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基于自适应灰狼算法的有源配电网故障恢复策略

Fault Recovery Strategy of Active Distribution Network Based on Adaptive Gray Wolf Algorithm

  • 摘要: 为进一步提高有源配电网供电可靠性,针对有源配电网故障恢复中传统算法存在的早熟、计算量大、计算效率低等问题,提出基于自适应灰狼算法的有源配电网故障恢复策略。该策略通过引入自适应收敛因子,解决陷入局部最优的问题,扩大种群多样性,提高全局收敛能力。在IEEE 33节点算例验证下,证明该策略适用于有源配电网故障恢复模型,可有效改善节点电压,降低有功网损。

     

    Abstract: In order to further improve the reliability of active distribution network, the fault recovery strategy of active distribution network based on adaptive gray wolf algorithm is proposed, aiming at the problems of prematurity, large computation and low computation efficiency of traditional fault recovery algorithms. By introducing an adaptive convergence factor, this method solves the problem of local optimization, enlarges population diversity, and improves global convergence ability. It is proved that the proposed method is suitable for the fault recovery model of active distribution network, and can effectively improve the node voltage and reduce the active power loss.

     

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