Optimal power flow solutions to power systems with wind energy using a highly effective meta-heuristic algorithm

T. Le, X. Le, N.N.P Huynh, A. Doan, T. V. Dinh, M. Q. Duong
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引用次数: 2

Abstract

This paper implements two novel meta-heuristic algorithms, including the Coati optimization algorithm (COA) and War strategy optimization (WSO) for determining the optimal solutions to the optimal power flow problem incorporating the use of wind turbines. Two objective functions are considered in this study, including minimizing the entire electricity generation cost (EEGC) with the value point effect and minimizing the voltage fluctuation index (VFI). IEEE 30-bus system is chosen to conduct the whole study and validate the efficiency of the two applied methods. Furthermore, DFIG wind turbines are used in grids with varying power output and power factor ranges. The comparison of the results obtained from the two methods in all case studies reveals that WSO is vastly superior to COA in almost all aspects. In addition, the positive contributions of wind turbines to the EEGE and VFI while they are properly placed in the grid are also clarified by using WSO. As a result, WSO is acknowledged as a highly effective search method, and we strongly recommend using WSO for dealing with such OPF problems considering the presence of renewable energy sources.
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利用高效元启发式算法求解风能电力系统的最优潮流
本文实现了两种新的元启发式算法,包括Coati优化算法(COA)和战争策略优化(WSO),用于确定结合使用风力涡轮机的最优潮流问题的最优解。本研究考虑了两个目标函数,包括利用值点效应最小化整个发电成本(EEGC)和最小化电压波动指数(VFI)。选择IEEE 30总线系统进行整个研究,并验证了两种应用方法的有效性。此外,DFIG风力涡轮机用于具有不同功率输出和功率因数范围的电网中。两种方法在所有案例研究中获得的结果的比较表明,WSO在几乎所有方面都远远优于COA。此外,还通过使用WSO阐明了风力涡轮机在正确放置在电网中时对EEGE和VFI的积极贡献。因此,WSO被公认为一种高效的搜索方法,考虑到可再生能源的存在,我们强烈建议使用WSO来处理此类OPF问题。
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CiteScore
4.50
自引率
16.00%
发文量
83
审稿时长
8 weeks
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