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New Hybrid Multi-Objective Optimization Technique for Multi-DG Installation in Bulk Distribution System

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dc.citedby0
dc.contributor.authorAbdullah A.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorOthman M.M.en_US
dc.contributor.authorRahim S.R.A.en_US
dc.contributor.authorKumar A.V.S.en_US
dc.contributor.authorid57197864035en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid35944613200en_US
dc.contributor.authorid11639107900en_US
dc.contributor.authorid56888921600en_US
dc.date.accessioned2025-03-03T07:41:49Z
dc.date.available2025-03-03T07:41:49Z
dc.date.issued2024
dc.description.abstractThis article proposes a multi-objective Integrated Immune Moth Flame Evolutionary Programming (MO-IIMFEP) algorithm to identify the optimal sizing and placement of distribution generation (DG) in a radial distribution system (RDS). These objectives are simultaneously minimizing the total active power loss, reducing the total operating cost and reducing the cumulative voltage deviation (CVD) while considering the distribution system's operational constraints. With the aid of the fuzzy decision-making procedure, the non-dominant Pareto solutions are narrowed down to the optimal prospective compromise solution. The proposed efficacy is evaluated using a bulk distribution system, i.e. IEEE 118-bus RDS, and the outcomes are contrasted with multi-objective Evolutionary Programming (MO-EP) and multiobjective Moth Flame Optimization (MO-MFO) approaches. The outcomes demonstrate that the MO-IIMFEP algorithm is effective in obtaining the best compromise solutions for multi-objective problems. The study also shows that installing DG Type 1 into a distribution system with multi-objective optimization substantially reduces total power loss, enhances cumulative voltage deviation, and minimizes the total operating costs. ? 2024 American Institute of Physics Inc.. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo20001
dc.identifier.doi10.1063/5.0207745
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85205486569
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85205486569&doi=10.1063%2f5.0207745&partnerID=40&md5=4890623dc534d071709fe246ed51ba2d
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36292
dc.identifier.volume3115
dc.publisherAmerican Institute of Physicsen_US
dc.sourceScopus
dc.sourcetitleAIP Conference Proceedings
dc.titleNew Hybrid Multi-Objective Optimization Technique for Multi-DG Installation in Bulk Distribution Systemen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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