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<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Kashan</PublisherName>
				<JournalTitle>Soft Computing Journal</JournalTitle>
				<Issn>2322-3707</Issn>
				<Volume>6</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2021</Year>
					<Month>05</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Frequency Control of an Islanded Microgrid based on Intelligent Control of Demand Response using Fuzzy Logic and Particle Swarm Optimization (PSO) Algorithm</ArticleTitle>
<VernacularTitle>Frequency Control of an Islanded Microgrid based on Intelligent Control of Demand Response using Fuzzy Logic and Particle Swarm Optimization (PSO) Algorithm</VernacularTitle>
			<FirstPage>18</FirstPage>
			<LastPage>31</LastPage>
			<ELocationID EIdType="pii">111419</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Reza</FirstName>
					<LastName>Ghasemi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Hamid Reza</FirstName>
					<LastName>Mohammadi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Seyed Abbas</FirstName>
					<LastName>Taher</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>05</Month>
					<Day>23</Day>
				</PubDate>
			</History>
		<Abstract>Due to the increasing penetration of renewable energies in the power system, the frequency control problem has attracted more attention, while the traditional control methods are not capable of regulating the frequency and securing the stability of the system. In smart grids, demand response as the frequency control tool reduces the dependence on spinning reserve and high cost controllers. In addition to the economic benefits of the demand response control, its high-speed in damping of frequency changes is significant. In this paper, based on intelligent control of demand response and using fuzzy logic and particle swarm optimization algorithm, frequency control of an islanded microgrid is proposed. This approach is capable of continuously balancing the generation and demand in case of natural undetermined variation in the output power of wind generation and photovoltaic systems. In comparison with the related work, the proposed controller improves the settling time, overshoot, and undershoot of the response. Moreover, it resolves the restriction of the energy storage systems and effectively reduces environmental pollution due to diesel operation. The simulation results in an islanded microgrid show the good performance of the proposed intelligent controller for demand response control in comparison with traditional controllers.</Abstract>
			<OtherAbstract Language="FA">Due to the increasing penetration of renewable energies in the power system, the frequency control problem has attracted more attention, while the traditional control methods are not capable of regulating the frequency and securing the stability of the system. In smart grids, demand response as the frequency control tool reduces the dependence on spinning reserve and high cost controllers. In addition to the economic benefits of the demand response control, its high-speed in damping of frequency changes is significant. In this paper, based on intelligent control of demand response and using fuzzy logic and particle swarm optimization algorithm, frequency control of an islanded microgrid is proposed. This approach is capable of continuously balancing the generation and demand in case of natural undetermined variation in the output power of wind generation and photovoltaic systems. In comparison with the related work, the proposed controller improves the settling time, overshoot, and undershoot of the response. Moreover, it resolves the restriction of the energy storage systems and effectively reduces environmental pollution due to diesel operation. The simulation results in an islanded microgrid show the good performance of the proposed intelligent controller for demand response control in comparison with traditional controllers.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Frequency Control</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Microgrid</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Demand Response</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fuzzy Logic</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Particle Swarm Optimization</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://scj.kashanu.ac.ir/article_111419_02dd9281ac059650ccff01e50b972239.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
