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Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm

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  • Javed, Muhammad Shahzad
  • Song, Aotian
  • Ma, Tao

Abstract

Hybrid renewable energy systems are proving to be capable and emission-free sources of power generation, especially for off-grid/remote areas. This study develops a mathematical model to optimize a hybrid solar-wind energy system with storage for a remote island with genetic algorithm (GA). Four different cases are evaluated and the results are compared with that, the widely-used HOMER software, illustrating that GA method can output a more optimal system than HOMER in respect of cost and system reliability. Moreover, two systems with different wind turbine size are analyzed and their results present very little difference in terms of system cost and reliability, indicating that wind turbine size has little impact on the results. Furthermore, the simulated performance of the system and the effects of loss of power supply probability (LPSP), variation of load and renewable energy resources on the system cost are analyzed. Sensitivity analysis on some key parameters indicates that by considering a slight (1–5%) LPSP there is a significant decrease in initial capital cost (25–30%), operating cost (15–17%) as well as COE. It is evident from the sensitivity analysis that initially it is better to energize the off-grid/remote areas with small LPSP than no electricity.

Suggested Citation

  • Javed, Muhammad Shahzad & Song, Aotian & Ma, Tao, 2019. "Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm," Energy, Elsevier, vol. 176(C), pages 704-717.
    • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:704-717
    DOI: 10.1016/j.energy.2019.03.131
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