Isaac Kofi Otchere, Kwabena Amoako Kyeremeh, E. Frimpong
{"title":"Adaptive PI-GA Based Technique for Automatic Generation Control with Renewable Energy Integration","authors":"Isaac Kofi Otchere, Kwabena Amoako Kyeremeh, E. Frimpong","doi":"10.1109/PowerAfrica49420.2020.9219960","DOIUrl":null,"url":null,"abstract":"To enhance the reliability of the power system, conventional power grid requires a robust automatic generation control system to maintain the balance between generation and demand. However, high penetration of renewable energy such as photovoltaic and wind energy to the power grid requires a flexible control technique to maintain the stability of the power system. This paper presents an adaptive proportional-integral (PI) based genetic algorithm (GA) controller for a two-area non-reheat thermal plant coupled with renewable energy sources (RES). The test system is simulated in a MATLAB/Simulink environment. Test results of the proposed technique shows an improved performance with zero frequency deviation and less settling time after a load disturbance. PI based particle swarm optimization control is used as a benchmark.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE PES/IAS PowerAfrica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PowerAfrica49420.2020.9219960","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
To enhance the reliability of the power system, conventional power grid requires a robust automatic generation control system to maintain the balance between generation and demand. However, high penetration of renewable energy such as photovoltaic and wind energy to the power grid requires a flexible control technique to maintain the stability of the power system. This paper presents an adaptive proportional-integral (PI) based genetic algorithm (GA) controller for a two-area non-reheat thermal plant coupled with renewable energy sources (RES). The test system is simulated in a MATLAB/Simulink environment. Test results of the proposed technique shows an improved performance with zero frequency deviation and less settling time after a load disturbance. PI based particle swarm optimization control is used as a benchmark.