Probability Analysis and Application of Voltage Stability Index of Distribution Network Based on Unscented Transformation

被引：0
|
作者：
Xu Y. [1 ]
Dong S. [1 ]
Mao H. [2 ]
Song Y. [3 ]
机构：
[1] Zhejiang University, Hangzhou
[2] State Grid Zhejiang Electric Power Co., Ltd., Hangzhou
[3] State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering, University of Macau, Macau
来源：
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2020年 / 40卷
关键词：
Distributed generation (DG); Distribution network; Probabilistic analysis; Randomness; Unscented transformation; Voltage stability index;
D O I：
10.13334/j.0258-8013.pcsee.200625
中图分类号：
学科分类号：
摘要：
A probabilistic analysis method of voltage stability index was proposed for the distribution network with intermittent distributed power, which could analyze the voltage stability of the distribution network reasonably and help to analyze the weak nodes of the system. First, considering the randomness of load power and renewable power output, a probability model of the distribution network was established; then, a probability model of the voltage stability index of the distribution network was established, and the probabilistic characteristics of voltage stability were analyzed by means and standard deviations of the voltage stability index. The probabilistic analysis problem was transformed into a deterministic problem for fast solution by the unscented transformation method. Taking the distribution network connected to the wind turbine as an example, the actual wind speed data of Northwest China and the IEEE 33 node distribution network system were used to analyze the examples. Based on the calculation results of Monte Carlo simulation, the accuracy and efficiency of this method were verified. Finally, the voltage stability of the distribution network was improved with the proposed voltage stability index probability analysis method. It was showed that the optimal configuration of energy storage could be guided correctly to improve the voltage stability of the distribution network by this method. © 2020 Chin. Soc. for Elec. Eng.
引用
收藏
页码：47 / 55
页数：8
相关论文
共 20 条
  • [1] Zhang Xi, Zhang Ning, Long Fei, Research of the impacts on static voltage stability of distribution networks with distributed generation from different aspects, Power System Protection and Control, 45, 6, pp. 120-125, (2017)
  • [2] Wu Xiaomeng, Liu Jian, Bi Pengxiang, Research on voltage stability of distribution networks, Power System Technology, 30, 24, pp. 31-35, (2006)
  • [3] Xu Lin, Lu Jiping, Wang Yang, Et al., Research on nodal voltage stability index of power system, Power System Technology, 34, 3, pp. 26-30, (2010)
  • [4] Zhang Qian, Liao Qingfen, Tang Fei, Et al., Steady state voltage stability assessment method of distribution network considering interconnection of distributed generators, Automation of Electric Power Systems, 39, 15, pp. 42-48, (2015)
  • [5] Gao Feng, Wang Yanwen, Guo Lin, Et al., Load-nodal on-line voltage stability index for power system, Electric Power Construction, 37, 2, pp. 69-77, (2016)
  • [6] Li Tiyin, Han Yongqiang, Hu Xiaoqin, Et al., Characteristics of static voltage stability for distributed generation integrated into power system and its impacts analysis, Power System Protection and Control, 42, 12, pp. 8-13, (2014)
  • [7] Dai Jinglong, Wei Hua, Bao Haibo, Et al., Stochastic power flow calculation based on unscented transform for power system with distributed generations, Electric Power Automation Equipment, 36, 3, pp. 86-93, (2016)
  • [8] Julier S J, Uhlmann J K., Unscented filtering and nonlinear estimation, Proceedings of the IEEE, 92, 3, pp. 401-422, (2004)
  • [9] Aien M, Fotuhi-Firuzabad M, Aminifar F., Probabilistic load flow in correlated uncertain environment using unscented transformation, IEEE Transactions on Power Systems, 27, 4, pp. 2233-2241, (2012)
  • [10] Han Xiao, Zhou Ming, Li Gengyin, Stochastic optimal dispatching of active distribution networks based on stochastic power flow modeling using unscented transformation, Power System Protection and Control, 46, 3, pp. 9-17, (2018)
12