{"title":"Bus voltage stability control of DC microgrid considering voltage constraints","authors":"Zhong-Qiang Wu, Shao-Chen Geng, Zong-Kui Xie","doi":"10.3934/jimo.2023121","DOIUrl":null,"url":null,"abstract":"Aiming at the bus voltage fluctuation caused by nonlinearity, limited bus voltage change and uncertain factors such as bus voltage deviation, load and system parameter change caused by traditional droop control in DC microgrid, a precise bus voltage control scheme considering voltage constraints is proposed. Firstly, parabolic droop control is used to replace the traditional linear droop control to improve the accuracy of power distribution. On this basis, a bus voltage controller based on barrier Lyapunov function is designed to precisely control the voltage of droop control to reach the expected value. The controller adopts backstepping method to deal with nonlinear problems; the barrier Lyapunov function is used to design the system to meet the condition of voltage constraints; RBF neural network is used to eliminate the uncertainty in the system and improve the disturbance suppression ability of the system. The simulation results show that the designed controller can ensure voltage stability when the load changes and the system parameters change, and its performance is better than that of PI control. It can achieve high-precision control of bus voltage and load distribution when the state is limited. The simulation results verify that this control strategy can reduce voltage drop and achieve bus voltage stability.","PeriodicalId":16022,"journal":{"name":"Journal of Industrial and Management Optimization","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Industrial and Management Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3934/jimo.2023121","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Aiming at the bus voltage fluctuation caused by nonlinearity, limited bus voltage change and uncertain factors such as bus voltage deviation, load and system parameter change caused by traditional droop control in DC microgrid, a precise bus voltage control scheme considering voltage constraints is proposed. Firstly, parabolic droop control is used to replace the traditional linear droop control to improve the accuracy of power distribution. On this basis, a bus voltage controller based on barrier Lyapunov function is designed to precisely control the voltage of droop control to reach the expected value. The controller adopts backstepping method to deal with nonlinear problems; the barrier Lyapunov function is used to design the system to meet the condition of voltage constraints; RBF neural network is used to eliminate the uncertainty in the system and improve the disturbance suppression ability of the system. The simulation results show that the designed controller can ensure voltage stability when the load changes and the system parameters change, and its performance is better than that of PI control. It can achieve high-precision control of bus voltage and load distribution when the state is limited. The simulation results verify that this control strategy can reduce voltage drop and achieve bus voltage stability.
期刊介绍:
JIMO is an international journal devoted to publishing peer-reviewed, high quality, original papers on the non-trivial interplay between numerical optimization methods and practically significant problems in industry or management so as to achieve superior design, planning and/or operation. Its objective is to promote collaboration between optimization specialists, industrial practitioners and management scientists so that important practical industrial and management problems can be addressed by the use of appropriate, recent advanced optimization techniques.