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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Main Authors: Omar Hazem Mohammed, Yassine Amirat, Mohamed Benbouzid
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Electronics
Subjects:
Online Access:http://www.mdpi.com/2079-9292/7/10/233
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spelling 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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