A New Adaptive Switching Control Method for the Complex Operating Condition of the Grid-Connected Power System

Author:

Yu Miao123ORCID,Zhang Yihui12ORCID,Zhang Shouzhi12ORCID,Hu Jingxuan12ORCID,Yang Shuwei12ORCID,Du Weijie12ORCID,Li Jinglin12ORCID

Affiliation:

1. School of Mechanical-Electronic and Automobile Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China

2. Beijing Key Laboratory of Service Performance of Urban Rail Transit Vehicles, Beijing University of Civil Engineering and Architecture, Beijing 100044, China

3. State Key Laboratory of Control and Simulation of Power System and Generation Equipment, Tsinghua University, Beijing 100084, China

Abstract

Due to the increase in wind power accessing power system in recent years, the low-frequency oscillation of power system is more complicated. Therefore, a new adaptive switching control method combined with a nonlinear system is proposed for the complex operating conditions of the grid-connected power system. Firstly, this method decomposes the low-frequency oscillation control problem of the power system into two parts, which are the linear system control and the nonlinear system control. Then, in the linear system control part, the iterative identification method is used to control this part. In the nonlinear system control part, the nonlinear term is decomposed into a combination of the previous beating measurable and the nonlinear estimation increment. Secondly, the nonlinear system is divided into three different operating conditions by the nonlinear estimation increment. Thus, four different adaptive controllers are obtained. Then, the designed controller is switched according to the controlled object with four controllers by the switching function, which not only ensures the stability of the closed-loop system, but also improves the control performance of the controller under different operating conditions. Finally, the feasibility and effectiveness of this method are verified, and the controller can fit the control efficiency of the real power system well.

Funder

Beijing University of Civil Engineering and Architecture

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,General Computer Science,Signal Processing

Reference18 articles.

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