王鲁明, 程静, 王维庆. 基于改进灰狼算法的含分布式电源配电网重构研究[J]. 现代电力, 2022, 39(1): 56-63. DOI: 10.19725/j.cnki.1007-2322.2021.0040
引用本文: 王鲁明, 程静, 王维庆. 基于改进灰狼算法的含分布式电源配电网重构研究[J]. 现代电力, 2022, 39(1): 56-63. DOI: 10.19725/j.cnki.1007-2322.2021.0040
WANG Luming, CHENG Jing, WANG Weiqing. Research on Distribution Network Reconfiguration with Distributed Generation Based on Improved Grey Wolf Optimizer[J]. Modern Electric Power, 2022, 39(1): 56-63. DOI: 10.19725/j.cnki.1007-2322.2021.0040
Citation: WANG Luming, CHENG Jing, WANG Weiqing. Research on Distribution Network Reconfiguration with Distributed Generation Based on Improved Grey Wolf Optimizer[J]. Modern Electric Power, 2022, 39(1): 56-63. DOI: 10.19725/j.cnki.1007-2322.2021.0040

基于改进灰狼算法的含分布式电源配电网重构研究

Research on Distribution Network Reconfiguration with Distributed Generation Based on Improved Grey Wolf Optimizer

  • 摘要: 使用基本环矩阵编码的智能优化算法在处理配电网重构问题中,通常使用无序的解空间,解空间中局部峰值较多,使得智能优化算法难以发挥自身优势,耗时严重且难以寻找到最优解。针对以上问题,提出一种有序环网编码方式,并基于改进灰狼算法求解含分布式电源(distributed generation,DG)配电网的重构方法。首先,将基本环矩阵的元素按支路顺序排列,再利用启发式规则初步寻找较优解,并将其与初始狼群中的Alpha狼比较,取其较优解作为新的Alpha狼;然后,引入Gamma狼,用于环绕Alpha狼寻优,使狼群保证种群多样性的同时,提高其局部搜索能力;最后,使用改进灰狼算法求解修改后IEEE 33配电网和Taipower 84配电系统,有效地降低系统网损并且提高了系统内的最低电压。经验证,该方法有效可行、算法简单、快速性高,得到的结果更优。

     

    Abstract: During the process of distribution network reconfiguration by intelligent optimization algorithm using basic ring matrix coding the disordered solution space is usually utilized, however there are many local peaks in the solution space so that it makes the intelligent optimization algorithm hard to full play its own advantages, besides it consumes too much time and it is difficult to search out the optimal solution. In allusion to above-mentioned defects, an ordered ring network coding scheme was proposed and the improved gray wolf algorithm was used to search out the method to reconfigure distribution network containing distributed generation (DG). Firstly, the elements of the basic ring matrix wee arranged according to the order of branches, and then the heuristic rules were used to preliminary find the better solution and this better solution was compared with the alpha wolf in the initial wolf pack, and the better solution was taken as the new alpha wolf. Secondly, the gamma wolf was led in to surround the alpha wolf for optimization to ensure the population diversity of the wolf pack meanwhile to improve its local searching ability. Finally, the improved grey wolf algorithm was used to conduct the simulation in the modified IEEE 33-bus distribution network and the Taipower84 distribution system. Simulation results show that using the proposed reconfiguration method the network loss is effectively reduced and the lowest voltage in the system is improved, thus, the proposed reconfiguration method is effective and feasible, the algorithm is simple and fast, and the obtained results are better.

     

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