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A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks

机译:智能配电网中考虑数据不确定性的网络重构方法

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This work presents a method for distribution network reconfiguration with the simultaneous consideration of distributed generation (DG) allocation. The uncertainties of load fluctuation before the network reconfiguration are also considered. Three optimal objectives, including minimal line loss cost, minimum Expected Energy Not Supplied, and minimum switch operation cost, are investigated. The multi-objective optimization problem is further transformed into a single-objective optimization problem by utilizing weighting factors. The proposed network reconfiguration method includes two periods. The first period is to create a feasible topology network by using binary particle swarm optimization (BPSO). Then the DG allocation problem is solved by utilizing sensitivity analysis and a Harmony Search algorithm (HSA). In the meanwhile, interval analysis is applied to deal with the uncertainties of load and devices parameters. Test cases are studied using the standard IEEE 33-bus and PG&E 69-bus systems. Different scenarios and comparisons are analyzed in the experiments. The results show the applicability of the proposed method. The performance analysis of the proposed method is also investigated. The computational results indicate that the proposed network reconfiguration algorithm is feasible.
机译:这项工作提出了一种同时考虑分布式发电(DG)分配的配电网络重新配置方法。还考虑了网络重新配置之前负载波动的不确定性。研究了三个最佳目标,包括最小的线路损耗成本,最小的未提供预期能量和最小的开关操作成本。利用加权因子将多目标优化问题进一步转化为单目标优化问题。所提出的网络重配置方法包括两个周期。第一个阶段是通过使用二进制粒子群优化(BPSO)创建可行的拓扑网络。然后利用灵敏度分析和和声搜索算法(HSA)解决DG分配问题。同时,采用区间分析法处理负荷和设备参数的不确定性。使用标准的IEEE 33总线和PG&E 69总线系统研究测试用例。在实验中分析了不同的场景和比较。结果表明了该方法的适用性。还研究了该方法的性能分析。计算结果表明,该算法是可行的。

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