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Authors: Mustapha Hatti and Hachemi Rahmani

Affiliation: Unité de Développement des Equipements Solaires, UDES, Centre de Développement des Energies Renouvelables and CDER, Algeria

ISBN: 978-989-758-105-2

Keyword(s): PV-PEMFC Hybrid System, Fuzzy Logic Controller, Genetic Algorithm, Management, Hydrogen.

Related Ontology Subjects/Areas/Topics: Energy and Economy ; Energy Management Systems (EMS) ; Energy-Aware Systems and Technologies ; Renewable Energy Resources

Abstract: European cities have established programs integrating the energy, transport and ICT sectors in order to deliver more efficient services for their populations. The paper tackles the study of feasibility to implement fuzzy logic control into an energetic hybrid system and to optimize the membership functions of the fuzzy logic controller for the Photovoltaic-Proton Exchange Membrane Fuel Cell hybrid system using genetic algorithm (GA). The paper deals with a fuzzy logic control strategy objective to produce electrical energy according to the demand, prone to the constraints and the dynamics of the physical load and intermittence of the energetic resource, by distributing the energy demand between the photovoltaic field and the Proton Exchange Membrane Fuel Cell system. Photovoltaic-Proton Exchange Membrane Fuel Cell is described in detail as well as system configuration and components' parameters. The second section devotes to demonstrating the design process of fuzzy logic control for Photovoltaic-Proton Exchange Membrane Fuel Cell hybrid System. Finally, the optimal control problem is addressed and genetic algorithm is introduced to help find a set of optimum parameters in the fuzzy logic controller, best results are obtained and good optimization of the hybrid system is highlighted. (More)

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Paper citation in several formats:
Hatti, M. and Rahmani, H. (2015). Fine-tuning Genetic Algorithm for Photovoltaic-Proton Exchange Membrane Fuel Cell Hybrid System Optimization.In Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-105-2, pages 234-240. DOI: 10.5220/0005451702340240

@conference{smartgreens15,
author={Mustapha Hatti. and Hachemi Rahmani.},
title={Fine-tuning Genetic Algorithm for Photovoltaic-Proton Exchange Membrane Fuel Cell Hybrid System Optimization},
booktitle={Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2015},
pages={234-240},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005451702340240},
isbn={978-989-758-105-2},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Fine-tuning Genetic Algorithm for Photovoltaic-Proton Exchange Membrane Fuel Cell Hybrid System Optimization
SN - 978-989-758-105-2
AU - Hatti, M.
AU - Rahmani, H.
PY - 2015
SP - 234
EP - 240
DO - 10.5220/0005451702340240

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