Data driving frequency control method and system of power system, medium, equipment and product

Abstract

The invention discloses a data driving frequency control method and system of a power system, a medium, equipment and a product in the technical field of power system frequency control. The method comprises the following steps: constructing a frequency control model containing unknown Markov jump parameters according to a relationship of system frequency variations of a power system in which an electric vehicle participates in frequency modulation; introducing a PID (Proportion Integration Differentiation) control strategy according to the frequency control model containing the unknown Markov jump parameter to obtain a discrete frequency control model under the PID control strategy; according to the discrete frequency control model under the PID control strategy, introducing parameters for reducing output dimensions, and establishing an equivalent reconstruction model of the power system; solving a static output feedback gain matrix based on a linear matrix inequality condition according to the electric power system equivalent reconstruction model and the obtained electric power system data set; and constructing a static output feedback controller according to the static output feedback gain matrix, and performing frequency control of the power system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system frequency control, and in particular to a data-driven frequency control method, system, medium, equipment and product of a power system. BACKGROUND

[0002] The power system frequency is an important indicator reflecting the operation of the smart grid, and its stability is the premise of ensuring the reliable operation of the power system. In the power system, load frequency control (LFC) is widely used to stabilize the frequency fluctuations. In recent years, electric vehicles, as a kind of flexible load, participate in the operation of the power grid, making the operation of the power system more stable, reliable, and effectively improving the power quality. At the same time, the parameters in the power system may change randomly due to the damage of electrical elements, external interference and other factors, and the Markov jump system is suitable for describing the random change phenomenon of such parameters. In view of the above, it is of great significance and theoretical value to study the secondary frequency control method of the power system containing Markov jump parameters constituted by electric vehicles participating in the power system.

[0003] With the increasing complexity of application scenarios, the mechanism model of the power system becomes complex and the uncertainty increases, making it difficult to model it with accurate parameters, which brings challenges to the application of model parameter-based control methods. Therefore, it is necessary to effectively utilize the collected offline or online data to design a data-driven control scheme to achieve frequency control of the power system in the case of unknown parameters of the controlled object. At the same time, high-dimensional input and output data will increase the difficulty of calculating the controller gain, so it is of research value to ensure the effectiveness of the data-driven frequency control method under the premise of reducing the state dimension of the reconstructed system and the calculation difficulty of the controller gain. SUMMARY

[0004] The purpose of the present application is to overcome the deficiencies in the prior art, and to provide a data-driven frequency control method, system, medium, equipment and product of a power system, which stabilizes the frequency fluctuations of the power system through a data-driven static output feedback control method, and reduces the high calculation difficulty of the controller gain of the existing data-driven control method by introducing a parameter that reduces the output dimension.

[0005] To solve the above technical problems, the present application is implemented by using the following technical solutions:

[0006] In a first aspect, the present application provides a data-driven frequency control method of a power system, comprising:

[0007] According to the relationship between the system frequency variation of the power system participating in frequency regulation by electric vehicles, a frequency control model containing unknown Markov jump parameters is constructed;

[0008] According to the frequency control model containing unknown Markov jump parameters, a PID control strategy is introduced to obtain a discrete frequency control model under the PID control strategy;

[0009] According to the discrete frequency control model under the PID control strategy, a parameter for reducing the output dimension is introduced to establish an equivalent reconstruction model of the power system;

[0010] According to the equivalent reconstruction model of the power system and the obtained power system data set, a static output feedback gain matrix is solved based on a linear matrix inequality condition;

[0011] According to the static output feedback gain matrix, a static output feedback controller is constructed to perform frequency control of the power system.

[0012] Optionally, the frequency control model of the power system containing unknown Markov jump parameters is constructed according to the relationship between the system frequency variation of the power system participating in frequency modulation and the electric vehicle, and the frequency control model of the power system containing unknown Markov jump parameters includes:

[0013] According to the relationship between the system frequency variation of the power system participating in frequency modulation and the electric vehicle, a power system frequency control differential equation is established;

[0014] According to the power system frequency control differential equation, a state variable and a control input variable are determined, and a state space equation of the power system is established;

[0015] According to the state space equation of the power system and the power system parameters, the frequency control model of the power system containing unknown Markov jump parameters is obtained;

[0016] The expression of the power system frequency control differential equation is:

[0017] ,

[0018] wherein, is a continuous time, , denotes a positive real number, denotes a differential value of the position of the generator speed valve at the moment t, denotes the position of the generator speed valve at the moment t, denotes a speed governor time constant, denotes a thermal turbine participation coefficient, denotes a control input signal at the moment t, denotes a speed governor droop characteristic, denotes a frequency deviation signal at the moment t; denotes derivative of the incremental change of the electric vehicle at the current time, denotes derivative of the incremental change of the electric vehicle at the current time, denotes the time constant of the electric vehicle; denotes derivative of the incremental change of the electric vehicle at the current time, denotes derivative of the incremental change of the electric vehicle at the current time, denotes the time constant of the electric vehicle, denotes the participation factor of the electric vehicle, denotes the gain of the electric vehicle, denotes the droop characteristic of the electric vehicle; denotes derivative of the incremental change of the electric vehicle at the current time, denotes the load damping factor, denotes the inertia constant;

[0019] The expression of the state variable is:

[0020] ,

[0021] wherein, denotes derivative of the incremental change of the electric vehicle at the current time, denotes derivative of the incremental change of the electric vehicle at the current time, , denotes the frequency deviation factor, denotes the matrix transpose;

[0022] The expression of the control input variable is:

[0023] ,

[0024] wherein, denotes derivative of the incremental change of the electric vehicle at the current time;

[0025] The expression of the state space equation of the power system is:

[0026] ,

[0027] wherein, denotes derivative of the incremental change of the electric vehicle at the current time, denotes the state parameter matrix, denotes the control input parameter matrix;

[0028] The expression of the frequency control model of the power system containing unknown Markov jump parameters is:

[0029] ,

[0030] wherein, denotes the state parameter matrix at time t, denotes the control input parameter matrix at time t, denotes the continuous time Markov process mode at time t.

[0031] Optionally, the PID control strategy is introduced according to the frequency control model containing unknown Markov jump parameters, and a discrete frequency control model under the PID control strategy is obtained, comprising:

[0032] selecting the PID control strategy according to the area control error

[0033] selecting an output variable according to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, and establishing a discrete frequency control model under the PID control strategy;

[0034] the expression of the PID control strategy is:

[0035] ,

[0036] wherein, denotes the PID control strategy, the proportional control gain, denotes the integral control gain, denotes the differential control gain, denotes the differential value of the area control error;

[0037] the expression of the output variable is:

[0038] ,

[0039] wherein, denotes the output variable at time t, denotes the output variable parameter matrix;

[0040] the expression of the discrete frequency control model under the PID control strategy is:

[0041] ,

[0042] wherein, denotes the discrete time, , denotes a positive integer, , denotes the discrete time length,​ denotes time state variable, denotes time state variable, , denotes time frequency deviation signal, denotes time position of the generator governing valve, denotes time turbine output power, denotes time incremental change of the electric vehicle, denotes time control input variable, denotes time output variable, denotes time discrete Markov process, denotes time state parameter matrix, denotes time control input parameter matrix, denotes time output variable parameter matrix, denotes a static output feedback gain matrix to be solved, , denotes time proportional control gain of the mode , denotes time integral control gain of the mode , denotes time differential control gain of the mode .

[0043] Optionally, according to the discrete frequency control model under the PID control strategy, a parameter for reducing the output dimension is introduced to establish an equivalent reconstruction model of the power system, including:

[0044] Selecting system parameters related to the mode of the power system, constructing the parameter for reducing the output dimension as , so that the matrix pair is observable, wherein is a non-zero row vector;

[0045] According to the parameter for reducing the output dimension , a one-dimensional output variable is constructed; wherein ;

[0046] According to the one-dimensional output variable and control input variables , construct new state variables ; wherein, , denote the control input variables at time denote the control input variables at time denote the one-dimensional output variables at time denote the one-dimensional output variables at time

[0047] According to the new state variables and the discrete frequency control model under the PID control strategy, an equivalent reconstruction model of a power system is established; an expression of the equivalent reconstruction model of the power system is:

[0048] ,

[0049] wherein, denote the new state variables at time denote the new state parameter matrix at time denote the new control input parameter matrix at time denote the new output variable parameter matrix at time

[0050] Optionally, according to the equivalent reconstruction model of the power system and the obtained power system data set, a static output feedback gain matrix is solved based on a linear matrix inequality condition, including:

[0051] According to the input data and the output data in the obtained power system data set, an input matrix , an output matrix and a state matrix are constructed;

[0052] wherein, denote the modes of Markov processes, , denote time, , denote positive integers, , denote the input data at time , , denote the output data at time , , , , denotes the state of a new variable at time , denotes the state of a new variable at time , denotes the current time, denotes the next time;

[0053] According to the input data matrix , the output data matrix and the new state data matrix , the suitable dimension matrix and the nonsingular matrix are calculated by linear matrix inequality;

[0054] According to the suitable dimension matrix and the nonsingular matrix , the static output feedback gain matrix is calculated, wherein, ;

[0055] The linear matrix inequality is as follows:

[0056]

[0057] wherein, denotes the transition probability, p denotes the mode of the Markov process at the current time, q denotes the mode of the Markov process at the next time, denotes the auxiliary solution matrix, , .

[0058] Optionally, the expression of the mode-related static output feedback controller is: .

[0059] In a second aspect, the present application provides a data-driven frequency control system of a power system, which is suitable for the data-driven frequency control method of the power system according to any one of the first aspect, and comprises:

[0060] A frequency modulation operation module is configured to: according to the relationship between the system frequency variation of the power system in which the electric vehicle participates in frequency modulation, construct a frequency control model containing unknown Markov jump parameters;

[0061] A PID feedback control module is configured to: according to the frequency control model containing unknown Markov jump parameters, introduce a PID control strategy, and obtain a discrete frequency control model under the PID control strategy;

[0062] The output data dimension reduction module is configured to introduce a parameter for reducing the output dimension according to the discrete frequency control model under the PID control strategy, and establish an equivalent reconstruction model of the power system.

[0063] The controller gain solving module is configured to solve a static output feedback gain matrix based on a linear matrix inequality condition according to the equivalent reconstruction model of the power system and the obtained power system data set.

[0064] The frequency control module is configured to construct a static output feedback controller according to the static output feedback gain matrix, and perform frequency control of the power system.

[0065] In a third aspect, the present application provides a computer readable storage medium having computer instructions stored thereon, the computer instructions being executed by a processor to implement the steps of the data-driven frequency control method of the power system according to any one of the first aspect.

[0066] In a fourth aspect, the present application provides a computer device, comprising:

[0067] a memory configured to store computer instructions;

[0068] a processor configured to execute the computer instructions to implement the steps of the data-driven frequency control method of the power system according to any one of the first aspect.

[0069] In a fifth aspect, the present application provides a computer program product comprising computer instructions, wherein the computer instructions are executed by a processor to implement the steps of the data-driven frequency control method of the power system according to any one of the first aspect.

[0070] Compared with the prior art, the present application has the following beneficial effects:

[0071] 1. The power system load frequency control system based on the Markov jump model is considered, so that the power system is closer to the actual situation.

[0072] 2. The mechanism model of the power system is complex and has increased uncertainty, which cannot be accurately modeled, so that the power system is more consistent with complex working conditions.

[0073] 3. In view of the high calculation difficulty of the controller gain of the existing data-driven control method, a parameter for reducing the output dimension is introduced to establish an equivalent reconstruction model of the power system based on input and one-dimensional output data containing unknown Markov jump parameters, so as to ensure the smooth operation of the power system while reducing the calculation complexity. BRIEF DESCRIPTION OF DRAWINGS

[0074] Figure 1A flow chart of a data-driven frequency control method of a power system according to an embodiment of the present application is provided.

[0075] Figure 2 A logic diagram of a frequency control of a power system in which electric vehicles participate in frequency modulation according to an embodiment of the present application is provided.

[0076] Figure 3 A state diagram of a modal jump of a system parameter according to an embodiment of the present application is provided.

[0077] Figure 4 A state response diagram under a data-driven modal correlation static output feedback controller according to an embodiment of the present application is provided.

[0078] Figure 5 A structure diagram of a data-driven frequency control system of a power system according to an embodiment of the present application is provided.

[0079] Figure 6 A structure diagram of a computer device according to an embodiment of the present application is provided. DETAILED DESCRIPTION

[0080] The technical solutions of the present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific features in the embodiments and the specific embodiments of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application. In the case of no conflict, the technical features in the embodiments and the specific embodiments can be combined with each other.

[0081] It should be noted that the term "and / or" in this paper is only a description of the association relationship between the associated objects, which means that there can be three kinds of relationships, for example, A and / or B, which can represent the existence of A alone, the existence of A and B together, and the existence of B alone. In addition, the character " / " in this paper generally represents a "or" relationship between the associated objects before and after it.

[0082] Embodiment one:

[0083] The embodiments of the present application disclose a data-driven frequency control method of a power system, referring to Figure 1 as shown, comprising:

[0084] S1, according to the relationship between the system frequency variation of the power system in which electric vehicles participate in frequency modulation, a frequency control model containing unknown Markov jump parameters is constructed;

[0085] S2, according to the frequency control model containing unknown Markov jump parameters, a PID control strategy is introduced to obtain a discrete frequency control model under the PID control strategy;

[0086] S3, based on the discrete frequency control model under the PID control strategy, introducing parameters that reduce the output dimension and establishing an equivalent reconstruction model of the power system;

[0087] S4, solving a static output feedback gain matrix based on the power system equivalent reconstruction model and the acquired power system data set and a linear matrix inequality condition;

[0088] S5. Construct a static output feedback controller according to the static output feedback gain matrix to perform frequency control of the power system.

[0089] In step S1, the electric vehicle participates in the frequency modulation of the power system specifically referring to Figure 2 The frequency control logic of the power system with electric vehicles participating in frequency regulation is shown. Figure 2 The demonstration shows a highly integrated control structure, covering the core parts such as controller, thermal power plant, electric vehicle, feedback control module, etc.; not only considers the traditional frequency regulation function, but also introduces electric vehicles to participate in system frequency regulation; first, the controller generates a control signal based on the area control error (ACE) , and then the control signal is transmitted to the thermal power plant and electric vehicle system. The system adjusts the regulation signal in real time through the feedback control loop and finally determines the frequency deviation signal .

[0090] The frequency control model of the power system containing unknown Markov jump parameters is constructed based on the relationship between the system frequency change amount of the power system in which electric vehicles participate in frequency regulation, including:

[0091] S1.1. Based on the relationship between the system frequency change of the power system in which electric vehicles participate in frequency regulation, establish the power system frequency control differential equation:

[0092] ,

[0093] in, is continuous time, , represents a positive real number, express The differential value of the position of the generator speed regulating valve at time , express The position of the generator speed regulating valve at all times, represents the speed regulator time constant, represents the thermal turbine participation factor, express Control the input signal at all times, Indicates the governor droop characteristic, express Moment frequency deviation signal; express a differential value of the incremental change of the electric vehicle at the moment, represents a turbine output power at the moment, represents a turbine time constant; represents a differential value of the incremental change of the electric vehicle at the moment, represents an incremental change of the electric vehicle at the moment, represents an electric vehicle time constant, represents an electric vehicle participation factor, represents an electric vehicle gain, represents an electric vehicle droop characteristic; represents a differential value of the frequency deviation signal at the moment, represents a load damping coefficient, represents an inertia constant;

[0094] S1.2, determining state variables and control input variables according to the power system frequency control differential equation, establishing a state space equation of the power system:

[0095] ,

[0096] wherein, represents a differential value of the state variable at the moment, represents a state variable at the moment, , represents a zone control error at the moment, , represents a frequency deviation factor, represents a transpose; represents a state parameter matrix, represents a control input parameter matrix, , represents a control input variable at the moment;

[0097] S1.3, obtaining a frequency control model of the power system containing unknown Markov jump parameters according to the state space equation of the power system and power system parameters:

[0098] ,

[0099] wherein, represents a state parameter matrix at the moment, represents a control input parameter matrix at the moment, represents continuous time Markov process modal.

[0100] In step S1.2, the expression of the state parameter matrix is:

[0101] , the expression of the control input parameter matrix is: .

[0102] In step S2, the PID control strategy is introduced according to the frequency control model containing unknown Markov jump parameters, to obtain a discrete frequency control model under the PID control strategy, comprising:

[0103] The PID control strategy is selected according to the area control error :

[0104] ,

[0105] wherein, represents the PID control strategy, proportional control gain, represents integral control gain, represents differential control gain, represents the differential value of the area control error;

[0106] According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, the output variable is selected:

[0107] ,

[0108] wherein, represents the output variable at time , represents the output variable parameter matrix, .

[0109] According to the output variable and the state space equation of the power system, a discrete frequency control model under the PID control strategy is established:

[0110] ,

[0111] wherein, represents discrete time, , represents a positive integer, , represents the length of discrete time, represents the state variable at time , represents instantaneous state variable, , represents instantaneous frequency deviation signal, represents instantaneous position of the generator governor valve, represents instantaneous turbine output power, represents instantaneous incremental change of the electric vehicle, represents instantaneous control input variable, represents instantaneous output variable, represents instantaneous discrete Markov process, represents instantaneous state parameter matrix, represents instantaneous control input parameter matrix, represents instantaneous output variable parameter matrix, represents a static output feedback gain matrix to be solved, , represents instantaneous proportional control gain of the mode , represents instantaneous integral control gain of the mode , represents instantaneous derivative control gain of the mode .

[0112] In step S3, the equivalent reconstruction model of the power system is established according to the discrete frequency control model under the PID control strategy, including:

[0113] selecting system parameters related to the mode of the power system to construct a parameter for reducing the output dimension , so that the matrix pair is an observable state, wherein is a non-zero row vector with one row and three columns;

[0114] constructing a one-dimensional output variable according to the parameter for reducing the output dimension ; wherein ;

[0115] constructing a new state variable according to the one-dimensional output variable and the control input variable . ;in, , express Control the input variables at all times, express Control the input variables at all times, express One-dimensional output variable at time, express One-dimensional output variable at time;

[0116] According to the new state variable The discrete frequency control model under the PID control strategy is used to establish an equivalent reconstruction model of the power system. The expression of the equivalent reconstruction model of the power system is:

[0117] ,

[0118] in, express The new state variables at time express The new state parameter matrix at time t, express The new control input parameter matrix at time t, express The new output variable parameter matrix at time t.

[0119] In step S4, according to the power system equivalent reconstruction model and the acquired power system data set, based on the linear matrix inequality condition, the static output feedback gain matrix is ​​solved, including:

[0120] Collect a set of power system parameters in which the modal The input and output data are:

[0121] ,

[0122] in, represents the mode of the Markov process, , Indicates time, , represents a positive integer, , express Input data at time, , express Output data at each moment;

[0123] According to the input data and output data , construct the input matrix , output matrix and state matrix :

[0124] ,

[0125] wherein, denotes the state of the new variable at the time instant , , denotes the current time instant, denotes the next time instant;

[0126] According to the input data matrix , output data matrix and new state data matrix , a suitable dimension matrix and a non-singular matrix are calculated by linear matrix inequality.

[0127] The linear matrix inequality is as follows:

[0128]

[0129] wherein, denotes the transition probability, p denotes the mode of the Markov process at the current time instant, q denotes the mode of the Markov process at the next time instant, denotes the auxiliary solution matrix, , ;

[0130] According to the dimension matrix and the non-singular matrix , a static output feedback gain matrix is calculated.

[0131] In step S5, according to the mode-related static output feedback gain matrix calculated in step S4, a controller is constructed as follows: The controller parameters are configured in the power system for frequency regulation.

[0132] In order to verify the effectiveness of the data-driven frequency control method of the power system proposed in the embodiment, a verification example is performed on the power system, and the specific parameter values of the power system are shown in Table 1.

[0133] Table 1 Parameters of the power system under two Markov jump modes:

[0134] Parameter Modality 1 0.01 0.1667 2.4 0.1 0.3 0.4167 1 1 0.425 0.6 0.4 Modality 2 0.0083 0.1667 2.4 0.08 0.2 0.4167 1 1 0.425 0.5 0.5

[0135] The parameters in Table 1 are configured in the power system for frequency regulation, and the initial state vector is randomly generated. The simulation results are as followsFigure 3 and 4 as shown in the formula (1) and the formula (2) respectively. Figure 3 The switching state of the system parameter between two modes is shown; Figure 4 The state response of the power system under the controller parameter is shown; analysis Figure 3 and 4 It can be obtained that the power system participating in frequency modulation by the electric vehicle keeps the frequency stable under the data-driven frequency control method; in general, the above simulation results further prove that the method proposed in the embodiment can keep the load frequency stable when the power system contains unknown Markov jump parameters, the parameter reducing the output dimension is introduced, and the equivalent reconstruction model of the power system containing unknown Markov jump parameters based on the input and one-dimensional output data is established, so that the smooth operation of the power system is ensured while the calculation complexity is reduced.

[0136] To sum up, the data-driven frequency control method of the power system provided by the embodiment, by constructing the frequency modulation operation model of the power system, simulates the frequency variation of the power system containing unknown Markov jump parameters when the electric vehicle participates in frequency modulation, and constructs the operation model of the PID control strategy and the data-driven static output feedback controller, couples the frequency modulation operation model of the power system and the operation model of the static output feedback controller, obtains the frequency control model, introduces the parameter reducing the output dimension, and establishes the equivalent reconstruction model of the power system containing unknown Markov jump parameters based on the input and one-dimensional output data, so that the smooth operation of the power system is ensured while the calculation complexity is reduced.

[0137] Embodiment two:

[0138] Based on the same inventive concept as embodiment one, the embodiment of the application discloses a data-driven frequency control system of a power system, which is suitable for the data-driven frequency control method of any power system in embodiment one, and refers to Figure 5 as shown, comprising:

[0139] The frequency modulation operation module is used for: according to the relationship between the system frequency variation of the power system participating in frequency modulation by the electric vehicle, constructing the frequency control model containing unknown Markov jump parameters;

[0140] The PID feedback control module is used for: according to the frequency control model containing unknown Markov jump parameters, introducing the PID control strategy, and obtaining the discrete frequency control model under the PID control strategy;

[0141] The output data dimension reduction module is used for: according to the discrete frequency control model under the PID control strategy, introducing the parameter reducing the output dimension, and establishing the equivalent reconstruction model of the power system;

[0142] a controller gain solving module configured to: solve a static output feedback gain matrix based on a linear matrix inequality condition according to the equivalent reconfiguration model of the power system and the obtained power system data set;

[0143] a frequency control module configured to: construct a static output feedback controller according to the static output feedback gain matrix, and perform frequency control of the power system.

[0144] The specific function implementation of each module is referred to the related content in the method of Embodiment One, and is not described herein.

[0145] Embodiment Three:

[0146] The embodiment provides a computer readable storage medium, which stores computer instructions, and the computer instructions are executed by a processor to implement the steps of the data-driven frequency control method of the power system according to any one of Embodiment One.

[0147] Embodiment Four:

[0148] The embodiment provides a computer device, which refers to the device shown in Figure 6 and includes:

[0149] a memory configured to store computer instructions;

[0150] a processor configured to execute the computer instructions to implement the steps of the data-driven frequency control method of the power system according to any one of Embodiment One.

[0151] Embodiment Five:

[0152] The embodiment provides a computer program product, which includes computer instructions, and the computer instructions are executed by a processor to implement the steps of the data-driven frequency control method of the power system according to any one of Embodiment One.

[0153] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) containing computer-usable program code.

[0154] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure One one or more flow or blocks Figure One one or more flow or blocks

[0155] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure One one or more flow or blocks Figure One one or more flow or blocks

[0156] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure One one or more flow or blocks Figure One one or more flow or blocks

[0157] The embodiments of the present application described above are merely intended to illustrate the present application, but not to limit the present application. The skilled in the art can make many modifications and improvements without departing from the spirit and scope of the present application, which should be protected as long as they fall within the scope of the present application.

Claims

1. A data-driven frequency control method for power systems, characterized by, The method comprises the following steps: According to the relationship between the system frequency variation of the power system participating in frequency modulation by electric vehicles, a frequency control model containing unknown Markov jump parameters is constructed; According to the frequency control model containing unknown Markov jump parameters, a PID control strategy is introduced to obtain a discrete frequency control model under the PID control strategy; According to the discrete frequency control model under the PID control strategy, a parameter for reducing the output dimension is introduced to establish an equivalent reconstruction model of the power system; According to the equivalent reconstruction model of the power system and the obtained power system data set, a static output feedback gain matrix is solved based on a linear matrix inequality condition; According to the static output feedback gain matrix, a static output feedback controller is constructed to control the frequency of the power system.

2. The data-driven frequency control method of a power system according to claim 1, wherein, The method comprises the following steps: According to the relationship between the system frequency variation of the power system participating in frequency modulation by electric vehicles, a frequency control model containing unknown Markov jump parameters is constructed; According to the relationship between the system frequency variation of the power system participating in frequency modulation by electric vehicles, a frequency control model containing unknown Markov jump parameters is constructed; The expression of the power system frequency control differential equation is: The expression of the state variable is: ， wherein is a continuous time, , is a positive real number, is a is a differential value of the position of the generator governor valve at the time t, is a is a position of the generator governor valve at the time t, is a governor time constant, is a thermal turbine participation factor, is a is a control input signal at the time t, is a governor droop characteristic, is a is a frequency deviation signal at the time t; is a is a differential value of the turbine output power at the time t, is a is a turbine output power at the time t, is a turbine time constant; is a is a differential value of the incremental change of the electric vehicle at the time t, is a is an incremental change of the electric vehicle at the time t, is an electric vehicle time constant, is an electric vehicle participation factor, is an electric vehicle gain, is an electric vehicle droop characteristic; is a is a differential value of the frequency deviation signal at the time t, is a load damping factor, is an inertia constant; The expression of the control input variable is: ， wherein denotes time state variable, denotes time zone control error, , denotes frequency deviation factor, denotes matrix transpose; The expression of the state space equation of the power system is: ， wherein indicates time control input variable The expression of the frequency control model of the power system containing unknown Markov jump parameters is: ， wherein denotes the differential value of the state variable at the time instant denotes the state parameter matrix, denotes the control input parameter matrix; The method comprises the following steps: ， wherein, denotes the time state parameter matrix, denotes the time control input parameter matrix, denotes the continuous time Markov process mode.

3. The data-driven frequency control method of a power system according to claim 2, wherein, According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; According to the region control error PID control strategy is selected; The expression of the PID control strategy is: The expression of the output variable is: ， wherein, denotes a PID control strategy, proportional control gain, denotes an integral control gain, denotes a derivative control gain, denotes a differential value of the zone control error; The expression of the discrete frequency control model under the PID control strategy is: ， wherein represents the time instant output variable, represents the output variable parameter matrix; The method comprises the following steps: ， wherein denotes a discrete time, , denotes a positive integer, , denotes a discrete time length, denotes the state variable at time instant denotes the state variable at time instant , denotes the frequency deviation signal at time instant denotes the position of the generator governing valve at time instant denotes the turbine output power at time instant denotes the incremental change of the electric vehicle at time instant denotes the control input variable at time instant denotes the output variable at time instant denotes the discrete Markov process at time instant denotes the state parameter matrix at time instant denotes the control input parameter matrix at time instant denotes the output variable parameter matrix at time instant denotes the static output feedback gain matrix to be solved, , denotes the proportional control gain of the mode at time instant denotes the integral control gain of the mode at time instant denotes the derivative control gain of the mode at time instant 4. The data-driven frequency control method of a power system according to claim 3, wherein, According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The system parameters related to the power system modal are selected, and the parameters for reducing the output dimension are constructed as , so that the matrix pair is observable, where is a non-zero row vector; According to the parameter of reducing the output dimension , a one-dimensional output variable is constructed ; wherein ; According to the one-dimensional output variable and the control input variable , a new state variable is constructed; wherein , denotes the control input variable at the time instant , denotes the control input variable at the time instant , denotes the one-dimensional output variable at the time instant , denotes the one-dimensional output variable at the time instant ; According to the new state variable And the discrete frequency control model under the PID control strategy, an equivalent reconstruction model of the power system is established; the expression of the equivalent reconstruction model of the power system is: ， wherein denotes a new state variable at the time instant denotes a new state parameter matrix at the time instant denotes a new control input parameter matrix at the time instant denotes a new output variable parameter matrix at the time instant 5. The data-driven frequency control method of a power system according to claim 4, wherein, The expression of the PID control strategy is: According to the input data in the acquired power system dataset and the output data , an input matrix , an output matrix and a state matrix are constructed; in, represents the mode of the Markov process, , Indicates time, , represents a positive integer, , express Input data at time, , express Output data at each moment, , , , Indicates New variables at the moment status, , Indicates the current moment, Indicates the next moment; According to the input data matrix , output data matrix and new state data matrix , a suitable dimension matrix and a non-singular matrix are calculated by linear matrix inequality. According to the suitable dimension matrix and the non-singular matrix , a static output feedback gain matrix is calculated, wherein ; The expression of the output variable is: wherein, denotes the transition probability, p denotes the mode of the Markov process at the current time instant, q denotes the mode of the Markov process at the next time instant, denotes the auxiliary solution matrix, , .

6. The data-driven frequency control method of a power system according to claim 1, wherein, The expression of the modal dependent static output feedback controller is: .

7. A data-driven frequency control system for an electric power system, characterized by The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to the PID control strategy and the frequency control model of the power system containing unknown Markov jump parameters, an output variable is selected to establish a discrete frequency control model under the PID control strategy; The expression of the PID control strategy is: The expression of the output variable is: The expression of the discrete frequency control model under the PID control strategy is: The method comprises the following steps: According to An output data dimension reduction module is configured to introduce a parameter for reducing output dimension according to a discrete frequency control model under the PID control strategy, and establish an equivalent reconstruction model of the power system; A controller gain solving module is configured to solve a static output feedback gain matrix based on a linear matrix inequality condition according to the equivalent reconstruction model of the power system and the obtained power system data set; A frequency control module is configured to construct a static output feedback controller according to the static output feedback gain matrix, and perform frequency control of the power system.

8. A computer readable storage medium having stored thereon computer instructions, wherein, The computer instructions, when executed by the processor, implement the steps of the data-driven frequency control method of the power system according to any one of claims 1-6.

9. A computer device, comprising: Comprise: A memory for storing computer instructions; A processor for executing the computer instructions to implement the steps of the data-driven frequency control method of the power system according to any one of claims 1-6.

10. A computer program product comprising computer instructions, characterized in that, The computer instructions, when executed by the processor, implement the steps of the data-driven frequency control method of the power system according to any one of claims 1-6.

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