一种新的混合模糊动态速度反馈粒子群算法求解非凸经济调度问题

E. Muneender, D. Vinodkumar
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引用次数: 2

摘要

提出了一种新的混合模糊动态速度反馈粒子群优化算法(HFDVF-PSO),用于解决考虑阀点效应和多种燃料选择的非光滑成本函数经济调度问题。在hfdvf -粒子群算法中,利用粒子平均速度的绝对值作为模糊推理系统的反馈,对粒子群的惯性权值进行动态非线性调整,以更好地平衡粒子群的全局搜索能力和局部搜索能力。在标准的10单元测试系统上对该方法的性能进行了测试,并与传统的粒子群算法和文献报道的方法进行了比较。仿真结果表明,HFDVF-PSO方法优于传统的粒子群算法和已有的进化算法(EA)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new Hybrid Fuzzy Dynamic Velocity Feedback PSO for non-convex economic dispatch problem
This paper proposes a new Hybrid Fuzzy Dynamic Velocity Feedback Particle Swarm Optimization (HFDVF-PSO) for solving Economic Dispatch (ED) problem with non-smooth cost functions considering valve-point effects and multiple fuel options. In the proposed HFDVF-PSO method, the inertia weight is dynamically and nonlinearly adjusted to obtain better balance between global and local search abilities of the PSO using the absolute value of the average velocity of the particles as a feedback to the fuzzy inference system. The performance of the proposed method is tested on standard 10-unit test system and is compared with the conventional PSO method and the methods reported in literature. The simulation results reveal that the proposed HFDVF-PSO method out performs the conventional PSO and other Evolutionary Algorithms (EA) reported in literature.
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