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<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Mohaghegh Ardabili</PublisherName>
				<JournalTitle>Journal of Operation and Automation in Power Engineering</JournalTitle>
				<Issn>2322-4576</Issn>
				<Volume>4</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A SAIWD-Based Approach for Simultaneous Reconfiguration and Optimal Siting and Sizing of Wind Turbines and DVR units in Distribution Systems</ArticleTitle>
<VernacularTitle>ترکیب الگوریتم های تبرید شبیه سازی شده و چکه آب های هوشمند جهت بازآرایی همزمان همراه با تخصیص بهینه توربین بادی و بازیاب دینامیکی ولتاژ در شبکه های توزیع</VernacularTitle>
			<FirstPage>93</FirstPage>
			<LastPage>103</LastPage>
			<ELocationID EIdType="pii">470</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>A.</FirstName>
					<LastName>Lashkar Ara</LastName>
<Affiliation>Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran</Affiliation>

</Author>
<Author>
					<FirstName>H.</FirstName>
					<LastName>Bagheri Tolabi</LastName>
<Affiliation>Department of Electrical Engineering, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran</Affiliation>

</Author>
<Author>
					<FirstName>R.</FirstName>
					<LastName>Hosseini</LastName>
<Affiliation>Department of Computer Engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>09</Month>
					<Day>16</Day>
				</PubDate>
			</History>
		<Abstract>&lt;em&gt;In this paper, a combination of simulated annealing (SA) and intelligent water drops (IWD) algorithm is used to solve the nonlinear/complex problem of simultaneous reconfiguration with optimal allocation (size and location) of wind turbine (WT) as a distributed generation (DG) and dynamic voltage restorer (DVR) as a distributed flexible AC transmission systems&lt;strong&gt; (&lt;/strong&gt;DFACT) unit in a distribution system. The objectives of this research are to minimize active power loss, minimize operational cost, improve voltage stability, and increase the load balancing of the system. For evaluation purposes, the proposed algorithm is evaluated using the Tai-Power 11.4-kV real distribution network. The impacts of the optimal placement of the WT, DVR, and WT with DVR units are separately evaluated. The results are compared in terms of statistical indicators. By comparing all the testing scenarios, it is observed that the multi-objective optimization evolutionary algorithm is more beneficial than its single-objective optimization counterpart. Also, the obtained results show that the proposed SAIWD method outperforms the IWD method and other intelligent search algorithms such as genetic algorithm or particle swarm optimization.&lt;/em&gt;</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">distribution system</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Dynamic voltage restorer</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Intelligent water drops</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Reconfiguration</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Simulated annealing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">wind turbine</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://joape.uma.ac.ir/article_470_6bea5c53942fa258c2e1ffd88cfaa9da.pdf</ArchiveCopySource>
</Article>
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