CN-122000947-A - Power market demand response management triggering privacy protection method based on aggregated games

CN122000947ACN 122000947 ACN122000947 ACN 122000947ACN-122000947-A

Abstract

The invention discloses an electric power market demand response management triggering privacy protection method based on an aggregation game, and belongs to the technical field of electric power market demand management; the method comprises the steps of obtaining the real-time state of the generator by utilizing a state space equation, constructing an aggregate game model of the multi-turbine generator to optimize the profit of the generator, constructing a continuous time random noise generation model, transmitting the estimation result of the added aggregate function and a noise estimation signal to other designated generators, determining the optimized output strategy of the generator, constructing the state space expression of the turbine generator, and driving the generator to output power according to a preset strategy. The invention introduces privacy protection triggering dynamic average consistent control, time-varying Nash balance point search and model prediction control, and the total electric power output by the generator set in a dynamic environment meets the market power demand, thereby realizing adjustment strategy to maximize the income of the set, saving communication resources and protecting the privacy information of the generator by the power value transmitted in a random noise interference network.

Inventors

YANG YANG
YU XINGHAI
LIU JIANJUN
WU YIZHOU
ZHANG TENGFEI
ZHANG YICHI
LI RUI

Assignees

南京邮电大学

Dates

Publication Date: 20260508
Application Date: 20260129

Claims (9)

1. The power market demand response management triggering privacy protection method based on the aggregated game is characterized by comprising the following steps of: Step S1, constructing a dynamic system model of a turbine generator in continuous time, determining a state space equation of power output of the turbine generator, and obtaining a real-time state of the generator; s2, constructing an aggregate game model of a multi-turbine generator to optimize generator profit, and utilizing an aggregate function estimation model to assist in solving; s3, constructing a continuous time random noise generation model, superposing the output of the continuous time random noise generation model into an aggregation function estimation result to realize privacy protection, and superposing noise to generate a noise estimation signal; S4, introducing an event triggering mechanism to avoid continuous transmission, and transmitting the noise added aggregation function estimation result and the noise estimation signal to other specified generators; S5, constructing a noise estimation model, and estimating original noise according to a noise estimation signal to obtain the input of an aggregation function estimation model; S6, constructing a time-varying Nash balance point search model, and determining an optimized output strategy of the generator; And S7, constructing a state space expression of the turbine generator, and generating a power control input to drive the generator to output power according to a preset strategy.
2. The method for triggering privacy protection based on the power market demand response management of the aggregated game according to claim 1, wherein the step S1 is characterized in that a turbo generator continuous time dynamic system model is constructed, specifically: on a communication network without directional communication, considering N turbine generators, the kinetic model of the ith turbine generator is as follows: ; Wherein, the Is the output power of the i-th generator system, Is the opening degree of a steam valve of the ith generator, Is the relative speed of the i-th generator, The time constant of the ith mechanical turbine, Is the time constant of the speed regulator of the ith machine, Is the turbine gain of the ith machine, Is the tuning constant of the ith machine, Is the speed of the synchronous machine, and the speed of the synchronous machine, Is the constant of inertia which is the constant of the inertia, Is the damping constant per unit of the mass, Is the power control input of the i-th generator.
3. The method for triggering privacy protection based on the power market demand response management of the aggregate game according to claim 1, wherein the step S2 is to construct an aggregate game model of a plurality of turbo generators, specifically: On a communication network without directional communication, considering that N turbine generators run in a profit maximization mode, defining an aggregate game model as follows: ; The constraint conditions are as follows: ; Wherein, the As a function of the power generation cost of the ith generator, The representation is a coefficient of cost and, ; Is an aggregation function for aggregating games; The electricity price is represented by the number of electricity, Indicating the extent to which the local energy price is affected by the total output power; is the total power demand in the market.
4. The method for triggering privacy protection based on power market demand response management of aggregated games according to claim 3, wherein in the step S2, solution is assisted by using an aggregate function estimation model, and the aggregate function estimation model is as follows: ; Wherein, the Is the aggregation function of generator i to market Is used to determine the local estimate of (a), Is that For neighbors from it Is the aggregate function of (2) Is used for the estimation of (a), Is scalar and meets , , , The aggregate function estimation model relies only on neighbor information.
5. The method for triggering privacy protection based on power market demand response management of aggregated games as set forth in claim 1, wherein in the step S3, a continuous time random noise generation model is constructed, the output of the continuous time random noise generation model is superimposed into an aggregated function estimation result to realize privacy protection, and a noise estimation signal is generated by superimposing noise, specifically: The continuous time random noise generation model is as follows: ; Wherein, the Is a one-dimensional standard Brownian motion in a complete probability space; And Representing a specified function; representing a constant; representing noise signals which are injected into the privacy information to protect the privacy information from being intercepted for the output of the random noise generation model; Will be The method is added to the aggregation function estimation result, so that the real information cannot be stolen in the transmission in an open network, and the noise estimation signal is obtained by adding noise to the real information, wherein the expression is as follows: 。
6. The method for triggering privacy protection based on power market demand response management of aggregated games according to claim 1, wherein an event triggering mechanism is introduced in step S4 to avoid continuous transmission, and the noisy aggregate function estimation result is transmitted to other designated generators together with a noise estimation signal, specifically: Determining an event triggering mechanism of an ith generator, wherein the expression is as follows: ; Wherein, the Is a trigger function that is used to trigger the device, And Is the measurement error of the light source and the light source, , , Is a constant; for the kth trigger instant of generator i, generator i will sequence of information only when triggered And the power is sent to the appointed generator j, so that continuous communication is avoided, and communication resources are saved.
7. The method for triggering privacy protection based on power market demand response management of aggregated games as claimed in claim 1, wherein in the step S5, a noise estimation model is constructed, and original noise is estimated according to noise estimation signals, so as to obtain the input of an aggregated function estimation model, specifically: Determining a random noise estimation model of a j-th generator, wherein the expression is as follows: ; Wherein, the And Representing noise of generator j to its neighbor i, respectively And Is used for the estimation of (a), For a continuously differentiable bounded time-varying gain, Meets Lipschitz condition , ; The generator j subtracts the estimated noise from the noisy aggregate function estimate from neighbor i to obtain an aggregate function estimate for i: ; Wherein, the Is the input to the aggregate function estimation model for j.
8. The method for triggering privacy protection based on the power market demand response management of the aggregated game according to claim 1, wherein the step S6 is characterized in that a time variant Nash balance point search model is built, and an optimal output strategy of the generator is determined, specifically: the time-varying Nash equilibrium point search model of the ith turbine generator is: ; Wherein, the , ; Is the control gain, satisfies ; Is a parameter and , Is a parameter satisfying ; And Is a constant, a set Representing a set of neighbors of i, with which i exchanges information.
9. The method for triggering privacy protection based on the power market demand response management of the aggregated game according to claim 1, wherein the step S7 is characterized in that a state space expression of a turbo generator is constructed, specifically: the state space of the ith turbine generator is expressed as: ; Wherein, the , , And ; Recording device Is a power control input sequence Is an output sequence for the ith generator output power Reaching a time-varying Nash equilibrium point Power control input The method comprises the following steps: ; Wherein, the , Is a diagonal matrix, diagonal elements are predetermined weight parameters, Is a sequence of discrete time references at time k, And Is a matrix, which is in the specific form: , 。

Description

Power market demand response management triggering privacy protection method based on aggregated games Technical Field The invention belongs to the technical field of power market demand management, and particularly relates to an aggregation game-based power market demand response management triggering privacy protection method. Background With the development of smart grids and energy internet, power market demand response management becomes an important means for realizing supply-demand balance and improving system stability and economy. In recent years, the aggregated game shows strong modeling capability in the field of demand response management, and can effectively characterize decision behaviors of a large number of participants in the electric power market, such as electric power companies, end users and the like, in a competitive environment. Participants in the market make optimal decisions meeting system constraints through a game model and acquire maximum benefits. Therefore, the demand response management research based on the aggregated games provides an economic and effective platform for the development of the electric power market, and has great significance. In the turbine generator payment function model, the profit obtained by the generation of electricity is related to the sum of all participant decisions. How the local turbo-generator obtains the decision sum in a completely distributed manner is a key point to solving the problem of aggregated gaming. Conventional decision sum estimation methods are often designed based on a fixed environment, i.e. the decision sum remains unchanged, which results in the conventional methods not being applicable in a dynamic environment. Because the strategy of the turbine generator in a dynamic environment needs to be adjusted according to the change of the environment, the decision sum is changed. The continuous time moving average consensus algorithm can effectively estimate the average of the dynamic decisions. By introducing a continuous time dynamic average consistent algorithm, the defect that the traditional method is not applicable in a dynamic environment is effectively overcome. Continuous time moving average consistent algorithms generally rely on multiple objects exchanging information with each other in an open network, and how to avoid theft of private information and continuous information exchange is a key to safely and efficiently performing tasks. Event triggering and privacy protection mechanisms are powerful tools to address these issues. The event triggering mechanism can avoid continuous information transmission and save communication resources. The privacy protection mechanism based on random noise injection can interfere a network eavesdropper to steal actual privacy information, and safety accidents and economic losses caused by privacy disclosure are avoided. Therefore, how to solve the problem of demand response management through dynamic aggregation gaming, and achieve privacy protection and triggering communication under the constraint of meeting the market power demand are technical problems to be solved by the invention. Disclosure of Invention The invention aims to provide an electric power market demand response management triggering privacy protection method based on an aggregated game so as to solve the problems in the background technology. The invention aims to realize the method for triggering privacy protection based on the power market demand response management of the aggregated game, which is characterized by comprising the following steps: Step S1, constructing a dynamic system model of a turbine generator in continuous time, determining a state space equation of power output of the turbine generator, and obtaining a real-time state of the generator; s2, constructing an aggregate game model of a multi-turbine generator to optimize generator profit, and utilizing an aggregate function estimation model to assist in solving; s3, constructing a continuous time random noise generation model, superposing the output of the continuous time random noise generation model into an aggregation function estimation result to realize privacy protection, and superposing noise to generate a noise estimation signal; S4, introducing an event triggering mechanism to avoid continuous transmission, and transmitting the noise added aggregation function estimation result and the noise estimation signal to other specified generators; S5, constructing a noise estimation model, and estimating original noise according to a noise estimation signal to obtain the input of an aggregation function estimation model; S6, constructing a time-varying Nash balance point search model, and determining an optimized output strategy of the generator; And S7, constructing a state space expression of the turbine generator, and generating a power control input to drive the generator to output power according to a preset strategy. Preferably, in the step