Multi-objective design of PV–wind–diesel–hydrogen–battery systems

This paper presents, for the first time, a triple multi-objective design of isolated hybrid systems minimizing, simultaneously, the total cost throughout the useful life of the installation, pollutant emissions (CO 2) and unmet load. For this task, a multi-objective evolutionary algorithm (MOEA) and...

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Bibliographic Details
Published in:Renewable energy 2008-12, Vol.33 (12), p.2559-2572
Main Authors: Dufo-López, Rodolfo, Bernal-Agustín, José L.
Format: Article
Language:English
Subjects:
Applied sciences
Economic data
Electric energy
Energy
Energy economics
Exact sciences and technology
General, economic and professional studies
Genetic algorithms
Hybrid systems
Methodology. Modelling
Multi-objective design
Multi-objective evolutionary algorithms
Natural energy
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Summary:This paper presents, for the first time, a triple multi-objective design of isolated hybrid systems minimizing, simultaneously, the total cost throughout the useful life of the installation, pollutant emissions (CO 2) and unmet load. For this task, a multi-objective evolutionary algorithm (MOEA) and a genetic algorithm (GA) have been used in order to find the best combination of components of the hybrid system and control strategies. As an example of application, a complex PV–wind–diesel–hydrogen–battery system has been designed, obtaining a set of possible solutions (Pareto Set). The results achieved demonstrate the practical utility of the developed design method.
ISSN:0960-1481
1879-0682
DOI:10.1016/j.renene.2008.02.027