基于模糊机制的连续遗传算法的非凸代价函数多目标优化

S. Parihar, Nitin Malik
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引用次数: 6

摘要

本文采用基于模糊机制的连续遗传算法,对考虑系统约束的电力系统各发电机组发电成本分配的非凸多目标优化问题进行了研究。同时考虑经济负荷调度和环境调度,优化发电系统总成本。在多目标问题中考虑了阀点负荷效应,得到了非凸环境经济调度问题。将这一双目标问题转化为考虑价格惩罚因素的单目标问题。该方法给出了现有Pareto最优解集中排名最高的最优折衷解。在三个和六个发电机组的两个测试系统(IEEE-30总线系统)上验证了该方法的性能。为了证明该方法的优势,将得到的结果与最近发表的结果进行了进一步的比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-objective optimization with non-convex cost functions using fuzzy mechanism based continuous genetic algorithm
In this paper, a fuzzy mechanism based continuous genetic algorithm is employed to optimize the non-convex multi-objective problem for allocating power generation cost to all the generating units of the electrical system considering system constraints. Here, the total system cost for generation is optimized by considering Economic load dispatch and Environmental Dispatch simultaneously. The valve point loading effect is also considered in the proposed multi-objective problem to obtain Non-Convex Environmental Economic Dispatch problem. This biobjective problem is transformed as single objective problem considering price penalty factor. The proposed technique gives the best compromised solution with the highest rank out of the existing Pareto optimal solution set. The performance of the proposed method is confirmed and validated on two test systems having three and six generating units (IEEE-30 bus system). To show the dominance of the method the obtained results are further compared with the recently published result.
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