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Multiple-objective dg optimal sizing in distribution system using an improved PSO algorithm

机译:改进PSO算法的配电系统多目标dg优化大小。

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An improved particle swarm optimization (PSO) algorithm has been presented in optimal sizing of multiple DG units in this paper. Firstly, multiple-objective functions have been formed with the consideration of minimum line loss, minimum voltage deviation and maximal voltage stability margin. Through fuzzy set theory, the multiple-objective optimization problem has been transformed to single objective comprehensive optimization with membership degree. The global particle swarm optimization algorithm dominates the search direction and works out the resu in the meanwhile, the inertia weight w, the cognitive and social parameters are updated in adaptive mode. And multi-initialization method is utilized to refresh the particle populations and increase its diversity. Several experiments have been made based on the IEEE 33-bus, actual 292-, 588- and 1180-bus test cases with the consideration of multiple DG units. The computational result and comparison indicate the proposed algorithm for optimal sizing of DG in distribution system is feasible and effective.
机译:本文提出了一种改进的粒子群算法(PSO)来优化多个DG机组的尺寸。首先,考虑到最小的线损,最小的电压偏差和最大的电压稳定裕度,形成了多目标函数。通过模糊集理论,将多目标优化问题转化为隶属度的单目标综合优化问题。全局粒子群优化算法主导搜索方向并得出结果。同时,以自适应模式更新惯性权重w,认知和社会参数。并采用多重初始化的方法来刷新粒子种群并增加其多样性。基于IEEE 33总线,实际292、588和1180总线测试用例,并考虑了多个DG单元,进行了一些实验。计算结果和比较结果表明,所提出的配电网分布式发电最佳规模算法是可行,有效的。

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