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The Thevenin equivalent based power flow method for integrated transmission and radial distribution networks
International Journal of Electrical Power & Energy Systems ( IF 5.0 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.ijepes.2020.106294
Jierui Yang , Zhihao Yun

Abstract With the large-scale integration of distributed generations into distribution networks (DNs), collaborative analysis for integrated transmission and distribution (T&D) networks is increasingly important. The fast collaborative power flow method with good convergence plays an important role in the real-time security analysis and off-line planning design for the T&D networks. The master–slave-splitting (MSS) method, a representative power flow method for integrated T&D networks, has more iterations and worse convergence when radial distribution networks (RDNs) have heavy loads, which hinders the analysis and decision-making for coordinated transmission and radial distribution (T&RD) networks. Therefore, this paper deduces theoretically the reason for the MSS method performance deterioration under heavy loads conditions in RDNs, and explore the improvement idea firstly. Then based on the improvement idea, the Thevenin equivalent based power flow (TEBPF) method for integrated T&RD networks is proposed. Known from the theoretical analysis, the TEBPF method can guarantee better convergence and less iterations in the heavily loaded RDNs compared with the MSS method. Simulation results demonstrate the effectiveness of the method proposed and the correctness of the deduction.

中文翻译:

基于戴维南等效的集成输电和径向配电网潮流方法

摘要 随着分布式电源大规模集成到配电网 (DN) 中,综合输配电 (T&D) 网络的协同分析变得越来越重要。具有良好收敛性的快速协同潮流方法在输配电网的实时安全分析和离线规划设计中具有重要作用。主从分裂(MSS)方法是集成输配电网潮流方法的代表,在径向配电网(RDN)负载较重时迭代次数多,收敛性差,阻碍了协调输电和电网的分析和决策。径向分布 (T&RD) 网络。所以,本文从理论上推导出了RDNs重载条件下MSS方法性能下降的原因,并首先探讨了改进思路。然后基于改进思想,提出了基于戴维南等效的潮流(TEBPF)方法用于集成输配电网。从理论分析可知,与MSS方法相比,TEBPF方法在重负载的RDNs中可以保证更好的收敛性和更少的迭代次数。仿真结果证明了所提方法的有效性和推导的正确性。与 MSS 方法相比,TEBPF 方法可以保证在重负载 RDN 中更好的收敛和更少的迭代。仿真结果证明了所提方法的有效性和推导的正确性。与 MSS 方法相比,TEBPF 方法可以保证在重负载 RDN 中更好的收敛和更少的迭代。仿真结果证明了所提方法的有效性和推导的正确性。
更新日期:2020-12-01
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