{"title":"Wavelet NeuroFuzzy based STATCOM Control","authors":"Farman-ullah Jan, R. Badar","doi":"10.1109/ETECTE55893.2022.10007165","DOIUrl":null,"url":null,"abstract":"The main objective of this research is to use a Flexible AC Transmission System (FACTS) controller to increase the stability of AC grid. Power system stability is a major concern for reliable and secure operation of the system. FACTS controllers are mainly used for voltage regulation and power flow control; however, they can be very effective for power stability when equipped with efficiently designed auxiliary control. In this work, an artificial intelligence approach based on NeuroFuzzy Hermite wavelet based direct adaptive control has been used as an auxiliary controller for shunt-type FACTS controller. The performance of the proposed controller has been checked using Single Machine Infinite Bus and IEEE 9 BUS multimachine systems installed with a Static Synchronous Compensator (STATCOM), a shunt-type FACTS controller. Finally, the comparative evaluation of the proposed controller has been made in terms of local and inter-area modes of oscillations using nonlinear time domain simulations for different faults and operating conditions.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETECTE55893.2022.10007165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

The main objective of this research is to use a Flexible AC Transmission System (FACTS) controller to increase the stability of AC grid. Power system stability is a major concern for reliable and secure operation of the system. FACTS controllers are mainly used for voltage regulation and power flow control; however, they can be very effective for power stability when equipped with efficiently designed auxiliary control. In this work, an artificial intelligence approach based on NeuroFuzzy Hermite wavelet based direct adaptive control has been used as an auxiliary controller for shunt-type FACTS controller. The performance of the proposed controller has been checked using Single Machine Infinite Bus and IEEE 9 BUS multimachine systems installed with a Static Synchronous Compensator (STATCOM), a shunt-type FACTS controller. Finally, the comparative evaluation of the proposed controller has been made in terms of local and inter-area modes of oscillations using nonlinear time domain simulations for different faults and operating conditions.
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基于小波神经模糊的STATCOM控制
本研究的主要目的是利用柔性交流输电系统(FACTS)控制器来提高交流电网的稳定性。电力系统的稳定性是电力系统能否可靠、安全运行的重要问题。FACTS控制器主要用于电压调节和潮流控制;然而,当配备有效设计的辅助控制时,它们可以非常有效地保持电源稳定性。本文将基于神经模糊Hermite小波的人工智能直接自适应控制方法作为并联型FACTS控制器的辅助控制器。采用安装静态同步补偿器(STATCOM)(并联型FACTS控制器)的单机无限总线和ieee9总线多机系统对所提出的控制器的性能进行了检查。最后,利用非线性时域仿真对不同故障和运行条件下的局部和区域间振荡模式进行了比较评价。
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