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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>9</Volume>
				<Issue>3</Issue>
				<PubDate PubStatus="epublish">
					<Year>2021</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Antlion Optimization Algorithm for Optimal Self-Scheduling Unit ‎Commitment in Power System Under Uncertainties</ArticleTitle>
<VernacularTitle>الگوریتم بهینه سازی شیرمورچه برای بهینه سازی خودبرنامه ریزی هماهنگی نیروگاهها، در سیستم قدرت تحت عدم قطعیت ها.</VernacularTitle>
			<FirstPage>226</FirstPage>
			<LastPage>241</LastPage>
			<ELocationID EIdType="pii">1110</ELocationID>
			
<ELocationID EIdType="doi">10.22098/joape.2021.7941.1556</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>M.R.</FirstName>
					<LastName>Behnamfar</LastName>
<Affiliation>Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful,</Affiliation>

</Author>
<Author>
					<FirstName>H.</FirstName>
					<LastName>Barati</LastName>
<Affiliation>Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful,</Affiliation>

</Author>
<Author>
					<FirstName>M.</FirstName>
					<LastName>Karami</LastName>
<Affiliation>Department of Electrical Engineering, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2020</Year>
					<Month>10</Month>
					<Day>26</Day>
				</PubDate>
			</History>
		<Abstract>optimal and economic operation is one of the main topics in power systems. In this paper, a stochastic single objective framework for GenCoʼs optimal self-scheduling unit commitment under the uncertain condition and in the presence of SH units is proposed. In order to solve this problem, a new meta-heuristic optimization technique named antlion optimizer (ALO) has been used. Some of the capabilities of the ALO algorithm for solving the optimization problems included : (1) the exploration and utilization, (2) abiding convergence, (3) capable of maintaining population variety, (4) lack of regulation parameters, (5) solving problems with acceptable quality. To approximate the simulation conditions to the actual operating conditions, the uncertainties of the energy price, spinning and non-spinning reserve (operating services) prices, as well as the renewable energy resources uncertainty, are considered in the proposed model. The objective function of the problem is profit maximization and modeled as a mixed-integer programming (MIP) problem. The proposed model is implemented on an IEEE 118-bus test system and is solved in the form of six case studies. Finally, the simulation results substantiate the strength and accuracy of the proposed model.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Antlion optimization algorithm</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Hydro-thermal self-scheduling</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Price uncertainty</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">WP and PV power uncertainty</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">SH power plant</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://joape.uma.ac.ir/article_1110_3f43285777c150ede4f212c5d3aa465b.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
