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Optimal Integration of Active and Reactive Power DGs in Distribution Network via a Novel Multi-Objective Intelligent Technique

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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.authorShaaya S.A.en_US
dc.contributor.authorSenthil Kumar A.V.en_US
dc.contributor.authorid57197864035en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid35944613200en_US
dc.contributor.authorid11639107900en_US
dc.contributor.authorid16022846200en_US
dc.contributor.authorid56888921600en_US
dc.date.accessioned2025-03-03T07:48:17Z
dc.date.available2025-03-03T07:48:17Z
dc.date.issued2024
dc.description.abstractThis work introduces a novel approach called the Multi-Objective Integrated Immune Moth Flame Evolutionary Programming (MO-IIMFEP) algorithm. This algorithm aims to determine the optimal sizes and positions for Type III distributed generators (DGs) that generate both active and reactive power. The objectives involve reducing overall losses in the distribution system while adhering to voltage restrictions and taking into account the cost limitations connected with the installation of DG. MO-IIMFEP overcomes the constraints of traditional Evolutionary Programming (EP) and Moth Flame Optimization (MFO), particularly in effectively handling local optima. Fuzzy logic is employed in MO-IIMFEP to determine the best solution to compromise conflicting goals, as obtained from the non-dominated Pareto solutions. The efficacy of MOIIMFEP in identifying optimal solutions for multi-objective problems is demonstrated through comprehensive assessments conducted on the 118-Bus Radial Distribution Systems (RDS), comparing it against MO-EP and MO-MFO. The results underscore the strategic benefits of DG installation in sustaining voltage levels, reducing power losses, and minimizing total operating costs for power suppliers. ? 2024 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ICPEA60617.2024.10498595
dc.identifier.epage162
dc.identifier.scopus2-s2.0-85191739695
dc.identifier.spage157
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85191739695&doi=10.1109%2fICPEA60617.2024.10498595&partnerID=40&md5=7f1239ee241ed192b3d0f6d17a874cf8
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/37176
dc.pagecount5
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2024 IEEE 4th International Conference in Power Engineering Applications: Powering the Future: Innovations for Sustainable Development, ICPEA 2024
dc.subjectComputer programming
dc.subjectCost reduction
dc.subjectDistributed power generation
dc.subjectEvolutionary algorithms
dc.subjectFuzzy logic
dc.subjectOperating costs
dc.subjectReactive power
dc.subjectActive and Reactive Power
dc.subjectCumulative voltage deviation
dc.subjectDistributed generators
dc.subjectDistribution systems
dc.subjectMulti objective
dc.subjectMulti-objectives optimization
dc.subjectPowerloss
dc.subjectTotal power
dc.subjectTotal power loss
dc.subjectVoltage deviations
dc.subjectMultiobjective optimization
dc.titleOptimal Integration of Active and Reactive Power DGs in Distribution Network via a Novel Multi-Objective Intelligent Techniqueen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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