Assessment of Amelioration in Frequency Regulation by deploying Novel Intelligent based Controller with Modified HVDC Tie-Line in Deregulated Environment
{"title":"Assessment of Amelioration in Frequency Regulation by deploying Novel Intelligent based Controller with Modified HVDC Tie-Line in Deregulated Environment","authors":"S. Murali, R. Shankar","doi":"10.1080/23080477.2022.2054197","DOIUrl":null,"url":null,"abstract":"ABSTRACT This article emphasizes the design and analysis of an optimal intelligent controller for frequency regulation application. The load frequency control (LFC) mechanism is an eminent and essential mechanism to reinstate the system frequency and scheduled tie-line power to their nominal values. Employing an appropriate controller enhances the operation of the LFC mechanism. Hence, this article put forward an adoptive control policy-based fuzzy-fractional ordered PI controller parallel with fractional PIDN controller (i.e., Fuzzy (PIλf)+PIλDN) for the LFC mechanism. Besides that, a maiden attempt of using a new opposition-learning-based volleyball premier league (OVPL) algorithm is carried out to obtain optimal control parameters. The proposed optimal intelligent controller is explored for a nonlinear multi-area interconnected power system under deregulated environment. The proposed LFC schemes performance has been compared with several popular strategies for step and random perturb in load. Also, the robustness of the proposed scheme has been verified for a wide range of system parameter variations. On the other hand, the modified HVDC tie-line model and the impact of the inertia emulation technique (IET) using converter capacitors on transient behavior are illustrated in this article. Finally, the efficacy of the proposed LFC scheme has been verified over published literature on its platform.","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23080477.2022.2054197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 3
Abstract
ABSTRACT This article emphasizes the design and analysis of an optimal intelligent controller for frequency regulation application. The load frequency control (LFC) mechanism is an eminent and essential mechanism to reinstate the system frequency and scheduled tie-line power to their nominal values. Employing an appropriate controller enhances the operation of the LFC mechanism. Hence, this article put forward an adoptive control policy-based fuzzy-fractional ordered PI controller parallel with fractional PIDN controller (i.e., Fuzzy (PIλf)+PIλDN) for the LFC mechanism. Besides that, a maiden attempt of using a new opposition-learning-based volleyball premier league (OVPL) algorithm is carried out to obtain optimal control parameters. The proposed optimal intelligent controller is explored for a nonlinear multi-area interconnected power system under deregulated environment. The proposed LFC schemes performance has been compared with several popular strategies for step and random perturb in load. Also, the robustness of the proposed scheme has been verified for a wide range of system parameter variations. On the other hand, the modified HVDC tie-line model and the impact of the inertia emulation technique (IET) using converter capacitors on transient behavior are illustrated in this article. Finally, the efficacy of the proposed LFC scheme has been verified over published literature on its platform.
期刊介绍:
Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials