基于变加速度系数的粒子群算法求解非凸经济负荷调度问题

V. K. Jadoun, K. R. Niazi, A. Swarnkar, N. Gupta
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引用次数: 4

摘要

提出了一种基于变加速度系数的粒子群优化(VACPSO)方法,在考虑禁止操作区域和阀点效应的情况下,求解燃油成本最小的经济负荷调度问题。提出的粒子群优化算法是对传统粒子群优化算法的改进。在拟议的VACPSO中提出了三个修改建议。首先,粒子的认知行为受到最佳和最差经验的影响。其次,提出了三个加速度系数,而不是传统粒子群中的两个加速度系数。第三,加速度系数是可变的,而不是仅仅赋予它们一个固定的值。这些建议的修改有助于以更少的计算负担更好地探索搜索空间。该方法在两个标准的发电系统上进行了测试。应用结果和与其他方法的比较表明,该方法以较少的计算时间提供了高质量的解。
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Variable Acceleration Coefficient-based Particle Swarm Optimization for Non-Convex Economic load dispatch problem
This paper presents Variable Acceleration Coefficient-based Particle Swarm Optimization (VACPSO) method to solve the economic load dispatch for minimizing fuel cost while considering prohibited operating zones and valve point effect. The proposed VACPSO is a modified version of the conventional Particle Swarm Optimization (PSO). Three modifications are suggested in the proposed VACPSO. First, the cognitive behavior of particle is influenced by best and worst experience. Second, three acceleration coefficients, instead of two as in the conventional PSO, are suggested. Third, the acceleration coefficients are made variable rather than assigning them merely a fixed value. These suggested modifications facilitate better exploration of the search space with less computational burden. The proposed method is tested on two standard generating systems available in the literature. The application results and comparison with other recent approaches show that the proposed approach provides good quality solution with less computational time.
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