Stochastic Estimation Method of Voltage Sags in Complex Distribution Systems
Li Gengyin, Yang Xiaodong, Zhou Ming
Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control Under Ministry of Education North China Electric Power University Beijing 102206 China
Abstract：With the development of new transmission and distribution techniques and rising requirement of modern consumers for better power quality, the voltage sag analysis and assessment has become an important research subject in power quality presently. In this paper the reconfiguration system (RCS)method, which derives from the direct method, is proposed for the voltage sag estimation in complex distribution systems. The coefficients of the voltage sag expression are calculated directly from the power flow calculation of reconfiguration system with RCS method. The areas of vulnerability and expected sag frequency (ESF) indices of sensitive load under three-phase short-circuit fault, single line-to-ground fault, double line-to-ground fault and line-to-line fault are calculated respectively. It is proved by IEEE 30-bus system that the RCS method is suitable for stochastic estimation of voltage sag in large distribution systems.
李庚银, 杨晓东, 周明. 复杂配电网的电压暂降随机预估方法[J]. 电工技术学报, 2009, 24(11): 134-141.
Li Gengyin, Yang Xiaodong, Zhou Ming. Stochastic Estimation Method of Voltage Sags in Complex Distribution Systems. Transactions of China Electrotechnical Society, 2009, 24(11): 134-141.
[1] Heine P, Pohjanheimo P, Lehtonen M, et al. A method for estimating the frequency and cost of voltage sags[J]. IEEE Trans. on Power Systems, 2002, 17(2): 290-296. [2] Qader M R, Bollen M H J, Allan R N. Stochastic prediction of voltage sags in a large transmission system[J]. IEEE Trans. on Industry Applications, 1999, 35(1): 152-162. . [3] Bahadoorsingh S, Milanovic J V, Zhang Y, et al. Minimization of voltage sag costs by optimal reconfiguration of distribution network using genetic algorithms[J]. IEEE Trans. on Power Delivery, 2007, 22(4): 2271-2278. [4] Bollen M H J. Fast assessment methods for voltage sags in distribution systems[J]. IEEE Trans. on Industry Applications, 1996, 32(6): 1414-1423. [5] Wang J, Chen S, Lie T T. System voltage sag performance estimation[J]. IEEE Trans. on Power Delivery, 2005, 20(2): 1738-1747. [6] Park C H, Jang G. Stochastic estimation of voltage sags in a large meshed network[J]. IEEE Trans. on Power Delivery, 2007, 22(3): 1655-1664. [7] Elisa E J, Araceli H. A method for voltage sag state estimation in power systems[J]. IEEE Trans. on Power Delivery, 2007, 22(4): 2517-2526. [8] Martinez J A, MartinArnedo J. Voltage sag studies in distribution networks-part I: system modeling[J]. IEEE Trans. on Power Delivery, 2006, 21(3): 1670-1678. [9] Martinez J A, Martin-Arnedo J. Voltage sag studies in distribution networks-part II: voltage sag assessm- ent[J]. IEEE Trans. on Power Delivery, 2006, 21(3): 1679-1688. [10] Moschakis M N, Hatziargyriou N D. Analytical calculation and stochastic assessment of voltage sags[J]. IEEE Trans. on Power Delivery, 2006, 21(3): 1727-1734. [11] 张鹏, 郭永基. 电压骤降的可靠性评估新方法[J]. 电力系统自动化, 2002, 26(8): 20-24. [12] 陶顺, 肖湘宁, 刘晓娟. 电压暂降对配电系统可靠性影响及其评估指标的研究[J]. 中国电机工程学报, 2005, 25(21): 63-69. [13] 周明, 张彪, 李庚银, 等. 基于质量工程理论的电压骤降经济评估[J]. 电工技术学报, 2007, 22(12): 152-158. [14] Bollen M H J. Method of critical distances for stochastic assessment of voltage sags[J]. IEE Procee- dings: Generation, Transmission and Distribution, 1998, 145(1): 70-76. [15] 张伯明, 陈寿孙, 严正. 高等电力网络分析[M]. 北京: 清华大学出版社, 2007.
2009, Vol. 24 
