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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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Title: Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm.
Authors: Javed, Muhammad Shahzad1 (AUTHOR), Song, Aotian2 (AUTHOR), Ma, Tao1,2 (AUTHOR) tao.ma@connect.polyu.hk
Source: Energy. Jun2019, Vol. 176, p704-717. 14p.
Subjects: Genetic algorithms, Hybrid systems, Renewable energy sources, Capital costs, Power resources, Wind turbines
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. • Techno-economic study of a hybrid solar-wind-battery system is conducted. • Genetic algorithm offer better results than HOMER in terms of cost and reliability. • Wind turbine size has little impact on system cost. • Considering a slight LPSP (1%) brings considerable decrease in COE value (13%–16%). • Effect of LPSP on COE remains same after considering the different load demands. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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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. • Techno-economic study of a hybrid solar-wind-battery system is conducted. • Genetic algorithm offer better results than HOMER in terms of cost and reliability. • Wind turbine size has little impact on system cost. • Considering a slight LPSP (1%) brings considerable decrease in COE value (13%–16%). • Effect of LPSP on COE remains same after considering the different load demands. [ABSTRACT FROM AUTHOR]
ISSN:03605442
DOI:10.1016/j.energy.2019.03.131