应用鲸鱼优化算法确定电网最大负荷极限

Suvabrata Mukherjee, P. Roy
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引用次数: 0

摘要

鲸鱼优化算法(Whale optimization algorithm, WOA)是一种简单、高效的元启发式算法,在综合优化的情况下具有出色的执行力。WOA采用气泡网狩猎方法,并模仿座头鲸的社会性质来获得最佳候选解决方案。在本文中,所提出的算法被用于确定电网的最大负载性极限(通常也称为电压稳定性)。为了评估实现预期输出的鲁棒性和高效性能,该算法在MATPOWER 30总线和IEEE 118总线测试系统上隐含。为了进一步评价,将WOA隐含的结果与差分进化算法(DE)、多智能体混合粒子群算法(MAHPSO)和混合粒子群算法(DEPSO)等替代算法进行了比较。经过20多次独立试验,结果清楚地表明,WOA通过在更短的时间内提供更大的加载点,在解决最大可加载性问题方面提供了更高的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determination of maximum loadability limit of power networks applying whale optimization algorithm
Whale optimization algorithm (WOA), is an uncomplicated and efficient metaheuristic algorithm which provides exceptional execution in case of comprehensive optimization. WOA employs bubble-net hunting approach and it mimics the social nature of humpback whales to get the best candidate solution. In the present article the proposed algorithm has been implied for determining the maximum loadability limit (also commonly referred to as voltage stability) of power network. To assess the robustness and efficient performance in attaining the desired output, the algorithm is implied on MATPOWER 30-bus and IEEE 118-bus test systems. For further evaluation, the results obtained by the implication of WOA has been compared with alternative algorithms such as differential evolution algorithm (DE), multi agent hybrid PSO (MAHPSO) and hybridized DE and PSO (DEPSO). The results, been considered over 20 independent trials, clearly highlights that WOA provides higher efficiency in solving the maximum loadability problem by providing large loading point in much lesser time.
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