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Power loss reduction of distribution systems using BFO based optimal reconfiguration along with DG and shunt capacitor placement simultaneously in fuzzy framework 被引量:1

Power loss reduction of distribution systems using BFO based optimal reconfiguration along with DG and shunt capacitor placement simultaneously in fuzzy framework
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摘要 In distribution systems,network reconfiguration and capacitor placement are commonly used to diminish power losses and keep voltage profiles within acceptable limits.Moreover,the problem of DG allocation and sizing is great important.In this work,a combination of a fuzzy multi-objective approach and bacterial foraging optimization(BFO) as a meta-heuristic algorithm is used to solve the simultaneous reconfiguration and optimal sizing of DGs and shunt capacitors in a distribution system.Each objective is transferred into fuzzy domain using its membership function.Then,the overall fuzzy satisfaction function is formed and considered a fitness function inasmuch as the value of this function has to be maximized to gain the optimal solution.The numerical results show that the presented algorithm improves the performance much more than other meta-heuristic algorithms.Simulation results found that simultaneous reconfiguration with DG and shunt capacitors allocation(case 5) has 77.41%,42.15%,and 56.14%improvements in power loss reduction,load balancing,and voltage profile indices,respectively in 33-bus test system.This result found 87.27%,35.82%,and 54.34%improvements of mentioned indices respectively for 69-bus system. In distribution systems, network reconfiguration and capacitor placement are commonly used to diminish power losses and keep voltage profiles within acceptable limits. Moreover, the problem of DG allocation and sizing is great important. In this work, a combination of a fuzzy multi-objective approach and bacterial foraging optimization (BFO) as a meta-heuristic algorithm is used to solve the simultaneous reconfiguration and optimal sizing of DGs and shunt capacitors in a distribution system. Each objective is transferred into fuzzy domain using its membership function. Then, the overall fuzzy satisfaction function is formed and considered a fitness function inasmuch as the value of this function has to be maximized to gain the optimal solution. The numerical results show that the presented algorithm improves the performance much more than other meta-heuristic algorithms. Simulation results found that simultaneous reconfiguration with DG and shunt capacitors allocation (case 5) has 77.41%, 42.15%, and 56.14% improvements in power loss reduction, load balancing, and voltage profile indices, respectively in 33-bus test system. This result found 87.27%, 35.82%, and 54.34% improvements of mentioned indices respectively for 69-bus system.
出处 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第1期90-103,共14页 中南大学学报(英文版)
关键词 network reconfiguration distributed generation (DG) capacitor banks fuzzy framework bacterial foragingoptimization 并联电容器 模糊多目标 功率损耗 配电系统 网络重构 位置 启发式搜索算法 模糊满意度函数
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