<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
		<Article>
		<Journal>
			<PublisherName>Majlesi Journal of Electrical Engineering</PublisherName>
			<JournalTitle>Biogeography based Novel AI Optimization with SSSC for Optimal Power Flow</JournalTitle>
			<Issn></Issn>
			<Volume>Volume 12 (2018)</Volume>
			<Issue>Issue 2, June 2018</Issue>
			<PubDate PubStatus="epublish">
                <Year>2024</Year>
                <Month>02</Month>
                <Day>15</Day>
			</PubDate>
		</Journal>
		<ArticleTitle>Biogeography based Novel AI Optimization with SSSC for Optimal Power Flow</ArticleTitle>
		<VernacularTitle></VernacularTitle>
		<FirstPage></FirstPage>
		<LastPage></LastPage>
		<ELocationID EIdType="doi"></ELocationID>
		<Language>EN</Language>
		<AuthorList>
            			<Author>
                				<FirstName>Sandeep</FirstName>
				<LastName>Gupta</LastName>
				<Affiliation>Department of Electrical Engineering, JECRC University, Jaipur, Rajasthan-303905, India</Affiliation>
				<Identifier Source="ORCID"></Identifier>
			</Author>
            			<Author>
                				<FirstName>Navdeep</FirstName>
				<LastName>Singh</LastName>
				<Affiliation>Department of Electrical Engineering, MMMUT Gorakhpur UP- 273010, India</Affiliation>
				<Identifier Source="ORCID"></Identifier>
			</Author>
            			<Author>
                				<FirstName>Kirti</FirstName>
				<LastName>Joshi</LastName>
				<Affiliation>Department of Electrical Engineering, JECRC University, Jaipur, Rajasthan-303905, India</Affiliation>
				<Identifier Source="ORCID"></Identifier>
			</Author>
            		</AuthorList>
		<PublicationType>Journal Article</PublicationType>
		<History>
			<PubDate PubStatus="received">
				<Year>2024</Year>
				<Month>02</Month>
				<Day>15</Day>
			</PubDate>
		</History>
		<Abstract>This paper objective presents static synchronous series compensation FACTS device with biogeography based optimization (BBO) to deal for obtaining worthwhile power flow control. The biogeography based optimization method is utilized to find the optimal fitted child sets by surviving parents with the help of migration and mutation process. The present BBO technique from the evolutionary strategy with static synchronous series compensator provides improved outcomes in comparison to other optimization methods. The simulation outcomes illustrate that the proposed BBO algorithm is efficacious, secure and correct to search the optimized values with SSSC based FACTS devices. The proposed method is considering the solution quality appears to be an optimistic substitute method for extricating the OPF problems. The simplification and effectiveness of this method are validated on the IEEE 57 bus and 75 bus Systems. In this paper, from the outcome results, it is clearly show that the proposed technique execution properly and can effectively apply to the optimal position of multiple OPF problems. i.e. BBO based algorithm with SSSC FACTS device is found better results when compared to without SSSC device in all aspects. </Abstract>
		<ObjectList>
            			<Object Type="keyword">
				<Param Name="value">SSSC Device</Param>
			</Object>
						<Object Type="keyword">
				<Param Name="value">FACTS Device and Optimization Technique</Param>
			</Object>
						<Object Type="keyword">
				<Param Name="value">OpenCV</Param>
			</Object>
						<Object Type="keyword">
				<Param Name="value">BBO</Param>
			</Object>
						<Object Type="keyword">
				<Param Name="value">Optimal Power Flow (OPF)</Param>
			</Object>
					</ObjectList>
	</Article>
	</ArticleSet>
