{"title":"Analysis of Load Frequency Control using Extended Kalman filter and Linear Quadratic Regulator based controller","authors":"Vishwas Vasuki Gautam, Renuka Loka, A. M. Parimi","doi":"10.1109/PARC52418.2022.9726570","DOIUrl":null,"url":null,"abstract":"Increasing power demands for sustenance cause power systems to receive multiple load disturbances rapidly, leading to variations in the system frequencies, thus making Load Frequency Control (LFC) one of the critical research areas in power system operation. One solution is the Linear Quadratic Regulator (LQR) based feedback controller for LFC that computes the optimal feedback gain values from the known system parameters and state variables by minimizing a cost function. However, all the system parameters and state variables may not be available at all times, which restricts the use of the LQR controller. Therefore, the proposed estimation algorithm, i.e., the Extended Kalman filter (EKF), is utilized to estimate the state variables using a series of measurements over time. The simulation results produced using the EKF-LQR-based controller validate that the proposed scheme can efficiently regulate the system frequency and offer robust performance compared to Virtual Synchronous Generator-based (VSG) and conventional PID controllers.","PeriodicalId":158896,"journal":{"name":"2022 2nd International Conference on Power Electronics & IoT Applications in Renewable Energy and its Control (PARC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Power Electronics & IoT Applications in Renewable Energy and its Control (PARC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PARC52418.2022.9726570","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Increasing power demands for sustenance cause power systems to receive multiple load disturbances rapidly, leading to variations in the system frequencies, thus making Load Frequency Control (LFC) one of the critical research areas in power system operation. One solution is the Linear Quadratic Regulator (LQR) based feedback controller for LFC that computes the optimal feedback gain values from the known system parameters and state variables by minimizing a cost function. However, all the system parameters and state variables may not be available at all times, which restricts the use of the LQR controller. Therefore, the proposed estimation algorithm, i.e., the Extended Kalman filter (EKF), is utilized to estimate the state variables using a series of measurements over time. The simulation results produced using the EKF-LQR-based controller validate that the proposed scheme can efficiently regulate the system frequency and offer robust performance compared to Virtual Synchronous Generator-based (VSG) and conventional PID controllers.