Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm Strategies
Hybrid renewable energy systems are a promising technology for clean and sustainable development. In this paper, an intelligent algorithm, based on a genetic algorithm (GA), was developed and used to optimize the energy management and design of wind/PV/tidal/ storage battery model for a stand-alone...
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doaj-1392de05794642149aba41ed72e165c32020-11-25T01:32:30ZengMDPI AGElectronics2079-92922018-10-0171023310.3390/electronics7100233electronics7100233Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm StrategiesOmar Hazem Mohammed0Yassine Amirat1Mohamed Benbouzid2Technical College of Mosul, Northern Technical University, Mosul 41002, IraqISEN Yncréa Ouest Brest, Institut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), 29200 Brest, FranceInstitut de Recherche Dupuy de Lôme (UMR CNRS 6027 IRDL), University of Brest, 29238 Brest, FranceHybrid renewable energy systems are a promising technology for clean and sustainable development. In this paper, an intelligent algorithm, based on a genetic algorithm (GA), was developed and used to optimize the energy management and design of wind/PV/tidal/ storage battery model for a stand-alone hybrid system located in Brittany, France. This proposed optimization focuses on the economic analysis to reduce the total cost of hybrid system model. It suggests supplying the load demand under different climate condition during a 25-years interval, for different possible cases and solutions respecting many constraints. The proposed GA-based optimization approach achieved results clear highlight its practicality and applicability to any hybrid power system model, including optimal energy management, cost constraint, and high reliability.http://www.mdpi.com/2079-9292/7/10/233hybrid energy systemgenetic algorithmenergy managementoptimizationeconomical coststand-alone system |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Omar Hazem Mohammed Yassine Amirat Mohamed Benbouzid |
spellingShingle |
Omar Hazem Mohammed Yassine Amirat Mohamed Benbouzid Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm Strategies Electronics hybrid energy system genetic algorithm energy management optimization economical cost stand-alone system |
author_facet |
Omar Hazem Mohammed Yassine Amirat Mohamed Benbouzid |
author_sort |
Omar Hazem Mohammed |
title |
Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm Strategies |
title_short |
Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm Strategies |
title_full |
Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm Strategies |
title_fullStr |
Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm Strategies |
title_full_unstemmed |
Economical Evaluation and Optimal Energy Management of a Stand-Alone Hybrid Energy System Handling in Genetic Algorithm Strategies |
title_sort |
economical evaluation and optimal energy management of a stand-alone hybrid energy system handling in genetic algorithm strategies |
publisher |
MDPI AG |
series |
Electronics |
issn |
2079-9292 |
publishDate |
2018-10-01 |
description |
Hybrid renewable energy systems are a promising technology for clean and sustainable development. In this paper, an intelligent algorithm, based on a genetic algorithm (GA), was developed and used to optimize the energy management and design of wind/PV/tidal/ storage battery model for a stand-alone hybrid system located in Brittany, France. This proposed optimization focuses on the economic analysis to reduce the total cost of hybrid system model. It suggests supplying the load demand under different climate condition during a 25-years interval, for different possible cases and solutions respecting many constraints. The proposed GA-based optimization approach achieved results clear highlight its practicality and applicability to any hybrid power system model, including optimal energy management, cost constraint, and high reliability. |
topic |
hybrid energy system genetic algorithm energy management optimization economical cost stand-alone system |
url |
http://www.mdpi.com/2079-9292/7/10/233 |
work_keys_str_mv |
AT omarhazemmohammed economicalevaluationandoptimalenergymanagementofastandalonehybridenergysystemhandlingingeneticalgorithmstrategies AT yassineamirat economicalevaluationandoptimalenergymanagementofastandalonehybridenergysystemhandlingingeneticalgorithmstrategies AT mohamedbenbouzid economicalevaluationandoptimalenergymanagementofastandalonehybridenergysystemhandlingingeneticalgorithmstrategies |
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1725081677199310848 |