基于改进粒子群算法的含DG配网反时限过流保护定值优化方法
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通讯作者:

方愉冬(1977-),男,硕士,高级工程师,主要从事电力系统继电保护研究;E-mail:2587360@qq.com

中图分类号:

TM863

基金项目:

国网浙江省电力有限公司科技项目(5211JH1900M1)


An optimization method for setting value of inverse-time overcurrent protection in distribution network with DG based on MPSO
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    摘要:

    随着分布式电源接入配电网带来故障电流大小、潮流方向的改变,配网继电保护整定工作愈发艰巨。针对含 DG配网反时限过电流保护定值优化问题,考虑配网故障不确定因素、继电器固有属性与继电保护的“四性”要求, 在粒子群算法(PSO)更新过程中引入“全局历史平均最优解”与动态惯性权重相关概念,提出基于改进粒子群算法 (MPSO)的含 DG配网反时限过流保护定值优化方法。结论表明,MPSO 能有效避免定值求解陷入局部最优困境, 适用于含 DG配网反时限过电流保护定值优化问题。

    Abstract:

    As distributed power sources connected to the distribution network, the magnitude of the fault current and the direction of the power flow have been changed, and the relay protection setting of the distribution network has become more difficult. Aiming at the optimization problem of inverse time overcurrent protection setting for the distribution network containing DG, the uncertain factors of distribution network failure, the inherent properties of relays and the four requirements of relay protection is considered. The concept of "global historical average optimal solution" and dynamic inertia weight is introduced in the update process of particle swarm optimization. Finally a fixed value optimization method for inverse time overcurrent protection in the distribution network containing DG based on improved particle swarm optimization is proposed. The conclusion shows that the improved particle swarm algorithm can effectively prevent the fixed value solution from falling into the local optimal dilemma, and it is suitable for the fixed value optimization problem of the inverse time overcurrent protection in the distribution network containing DG.

    参考文献
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方愉冬,徐峰,李跃辉,等.基于改进粒子群算法的含DG配网反时限过流保护定值优化方法[J].电力科学与技术学报,2022,37(4):13-19.
Fang Yudong, Xu Feng, Li Yuehui, et al. An optimization method for setting value of inverse-time overcurrent protection in distribution network with DG based on MPSO[J]. Journal of Electric Power Science and Technology,2022,37(4):13-19.

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  • 在线发布日期: 2022-09-23
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