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Multi-objective optimization of stand-alone hybrid PV-wind-diesel-battery system using improved fruit fly optimization algorithm

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Abstract

Stand-alone hybrid photovoltaic(PV)-wind-diesel-battery system is becoming an appropriate choice of power supply system for remote areas far from the power grid. However, the sizing optimization of the stand-alone hybrid PV-wind-diesel-battery system is difficult because of the system’s complexity. In this paper, a novel improved fruit fly optimization algorithm-based multi-objective optimization method is proposed for the optimization design of this system. Here, the objectives to be minimized are the annual total cost and the pollutant emission of the system. The obtained solutions of the best Pareto front can help decision-makers to choose the prior one. The simulation conducted in this paper is based on real data collected from Dongao Island. Simulation results show the excellent properties of the proposed optimization method and demonstrate the feasibility of the stand-alone hybrid PV-wind-diesel-battery system in Dongao Island.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (No.61104088) and Hunan Provincial Natural Science Foundation of China (No.2015JJ3053).

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Authors and Affiliations

  1. College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China

    Jingyi Zhao & Xiaofang Yuan

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  1. Jingyi Zhao
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  2. Xiaofang Yuan
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Correspondence to Xiaofang Yuan.

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Communicated by V. Loia.

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Zhao, J., Yuan, X. Multi-objective optimization of stand-alone hybrid PV-wind-diesel-battery system using improved fruit fly optimization algorithm. Soft Comput 20, 2841–2853 (2016). https://doi.org/10.1007/s00500-015-1685-6

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  • DOI: https://doi.org/10.1007/s00500-015-1685-6

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