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A dynamic MOPSO algorithm for multiobjective optimal design of hybrid renewable energy systems.

Authors :
Sharafi, Masoud
ElMekkawy, Tarek Y.
Source :
International Journal of Energy Research; Dec2014, Vol. 38 Issue 15, p1949-1963, 15p, 3 Diagrams, 4 Charts, 10 Graphs
Publication Year :
2014

Abstract

SUMMARY In this paper, a dynamic multiobjective particle swarm optimization (DMOPSO) method is presented for the optimal design of hybrid renewable energy systems (HRESs). The main goal of the design is to minimize simultaneously the total net present cost (NPC) of the system, unmet load, and fuel emission. A DMOPSO-simulation based approach has been used to approximate a worthy Pareto front (PF) to help decision makers in selecting an optimal configuration for an HRES. The proposed method is examined for a case study including wind turbines, photovoltaic (PV) panels, diesel generators, batteries, fuel cells, electrolyzer, and hydrogen tanks. Well-known metrics are used to evaluate the generated PF. The average spacing and diversification metrics obtained by the proposed approach are 1386 and 4656, respectively. Additionally, the set coverage metric value shows that at least 67% of Pareto solutions obtained by DMOPSO dominate the solutions resulted by other reported algorithms. By using a sensitivity analysis for the case study, it is found that if the PV panel and wind turbine capital cost are decreased by 50%, the total NPC of the system would be decreased by 18.8 and 3.7%, respectively. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0363907X
Volume :
38
Issue :
15
Database :
Complementary Index
Journal :
International Journal of Energy Research
Publication Type :
Academic Journal
Accession number :
99368624
Full Text :
https://doi.org/10.1002/er.3202