Technical-ecological optimization of the operation of a multi-source electrical system injecting into a distribution network using homer software and genetic algorithms

dc.contributor.authorOloulade, Arouna
dc.contributor.authorMOUKENGUE IMANO, ADOLPHE
dc.contributor.authorFIFATIN, François-Xavier
dc.contributor.authorOussou, Romain Agossou
dc.contributor.authorGANYE, Amedee
dc.contributor.authorAGBOMAHENA, MACAIRE BIENVENU
dc.contributor.authorVIANOU, Antoine
dc.contributor.authorBADAROU, RAMANOU
dc.date.accessioned2026-06-02T16:06:57Z
dc.date.available2026-06-02T16:06:57Z
dc.date.issued2020
dc.description.abstractThis work consisted in positioning and sizing a photovoltaic solar power plant with or without storage in an existing hybrid system consisting of a Diesel power plant, a hydroelectric power plant and an infinite network. Genetic algorithms and Homer software inspire the tools used. The objectives of this study are the minimization of losses, voltage deviations, greenhouse gases and the cost of energy distributed to the customer. From this study, it emerges that the optimal hybrid system is that consisting of 2.11 MW photovoltaic (1.71 MW at node 169 and 0.4 MW at node 110), 1 MW hydroelectricity, 4 MW Diesel and 1 MW Network. Greenhouse gas emissions have improved by 20.96% and the cost of hybrid energy has dropped from 166 FCFA to 120 FCFA, a decrease of 28.75%.
dc.identifier.doi10.1109/PowerAfrica49420.2020.9219833
dc.identifier.otherBECDB-12847
dc.identifier.urihttps://dspace.uac.bj/handle/123456789/11076
dc.language.isofr
dc.relation.ispartofIEEE
dc.subjectDecentralized sources
dc.subjectGenetic algorithms
dc.subjectGreenhouse gas
dc.subjectHomer software
dc.subjectMicro-production of renewable energy.
dc.titleTechnical-ecological optimization of the operation of a multi-source electrical system injecting into a distribution network using homer software and genetic algorithms
dc.typeArticle

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