{"title":"Load Frequency Control Analysis of PV System Using PID and ANFC Controller","authors":"R. Rituraj, A. Várkonyi-Kóczy","doi":"10.1109/INES52918.2021.9512913","DOIUrl":null,"url":null,"abstract":"This paper deals with the Adaptive neuro-fuzzy inference system (ANFIS)–based load frequency controller (LFC). These controllers are projected for load frequency control of thermal-Photovoltaic (PV) power generation entity as a hybrid power system. In this study, random solar isolation is applied to the proposed hybrid power system. The proposed hybrid power system consists of a PV power unit with a maximum power point tracking control, a PV inverter, and an AC load. Simulations are performed with structural change in the load setting. The solar isolation results are compared with conventional proportional-integral-derivative (PID) and fuzzy logic controller (FLC). The results are then projected with an ANFIS based LFC. The simulation results observed that ANFIS attains a relatively better response for the frequency deviation profile. It typically controls the frequency deviation of a given hybrid power system and thereby advances the dynamic performances. The results also show that the performance of the hybrid power system with the use of ANFIS based neuro-fuzzy controllers attains relatively better than those which attains by the PID and FLC.","PeriodicalId":427652,"journal":{"name":"2021 IEEE 25th International Conference on Intelligent Engineering Systems (INES)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 25th International Conference on Intelligent Engineering Systems (INES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES52918.2021.9512913","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper deals with the Adaptive neuro-fuzzy inference system (ANFIS)–based load frequency controller (LFC). These controllers are projected for load frequency control of thermal-Photovoltaic (PV) power generation entity as a hybrid power system. In this study, random solar isolation is applied to the proposed hybrid power system. The proposed hybrid power system consists of a PV power unit with a maximum power point tracking control, a PV inverter, and an AC load. Simulations are performed with structural change in the load setting. The solar isolation results are compared with conventional proportional-integral-derivative (PID) and fuzzy logic controller (FLC). The results are then projected with an ANFIS based LFC. The simulation results observed that ANFIS attains a relatively better response for the frequency deviation profile. It typically controls the frequency deviation of a given hybrid power system and thereby advances the dynamic performances. The results also show that the performance of the hybrid power system with the use of ANFIS based neuro-fuzzy controllers attains relatively better than those which attains by the PID and FLC.