CN-122000892-A - Heterogeneous power system fault diagnosis method, device, medium and computer equipment based on polygonal interaction

CN122000892ACN 122000892 ACN122000892 ACN 122000892ACN-122000892-A

Abstract

The application discloses a heterogeneous power system fault diagnosis method, device, medium and computer equipment based on polygonal interaction. The method comprises the steps of establishing a state space model of a heterogeneous multi-subsystem of a distributed power system, designing an observer for estimating distributed states and faults based on an unknown input method, constructing a dynamic equation for estimating system states and fault signals simultaneously, defining a local state estimation error vector and a fault estimation error vector, deriving a global error system model based on the dynamic equation and the state space model of the observer, carrying out stability analysis on the global error system model based on Lyapunov stability theory, converting stability conditions into an inequality equation set of a linear matrix to obtain matrix parameters of the observer, configuring the observer through the matrix parameters, and outputting the estimation of the system states and the fault signals in real time through the observer to complete fault diagnosis. The method can improve the accuracy of fault diagnosis of the heterogeneous power system.

Inventors

MA XINTONG
ZHANG QIANG
CHENG JIFENG
YUAN PENG
HU SHUBO
XIE BING
GE YANGYANG
MU YUNFEI
HU XUGUANG
DING ZHENG
ZHI YUANQING
LI PING

Assignees

国网辽宁省电力有限公司电力科学研究院
东北大学

Dates

Publication Date: 20260508
Application Date: 20251204

Claims (10)

1. A heterogeneous power system fault diagnosis method based on multilateral interaction, the method comprising: Establishing a state space model of heterogeneous multi-subsystem of a distributed power system, wherein the state space model is used for describing line dynamic characteristics, fault dynamic characteristics and coupling interconnection characteristics of all subsystems; Designing an observer based on the distributed state and fault estimation of an unknown input method for each subsystem, wherein the observer constructs a dynamic equation for simultaneously estimating the state of the system and the fault signal by introducing derivative information of an output signal and fusing state estimation values of adjacent subsystems; Defining a local state estimation error vector and a fault estimation error vector of each subsystem, and deriving a global error system model based on a dynamic equation of the observer and the state space model; performing stability analysis on the global error system model based on a Lyapunov stability theory to obtain a matrix inequality condition for enabling the global error system model to be asymptotically stable; converting the matrix inequality condition into an inequality equation set of a linear matrix, and obtaining matrix parameters of the observer by solving the inequality equation set of the linear matrix; And configuring the observer through matrix parameters of the observer, and completing fault diagnosis of the distributed power system through estimation of system states and fault signals output by the observer in real time during operation.
2. The method of claim 1, wherein the distributed power system comprises a plurality of heterogeneous interconnected subsystems having different physical structures and dynamic characteristics, and wherein the building a state space model of the heterogeneous plurality of subsystems of the distributed power system comprises: Establishing state space equations of the subsystems to describe voltage dynamics of filter inductance current and a common connection point of the subsystems, coupling relations among the filter inductance current and line current dynamics and the subsystems, and modeling system faults as unknown input items of the state space equations; And coupling state space equations of the subsystems to establish a state space model comprising line dynamic characteristics, fault dynamic characteristics and coupling interconnection characteristics.
3. The method of claim 1, wherein the observer's dynamic equation for any subsystem is as follows: Wherein, the Is subsystem Is used to determine the state of the observer of the system, Is subsystem System state of (2) Is used for the estimation of the (c), Is subsystem System failure of (a) Is used for the estimation of the (c), Is subsystem Is provided with a plurality of outputs which are measured, Is subsystem Is provided with a control input for the control of the (c), Representation of System and adjacent The coupling relationship between the systems is such that, Is an adjacent subsystem System state of (2) Is used for the estimation of the (c), Is subsystem Is known in the state space equation of (c), Is the first Subsystem Is defined as , Is the gain matrix of the observer to be solved.
4. The method of claim 1, wherein said defining a local state estimation error vector and a fault estimation error vector for each of said subsystems and deriving a global error system model based on said observer's dynamic equations and said state space model comprises: Defining a local state estimation error vector of each subsystem, and deriving a local state error dynamic equation of each subsystem based on the state space model and the observer dynamic equation; selecting a group of matrix parameters for a gain matrix of a dynamic equation of the observer, and simplifying the local state error dynamic equation based on the selected matrix parameters; Defining a fault estimation error vector for each of the subsystems and expressing the fault estimation error vector as a linear combination of the local state estimation error vectors based on a dynamic equation of the observer; and integrating the simplified local state error dynamic equation and the expressed fault estimation error vector of each subsystem to construct the global error system model.
5. The method according to claim 1, wherein the performing stability analysis on the global error system model based on lyapunov stability theory to obtain a matrix inequality condition for asymptotically stabilizing the global error system model includes: Performing regional pole allocation on the global error system model to enable the characteristic value of the global error system model to fall into a preset stable region; calculating the derivative of the global error system model along the system track through a quadratic Lyapunov function; And setting the derivative of the global error system model along the system track as a negative number so as to deduce a matrix inequality condition for ensuring the asymptotic stability of the global error system model.
6. The method of claim 1, wherein said converting the matrix inequality condition into a system of inequality equations for a linear matrix and deriving the matrix parameters for the observer by solving the system of inequality equations for the linear matrix comprises: Defining intermediate variables, and performing variable substitution on nonlinear product terms in dynamic equations of the observer to convert the matrix inequality condition into an inequality equation set of a linear matrix related to the intermediate variables; solving an inequality equation set of the linear matrix to obtain the value of the intermediate variable; And based on the values of the intermediate variables, reversely solving matrix parameters of all gain matrices of the observer.
7. The method of claim 1, wherein configuring the observer through matrix parameters of the observer and performing fault diagnosis of the distributed power system through estimation of system status and fault signals output by the observer in real time at run-time comprises: Performing parameter configuration on the observer of each subsystem based on matrix parameters of the observer; In the running process of the distributed power system, an observer of each subsystem carries out real-time operation based on the locally measured output signal, the derivative of the output signal, the control input and the state estimation value from the adjacent subsystem, and synchronously outputs the state estimation value and the fault estimation value of the subsystem; And taking the fault estimation value as a quantitative diagnosis result of the subsystem actuator fault so as to realize fault diagnosis of the distributed power system.
8. A heterogeneous power system fault diagnosis device based on multilateral interaction, the device comprising: The system comprises a space model establishing module, a state space model generating module and a coupling and interconnection module, wherein the space model establishing module is used for establishing a state space model of heterogeneous multi-subsystem of a distributed power system, and the state space model is used for describing line dynamic characteristics, fault dynamic characteristics and coupling and interconnection characteristics of each subsystem; The observer design module is used for designing an observer based on the distributed state and fault estimation of an unknown input method for each subsystem, wherein the observer builds a dynamic equation for simultaneously estimating the state of the system and the fault signal by introducing derivative information of an output signal and fusing state estimation values of adjacent subsystems; The error model building module is used for defining a local state estimation error vector and a fault estimation error vector of each subsystem and deducing a global error system model based on a dynamic equation of the observer and the state space model; The stability analysis module is used for carrying out stability analysis on the global error system model based on a Lyapunov stability theory to obtain a matrix inequality condition for enabling the global error system model to be asymptotically stable; The matrix parameter solving module is used for converting the matrix inequality condition into an inequality equation set of a linear matrix and obtaining the matrix parameters of the observer by solving the inequality equation set of the linear matrix; And the system fault diagnosis module is used for configuring the observer through matrix parameters of the observer, and completing fault diagnosis of the distributed power system through estimation of system states and fault signals output by the observer in real time during operation.
9. A storage medium having stored thereon a computer program, which when executed by a processor, implements the method of any of claims 1 to 7.
10. A computer device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, characterized in that the processor implements the method of any one of claims 1 to 7 when executing the computer program.

Description

Heterogeneous power system fault diagnosis method, device, medium and computer equipment based on polygonal interaction Technical Field The application relates to the technical field of power system state monitoring and fault diagnosis, in particular to a heterogeneous power system fault diagnosis method, device, medium and computer equipment based on polygonal interaction. Background Along with the large-scale access of new energy power generation and distributed power sources, the power system structure gradually evolves from the traditional centralized and isomorphic form to the distributed, isomerized and networked directions. The nodes in the system are difficult to describe by using a unified mathematical model due to the differences among the equipment types, the control strategies and the dynamic characteristics. This structural change presents new challenges to traditional centralized state estimation, fault diagnosis and control methods, especially when networking faults occur in the system, the observability and reliability of the system are significantly reduced. At present, state estimation and fault diagnosis of a power system mainly depend on a centralized processing mode, and state reconstruction is performed based on global measurement data and a unified parameter model. However, when a system has problems such as disconnection of lines, communication abnormality, or networking of sensor failure, the observability of the centralized method is drastically reduced. In order to cope with the problem, a distributed state estimation method based on polygonal information interaction appears in recent years, but most of the method is still established on the ideal isomorphic assumption that the subsystems are identical in structure, so that the dynamic characteristics of a heterogeneous power system are difficult to adapt to actual existence. In addition, the existing methods often impose strong constraints on fault dynamics, along with complex mathematical conditions, resulting in high computational complexity and insufficient diagnostic capabilities for time-varying faults. Disclosure of Invention In view of the above, the embodiment of the application provides a heterogeneous power system fault diagnosis method, a device, a medium and computer equipment based on polygonal interaction, which mainly aim to solve the technical problems that the existing method is difficult to adapt to the dynamic characteristics of a heterogeneous power system, has high calculation complexity and has insufficient diagnosis capability on time-varying faults. According to one aspect of the present application, there is provided a heterogeneous power system fault diagnosis method based on multilateral interaction, the method comprising: Establishing a state space model of heterogeneous multi-subsystem of a distributed power system, wherein the state space model is used for describing line dynamic characteristics, fault dynamic characteristics and coupling interconnection characteristics of all subsystems; Designing an observer based on the distributed state and fault estimation of an unknown input method for each subsystem, wherein the observer constructs a dynamic equation for simultaneously estimating the state of the system and the fault signal by introducing derivative information of an output signal and fusing state estimation values of adjacent subsystems; Defining a local state estimation error vector and a fault estimation error vector of each subsystem, and deriving a global error system model based on a dynamic equation of the observer and the state space model; performing stability analysis on the global error system model based on a Lyapunov stability theory to obtain a matrix inequality condition for enabling the global error system model to be asymptotically stable; converting the matrix inequality condition into an inequality equation set of a linear matrix, and obtaining matrix parameters of the observer by solving the inequality equation set of the linear matrix; And configuring the observer through matrix parameters of the observer, and completing fault diagnosis of the distributed power system through estimation of system states and fault signals output by the observer in real time during operation. According to another aspect of the present application, there is provided a heterogeneous power system fault diagnosis apparatus based on multilateral interactions, the apparatus comprising: The system comprises a space model establishing module, a state space model generating module and a coupling and interconnection module, wherein the space model establishing module is used for establishing a state space model of heterogeneous multi-subsystem of a distributed power system, and the state space model is used for describing line dynamic characteristics, fault dynamic characteristics and coupling and interconnection characteristics of each subsystem; The observer design module is used for designing an ob