If the thermal power unit does not generate the primary frequency regulation control strategy at the current time t, set the primary frequency regulation control strategy of the thermal power unit at the current time t to [0,0]; S42: Calculate the primary frequency control strategy of thermal power units The robustness weight in: exp(·) represents an exponential function with a natural constant as the base; Q represents the set of primary frequency regulation control strategies of all thermal power units at the current time t, q∈Q, q represents any set of primary frequency regulation control strategies of thermal power units in the set Q; S43: Primary frequency control strategy for thermal power units Robust optimization is performed, and the primary frequency regulation control strategy of the thermal power unit after robust optimization is Primary frequency regulation control strategy of thermal power units after robust optimization Primary frequency control strategy for thermal power units The corresponding thermal power units are adjusted and controlled.

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