基于柔性自适应遗传算法的配电网电力恢复孤岛方法

Jiawei Zhang, X. Kang, Shiduo Jia, Yunzhang Yang, Chengpeng Xue
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引用次数: 0

摘要

目前,当配电网因故障与主网断开时,可以通过分布式代(dg)将供电恢复到周围可恢复的负荷。本文将配电网建模为树型,用0-1数组表示节点间的通断关系。采用灵活的自适应遗传算法确定孤岛电力恢复区域。在选择过程中,采用改进的指针随机抽样取代传统的轮盘抽样,并考虑突变的灵活性,以提高个体适应度。在电压、线路容量、网络连接和孤岛容量约束下,以负荷恢复效果、网损和开关动作成本为孤岛区域的最优目标函数。仿真结果表明,该方法能快速形成恢复方案,在电力系统中是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Islanding Method for Power Restoration of Distribution Network Based on Flexible Adaptive Genetic Algorithm
Nowadays, when the distribution network is disconnected from the main network due to faults, it can restore the power supply to the recoverable loads around by distributed generations (DGs). In this paper, the distribution network is modeled as a tree and 0-1 array is used to represent the on-off between nodes. A flexible adaptive genetic algorithm is used to determine the islanded power restoration area. In the selection process, the improved pointer random sampling is used to replace the traditional roulette wheel sampling, and the flexibility in mutation is considered in order to improve individual fitness. Load recovery effect, network loss, and switching action cost are taken as objective functions to island areas optimally under the constraints of voltage, line capacity, network connection, and islanding capacity. The simulation results show that the proposed method can quickly form a recovery scheme and is feasible in power systems.
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