AHP (analytic hierarchy process) and GA (genetic algorithm)-based parameter optimization method applied to participation of energy storage device in power grid frequency modulation

Abstract

The invention discloses an AHP (analytic hierarchy process) and GA (genetic algorithm)-based parameter optimization method applied to the participation of an energy storage device in power grid frequency modulation. The method includes the following steps that: the energy storage device and a controller thereof are added into a regional frequency modulation model; the analytic hierarchy process is utilized to determine the weight of the factors of the controller that influence a control effect, so that a fitness function can be obtained; the genetic algorithm is utilized to optimize control parameters, so that optimized parameters can be obtained; and the optimized parameters are screened according to the fitness function, optimized individuals are obtained; and the optimized individuals are transported to the energy storage device to control the output power of the energy storage device. According to the AHP (analytic hierarchy process) and GA (genetic algorithm)-based parameter optimization method applied to the participation of the energy storage device in power grid frequency modulation of the invention, an energy storage device assisted AGC frequency modulation mode is adopted, and therefore, frequency modulation performance can be effectively improved, frequency disturbance can be suppressed effectively, the frequency deviation of a system can be effectively reduced, and adjustment time can be shortened; and the analytic hierarchy process and genetic algorithm are adopted to set the parameters of the controller, so that high accuracy and high flexibility can be realized.

Description

technical field [0001] The invention relates to the field of power systems, in particular to a parameter optimization method for an energy storage device based on AHP and GA to participate in power grid frequency regulation. Background technique [0002] The traditional frequency modulation device in the power system responds slowly to disturbances, and is not suitable for participating in short-cycle frequency modulation; the energy storage device has the characteristics of fast response speed, accurate tracking, and two-way energy flow, which can effectively assist the traditional frequency modulation device. The frequency of the power grid after the disturbance is adjusted; therefore, the energy storage device assists in the frequency regulation of the power system, which has certain practical value for the safe and stable operation of the power grid. [0003] For the research on energy storage devices assisting in frequency modulation, different types of energy storage d...

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Problems solved by technology

[0004] Partially based on fuzzy control to control the battery energy storage, assisting the AGC to adjust the frequency, but the BESS model used is simulated by the first-order inertial link, without considering the state of charge and capacity of the energy storage; using the time absolute deviation product integral (ITAE) is used as the fitness function of the improved particle swarm optimization algorithm to adjust the PI controller parameters of the energy storage system, and there is a defect that the ITAE criterion has a single judgment factor and may have inaccurate judgments.

[0005] Although the current research has noticed that the parameters of the energy storage controller have a certain influence on the control effect, the evaluation indicators selected in the control strategy are relatively simple, and the evaluation indicators (such as maximum deviation amplitude, stable state deviation, adjustment time, etc.), and then optimize the control parameters of the energy storage controller

[0006] Using the maximum deviation amplitude, steady-state deviation, adjustment time and other indicators to construct the genetic algorithm fitness function can make the genetic algorithm optimize the control parameters of the energy storage device to achieve the best effect, but the difficulty of constructing the fitness function lies in the relationship between the three and the regional The weight ratio relationship among them is vague and difficult to judge, and it is often necessary to manually determine the weight, but human judgment will lead to inconsistent weights due to the lack of understanding of the complex relationship.

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