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<ArticleSet>
<Article>
<Journal>
<PublisherName>OICC Press</PublisherName>
<JournalTitle>Majlesi Journal of Electrical Engineering</JournalTitle>
<Issn>2345-3796</Issn>
<Volume>9</Volume>
<Issue>1</Issue>
<PubDate PubStatus="epublish">
<Year>2024</Year>
<Month>02</Month>
<Day>20</Day>
</PubDate>
</Journal>
<ArticleTitle>Reliability and Security Constrained Unit Commitment With Hybrid Optimization Method</ArticleTitle>
<VernacularTitle></VernacularTitle>
<FirstPage></FirstPage>
<LastPage></LastPage>
<ELocationID EIdType="doi"></ELocationID>
<Language>EN</Language>
<AuthorList>
<Author>
<FirstName>Ahmad</FirstName>
<LastName>Heidari</LastName>
<Affiliation>Department of Electrical Engineering, Malek-Ashtar University of Technology (MUT), Tehran, Iran.</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Mohammad Reza</FirstName>
<LastName>Alizadeh Pahlavani</LastName>
<Affiliation>Department of Electrical Engineering, Malek-Ashtar University of Technology (MUT), Tehran, Iran.</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Hamid</FirstName>
<LastName>Dehghani</LastName>
<Affiliation>Department of Electrical Engineering, Malek-Ashtar University of Technology (MUT), Tehran, Iran.</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
</AuthorList>
<PublicationType>Journal Article</PublicationType>
<History>
<PubDate PubStatus="received">
<Year>2024</Year>
<Month>02</Month>
<Day>20</Day>
</PubDate>
</History>
<Abstract>This paper presents an advanced optimization technique to solve unit commitment problems and reliability issues simultaneously for thermal generating units. To solve unit commitment, generalized benders decomposition along with genetic algorithm to include minimum up/down time constraints are proposed, and for reliability issues consideration, a fuzzy stochastic-based technique is presented. To implement the problem into an optimization program, the MATLAB software, and CPLEX and KNITRO solvers are used. To verify the proposed technique and algorithm, two case studies that are IEEE 14 and 118 bus systems are implemented for optimal generation scheduling, and reliability issues. Finally, a comparison with other solution techniques has been given.</Abstract>
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<Object Type="keyword">
<Param Name="value">Benders decomposition</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Fuzzy programming</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Genetic Algorithm</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Optimization technique</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Reliability Issues</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Unit commitment</Param>
</Object>
</ObjectList>
</Article>
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