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Optimization of emission cost and economic analysis for microgrid by considering a metaheuristic algorithm-assisted dispatch model

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dc.citedby8
dc.contributor.authorSomakumar R.en_US
dc.contributor.authorKasinathan P.en_US
dc.contributor.authorMonicka G.en_US
dc.contributor.authorRajagopalan A.en_US
dc.contributor.authorRamachandaramurthy V.K.en_US
dc.contributor.authorSubramaniam U.en_US
dc.contributor.authorid57494441300en_US
dc.contributor.authorid57194393495en_US
dc.contributor.authorid57191916704en_US
dc.contributor.authorid57194865787en_US
dc.contributor.authorid6602912020en_US
dc.contributor.authorid57199091461en_US
dc.date.accessioned2023-05-29T09:37:09Z
dc.date.available2023-05-29T09:37:09Z
dc.date.issued2022
dc.descriptionCost benefit analysis; Cost functions; Costs; Diesel engines; Economic analysis; Electric load dispatching; Electric power system economics; Electric power transmission networks; Genetic algorithms; Iterative methods; Natural resources; Renewable energy resources; Solar power generation; Cost analysis; Dispatch model; Economics analysis; Emission costs; High demand; Meta-heuristics algorithms; Microgrid; Optimisations; Power grids; Renewable energy source; Fuel cellsen_US
dc.description.abstractElectric vehicles (EVs) have witnessed a steady and continuous rise in the last few years. The increased prevalence of EVs results in high demand for electricity from the power grid and it can be effectively handled by combining EV charging infrastructure with renewable energy sources (RES). However, the intermittent characteristic of RES introduces an additional challenge to the power grid. This paper proposes a metaheuristic algorithm called self-adaptive elephant herd optimization algorithm (SA-EHO) to achieve the desired dispatch model of microgrid (MG) with EVs and RES. The proposed algorithm optimizes both economic and emission cost of MG which comprises diesel engine (DE), solar photovoltaic (PV), EVs, fuel cell (FC), wind turbine (WT), and loads. The output constraints associated with a distributed power supply such as power limits of distributed generators (DG) and charging of EVs followed by its discharging are subjected to optimization. Finally, the performance of the proposed model is compared and proved over other existing models. Especially, a minimal total cost of the proposed model is 16.79%, 21.58%, 20%, 26.67%, and 1.33% superior to traditional HSA, GA, EHO, MSA, and FS-MSA models at 100th iteration. Furthermore, the reserved cost of the proposed scheme for the third scenario is 77.78%, 90.91%, 85.71%, 90.91%, and 90.91% superior to existing models such as HSA, GA, EHO, MSA, and FS-MSA, respectively. � 2022 John Wiley & Sons, Ltd.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNoe2993
dc.identifier.doi10.1002/jnm.2993
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85126107532
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85126107532&doi=10.1002%2fjnm.2993&partnerID=40&md5=629980ddc8a5a1cf5b712a57b90bc8e1
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26844
dc.identifier.volume35
dc.publisherJohn Wiley and Sons Ltden_US
dc.sourceScopus
dc.sourcetitleInternational Journal of Numerical Modelling: Electronic Networks, Devices and Fields
dc.titleOptimization of emission cost and economic analysis for microgrid by considering a metaheuristic algorithm-assisted dispatch modelen_US
dc.typeArticleen_US
dspace.entity.typePublication
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