CN-122000925-A - Energy storage integrated anti-deception attack frequency control method for power network

CN122000925ACN 122000925 ACN122000925 ACN 122000925ACN-122000925-A

Abstract

The application relates to a frequency control method, a device, computer equipment, a computer readable storage medium and a computer program product for energy storage integration anti-deception attack facing to an electric power network, which can be used in the technical field of electric power. The method comprises the steps of obtaining system operation parameters of an electric power system comprising an energy storage unit, constructing a frequency control model according to the system operation parameters, constructing a spoofing attack model aiming at the frequency control model according to frequency driving type spoofing attack information, constructing a closed-loop control system model comprising the frequency control model and the spoofing attack model according to PI control information, performing stability analysis processing on the closed-loop control system model, determining constraint conditions enabling the closed-loop control system model to meet preset robust performance indexes, determining target PI controller gain information according to the constraint conditions, and performing frequency control on the electric power system according to the target PI controller gain information. The method can improve the frequency control stability of the power system.

Inventors

FU YI
LI SHIJIE
HU YUFENG
ZHA JING
WANG QI
LI WEIWEI
LIAN YIQING
YANG YIYUE

Assignees

中国南方电网有限责任公司

Dates

Publication Date: 20260508
Application Date: 20251226

Claims (10)

1. The utility model provides a frequency control method of energy storage integration anti-deception attack towards power network, which is characterized in that the method includes: Acquiring system operation parameters of an electric power system comprising an energy storage unit, and constructing a frequency control model comprising dynamic characteristic information of a generator set and dynamic characteristic information of the energy storage system according to the system operation parameters; constructing a spoofing attack model aiming at the frequency control model according to preset frequency driving type spoofing attack information, and constructing a closed-loop control system model comprising the frequency control model and the spoofing attack model according to preset PI control information; Performing stability analysis processing on the closed-loop control system model, and determining constraint conditions for enabling the closed-loop control system model to meet preset robust performance indexes; determining target PI controller gain information according to the constraint conditions; and controlling the frequency of the power system according to the target PI controller gain information.
2. The method of claim 1, wherein constructing a fraud attack model for the frequency control model based on preset frequency-driven fraud attack information includes: determining attack weight parameters according to the frequency driving type spoofing attack information; according to the attack weight parameters, carrying out attack disturbance processing on the frequency information in the frequency control model to obtain damaged frequency information; According to the attack weight parameters, carrying out attack disturbance processing on the regional control error signals in the frequency control model to obtain damaged regional control error signals; and constructing the spoofing attack model according to the damaged frequency information and the damaged area control error signal.
3. The method of claim 1, wherein the performing a stability analysis process on the closed loop control system model comprises: Constructing a game model according to the controller information and the attacker information; determining a target performance index according to the game model, wherein the target performance index is used for representing the inhibition capability of the controller on disturbance signals under the most unfavorable attack condition; and according to the target performance index, performing stability analysis processing on the closed-loop control system model.
4. The method of claim 1, wherein determining target PI controller gain information based on the constraint comprises: initializing a candidate gain parameter population within a preset gain parameter range; according to the constraint condition, carrying out adaptability recognition processing on each candidate gain parameter in the candidate gain parameter population to obtain a adaptability value of each candidate gain parameter; according to the fitness value of each candidate gain parameter, carrying out iterative updating processing on the candidate gain parameter population to obtain a target gain parameter; And determining the target PI controller gain information according to the target gain parameter.
5. The method of claim 1, wherein constructing a frequency control model including genset dynamic characteristic information and energy storage system dynamic characteristic information based on the system operating parameters comprises: Determining power balance information of the power system according to the system operation parameters; determining state space information according to the power balance information, wherein state variables in the state space information comprise frequency deviation, speed regulator valve position deviation, turbine mechanical power deviation and energy storage unit output power deviation; And constructing the frequency control model according to the state space information.
6. The method of any one of claims 1 to 5, wherein the closed loop control system model contains composite disturbance information; The method further comprises the steps of: external disturbance information is acquired, and attack disturbance information is determined according to the spoofing attack model; and carrying out fusion processing on the external disturbance information and the attack disturbance information to obtain the composite disturbance information.
7. An energy storage integrated anti-spoofing attack frequency control device oriented to an electric power network, which is characterized by comprising: The parameter acquisition module is used for acquiring system operation parameters of the power system comprising the energy storage unit, and constructing a frequency control model comprising dynamic characteristic information of the generator set and dynamic characteristic information of the energy storage system according to the system operation parameters; the model construction module is used for constructing a spoofing attack model aiming at the frequency control model according to preset frequency driving type spoofing attack information and constructing a closed-loop control system model comprising the frequency control model and the spoofing attack model according to preset PI control information; the model analysis module is used for carrying out stability analysis processing on the closed-loop control system model and determining constraint conditions for enabling the closed-loop control system model to meet preset robust performance indexes; the information determining module is used for determining target PI controller gain information according to the constraint conditions; and the system control module is used for controlling the frequency of the power system according to the target PI controller gain information.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

Description

Energy storage integrated anti-deception attack frequency control method for power network Technical Field The present application relates to the field of power technology, and in particular, to a power network-oriented energy storage integrated anti-fraud attack frequency control method, apparatus, computer device, computer readable storage medium, and computer program product. Background In the technical field of power system control, frequency control is a key link for guaranteeing safe and stable operation of a power grid, but along with the improvement of networking and intelligent degree, a power system faces increasingly serious network security threat. In the existing frequency control scheme, the design is mainly aimed at physical faults, and the defense capability for network spoofing attacks is lacked, so that the frequency control stability of the power system is low. Disclosure of Invention In view of the foregoing, it is desirable to provide a frequency control method, apparatus, computer device, computer readable storage medium, and computer program product for energy storage integration anti-fraud attack for an electric power network, which can improve the frequency control stability of the electric power system. In a first aspect, the application provides a power network-oriented energy storage integrated anti-spoofing attack frequency control method. The method comprises the following steps: Acquiring system operation parameters of an electric power system comprising an energy storage unit, and constructing a frequency control model comprising dynamic characteristic information of a generator set and dynamic characteristic information of the energy storage system according to the system operation parameters; constructing a spoofing attack model aiming at the frequency control model according to preset frequency driving type spoofing attack information, and constructing a closed-loop control system model comprising the frequency control model and the spoofing attack model according to preset PI control information; Performing stability analysis processing on the closed-loop control system model, and determining constraint conditions for enabling the closed-loop control system model to meet preset robust performance indexes; determining target PI controller gain information according to the constraint conditions; and controlling the frequency of the power system according to the target PI controller gain information. In one embodiment, the constructing a fraud attack model for the frequency control model according to preset frequency driving type fraud attack information includes: determining attack weight parameters according to the frequency driving type spoofing attack information; according to the attack weight parameters, carrying out attack disturbance processing on the frequency information in the frequency control model to obtain damaged frequency information; According to the attack weight parameters, carrying out attack disturbance processing on the regional control error signals in the frequency control model to obtain damaged regional control error signals; and constructing the spoofing attack model according to the damaged frequency information and the damaged area control error signal. In one embodiment, the performing a stability analysis process on the closed-loop control system model includes: Constructing a game model according to the controller information and the attacker information; determining a target performance index according to the game model, wherein the target performance index is used for representing the inhibition capability of the controller on disturbance signals under the most unfavorable attack condition; and according to the target performance index, performing stability analysis processing on the closed-loop control system model. In one embodiment, the determining the target PI controller gain information according to the constraint condition includes: initializing a candidate gain parameter population within a preset gain parameter range; according to the constraint condition, carrying out adaptability recognition processing on each candidate gain parameter in the candidate gain parameter population to obtain a adaptability value of each candidate gain parameter; according to the fitness value of each candidate gain parameter, carrying out iterative updating processing on the candidate gain parameter population to obtain a target gain parameter; And determining the target PI controller gain information according to the target gain parameter. In one embodiment, the constructing a frequency control model including generator set dynamic characteristic information and energy storage system dynamic characteristic information according to the system operation parameters includes: Determining power balance information of the power system according to the system operation parameters; determining state space information according to the power balance informatio