基于动作时限曲线拟合思想的含DG型配电网后备保护新方法
New Method for Backup Protection in Distribution Networks With DG Based on Idea of Action Time Limit Curve Fitting
黄景光 1赵珩 1李浙栋 1张宇鹏 2梅诺男 1孙佳航 1张员宁 3翁汉琍1
作者信息
- 1. 三峡大学电气与新能源学院,湖北省宜昌市 443002
- 2. 国网浙江省电力有限公司绍兴供电公司,浙江省绍兴市 312000
- 3. 国网湖北省电力有限公司超高压公司,湖北省武汉市 430050
- 折叠
摘要
分布式电源(distributed generation,DG)的接入可能会改变电力系统的短路电流特性,从而影响到反时限过流保护的选择性和配合关系.为此,提出一种基于动作时限曲线拟合思想的含DG型配电网后备保护新方法.从配电网主保护和后备保护的动作时间差入手,建立曲线拟合模型,并运用梯度下降法对反时限过流保护的动作时限曲线进行优化.通过在优化整定计算中考虑保护的选择性以及DG接入所带来的影响,使优化参数适用于配电网中各分段位置.然后,在配电网中设置两相、三相短路故障,并根据故障位置、类型进行整定参数再调整,最终得到参数的全局最优解.基于PSCAD/EMTDC仿真软件进行仿真分析,验证了所提方法的有效性和实用性.
Abstract
The integration of distributed generation(DG)may alter the short-circuit current characteristics of the power system,thereby affecting the selectivity and coordination of the inverse time overcurrent protection.Therefore,this article proposes a new method for backup protection in distribution networks with DG based on the idea of action time limit curve fitting.Starting from the action time difference between the main protection and the backup protection in the distribution network,a curve fitting model is established,and the gradient descent method is used to optimize the action time curve of the inverse time overcurrent protection.By considering the selectivity of the protection and the impact of DG connection in the optimization setting calculation,the optimization parameters are applied to every segment position in the distribution network.Then,by setting some two-phase and three-phase short-circuit faults in the distribution network,the parameters are adjusted based on the fault locations and types,and ultimately obtaining the global optimal solution of the parameters.Based on the PSCAD/EMTDC simulation software,simulation analysis is conducted to verify the effectiveness and practicality of the proposed method.
关键词
反时限过流保护/分布式电源/梯度下降算法/曲线拟合/速动性/选择性Key words
inverse time overcurrent protection/distributed generation/gradient descent algorithm/curve fitting/rapidity/selectivity引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据