Sizing of Hybrid PV/Battery/Wind/Diesel Microgrid System Using an Improved Decomposition Multi-Objective Evolutionary Algorithm Considering Uncertainties and Battery Degradation

被引：10

作者：

Bouchekara, Houssem R. E. H. ^{[1
]}

Sha'aban, Yusuf A. ^{[1
]}

Shahriar, Mohammad S. ^{[1
]}

Abdullah, Saad M. ^{[2
]}

Ramli, Makbul A. ^{[3
]}

机构：

[1] Univ Hafr Al Batin, Dept Elect Engn, Hafar al Batin 31991, Saudi Arabia

[2] Islamic Univ Technol, Dept Elect & Elect Engn, Gazipur 1704, Bangladesh

[3] King Abdulaziz Univ, Dept Elect & Comp Engn, Jeddah 21589, Saudi Arabia

来源：

SUSTAINABILITY | 2023年 / 15卷 / 14期

关键词：

wind energy hybrid PV system; decomposition-based multi-objective EA; load uncertainty; battery degradation; ENERGY SUPPLY OPTIONS; SOLAR-WIND SYSTEM; RENEWABLE ENERGY; SCALARIZING FUNCTIONS; FEASIBILITY ANALYSIS; OPTIMUM DESIGN; OPTIMIZATION; STORAGE; MANAGEMENT; METHODOLOGY;

D O I：

10.3390/su151411073

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

In this paper, a small-scale PV/Wind/Diesel Hybrid Microgrid System (HMS) for the city of Yanbu, Saudi Arabia is optimally designed, considering the uncertainties of renewable energy resources and battery degradation. The optimization problem is formulated as a multi-objective one with two objective functions: the Loss of Power Supply Probability (LPSP) and the Cost of Electricity (COE). An Improved Decomposition Multi-Objective Evolutionary Algorithm (IMOEAD) is proposed and applied to solve this problem. In this approach, different decomposition schemes are combined effectively to achieve better results than the classical MOEA/D approach. Twelve case studies are investigated based on different scenarios and different numbers of houses (5 and 10 houses). Each time, the suggested approach produced a set of solutions that formed a Pareto front (PF). Considering a variety of parameters, the optimal compromise option can be selected by the designer from the PF.

引用

页数：38

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