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Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems

A sizing optimization of a hybrid system consisting of photovoltaic (PV) panels, a backup source (microturbine or diesel), and a battery system minimizes the cost of energy production (COE), and a complete design of this optimized system supplying a small community with power in the Palestinian Terr...

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Main Authors: Ismail M.S., Moghavvemi M., Mahlia T.M.I.
Other Authors: 9633224700
Format: Article
Published: Elsevier Ltd 2023
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spelling my.uniten.dspace-221202023-05-16T10:47:34Z Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems Ismail M.S. Moghavvemi M. Mahlia T.M.I. 9633224700 7003701545 56997615100 A sizing optimization of a hybrid system consisting of photovoltaic (PV) panels, a backup source (microturbine or diesel), and a battery system minimizes the cost of energy production (COE), and a complete design of this optimized system supplying a small community with power in the Palestinian Territories is presented in this paper. A scenario that depends on a standalone PV, and another one that depends on a backup source alone were analyzed in this study. The optimization was achieved via the usage of genetic algorithm. The objective function minimizes the COE while covering the load demand with a specified value for the loss of load probability (LLP). The global warming emissions costs have been taken into account in this optimization analysis. Solar radiation data is firstly analyzed, and the tilt angle of the PV panels is then optimized. It was discovered that powering a small rural community using this hybrid system is cost-effective and extremely beneficial when compared to extending the utility grid to supply these remote areas, or just using conventional sources for this purpose. This hybrid system decreases both operating costs and the emission of pollutants. The hybrid system that realized these optimization purposes is the one constructed from a combination of these sources. © 2014 Elsevier Ltd. All rights reserved. Final 2023-05-16T02:47:33Z 2023-05-16T02:47:33Z 2014 Article 10.1016/j.enconman.2014.05.064 2-s2.0-84902650959 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902650959&doi=10.1016%2fj.enconman.2014.05.064&partnerID=40&md5=908e74d9dba8f7568c7a5d81a75126cc https://irepository.uniten.edu.my/handle/123456789/22120 85 120 130 Elsevier Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
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description A sizing optimization of a hybrid system consisting of photovoltaic (PV) panels, a backup source (microturbine or diesel), and a battery system minimizes the cost of energy production (COE), and a complete design of this optimized system supplying a small community with power in the Palestinian Territories is presented in this paper. A scenario that depends on a standalone PV, and another one that depends on a backup source alone were analyzed in this study. The optimization was achieved via the usage of genetic algorithm. The objective function minimizes the COE while covering the load demand with a specified value for the loss of load probability (LLP). The global warming emissions costs have been taken into account in this optimization analysis. Solar radiation data is firstly analyzed, and the tilt angle of the PV panels is then optimized. It was discovered that powering a small rural community using this hybrid system is cost-effective and extremely beneficial when compared to extending the utility grid to supply these remote areas, or just using conventional sources for this purpose. This hybrid system decreases both operating costs and the emission of pollutants. The hybrid system that realized these optimization purposes is the one constructed from a combination of these sources. © 2014 Elsevier Ltd. All rights reserved.
author2 9633224700
author_facet 9633224700
Ismail M.S.
Moghavvemi M.
Mahlia T.M.I.
format Article
author Ismail M.S.
Moghavvemi M.
Mahlia T.M.I.
spellingShingle Ismail M.S.
Moghavvemi M.
Mahlia T.M.I.
Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems
author_sort Ismail M.S.
title Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems
title_short Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems
title_full Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems
title_fullStr Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems
title_full_unstemmed Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems
title_sort genetic algorithm based optimization on modeling and design of hybrid renewable energy systems
publisher Elsevier Ltd
publishDate 2023
_version_ 1806425490878103552
score 13.211869

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