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Optimal Techno-Economic Design of Standalone Hybrid Renewable Energy System Using Genetic Algorithm

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dc.citedby2
dc.contributor.authorHlal I.M.en_US
dc.contributor.authorRamachandaramurthy V.K.en_US
dc.contributor.authorHafiz Nagi F.en_US
dc.contributor.authorBin Tuan Abdullah T.A.R.en_US
dc.contributor.authorid57205344223en_US
dc.contributor.authorid6602912020en_US
dc.contributor.authorid56373028000en_US
dc.contributor.authorid57200039159en_US
dc.date.accessioned2023-05-29T07:24:46Z
dc.date.available2023-05-29T07:24:46Z
dc.date.issued2019
dc.descriptionEnergy conservation; Environmental technology; Multiobjective optimization; Renewable energy resources; Rural areas; Wind; Wind turbines; Battery energy storages (BES); Cost of energies; Hybrid renewable energy systems; Loss of power supply probability; Remote location; Rural electrification; Sorting genetic algorithm; Techno-economics; Genetic algorithmsen_US
dc.description.abstractThis paper presents a methodology to size Standalone Hybrid Renewable Energy System (SHRES) which combines solar PV, wind turbine (WT) and battery energy storage (BES) for application in rural areas. These sources are integrated via an AC bus to support the load demand. SHRES is simulated under varying load demand, solar radiation, temperature and wind speed obtained from the Malaysian Meteorological Department. A Multi-objective Optimization using Non-dominate Sorting Genetic Algorithm (NSGA-II) was utilized to determine the best sizing of PV / wind turbine / battery, and minimize Cost of Energy (COE) and Loss of Power Supply Probability (LPSP). The results show that the NSGAII optimization of the model is able to determine the best techno-economic sizing for the suggested location. For the case study, the optimum COE was 0.1099 (USD/kWh) and LPSP was 0.0865. The proposed tool can be used to size the SHRES for rural electrification and enhance energy access within remote locations. � Published under licence by IOP Publishing Ltd.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo12012
dc.identifier.doi10.1088/1755-1315/268/1/012012
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85068688425
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85068688425&doi=10.1088%2f1755-1315%2f268%2f1%2f012012&partnerID=40&md5=5b43f8d7495004cfa3b0ed8ac502d652
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24585
dc.identifier.volume268
dc.publisherInstitute of Physics Publishingen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleIOP Conference Series: Earth and Environmental Science
dc.titleOptimal Techno-Economic Design of Standalone Hybrid Renewable Energy System Using Genetic Algorithmen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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