Reliability evaluation method of grid connected with photovoltaic power station

被引：0
|
作者：
Yang X. [1 ]
Liu Y. [1 ]
Zhang H. [1 ]
Li J. [2 ]
机构：
[1] School of Control and Computer Engineering, North China Electric Power University, Beijing
[2] China Electric Power Research Institute, Beijing
来源：
Liu, Yuqi (liu_yuqi0926@163.com) | 2016年 / Science Press卷 / 42期
关键词：
Fuzzy-C means clustering method; Monte Carlo; Multi-state-time-series model; Photovoltaic system; Reliability index; Sequential;
D O I：
10.13336/j.1003-6520.hve.20160907005
中图分类号：
学科分类号：
摘要：
To study the influences of stochastic property and high penetration of photovoltaic power system on the reliability of power grid, we proposed a new multi-state-time-series model for photovoltaic power system. The model classify the historical output data of photovoltaic station into four different types of weather by Fuzzy-C means clustering method and statistics on transition probability. The ARMA method is used to model the time series of all sixteen kinds of transition states, to establish a new model which can meet the actual situation more accurately. Finally, based on the model established in this paper, the sequential Monte Carlo method is applied to evaluate the reliability of power grid when photovoltaic is accessed to the system, and a calculation method for calculating the reliability limit of photovoltaic system is proposed based on the output of typical weather station. The simulation results on RTS79 show that the proposed model is consistent with the actual photovoltaic power output characteristics, and the calculation method is simple and effective which has a guiding significance for guiding the power grid access photovoltaic stations. © 2016, High Voltage Engineering Editorial Department of CEPRI. All right reserved.
引用
收藏
页码：2689 / 2696
页数：7
相关论文
共 17 条
  • [1] Mosadeghy M., Yan R., Saha T.K., Impact of PV penetration level on the capacity value of South Australian wind farms, Renewable Energy, 85, pp. 1135-1142, (2016)
  • [2] Yuan G., Chen S., Liu Y., Et al., Economic optimal dispatch of virtual power plant based on time-of-use power price, Power System Technology, 40, 3, pp. 826-832, (2016)
  • [3] Liu H., Lu D., Yang B., Et al., Sispatch strategy of energy storage station to smooth power fluctuations of high penetration photovoltaic generation, High Voltage Engineering, 41, 10, pp. 3213-3223, (2015)
  • [4] Liang H., Cheng L., Liu S., Monte Carlo simulation based reliability evaluation of distribution system containing microgrids, Power System Technology, 35, 10, pp. 76-81, (2011)
  • [5] He J., Deng C., Xu Q., Et al., Assessment on capacity credit and complementary benedit of power generation system integrate with wind farm, energy storage system and photovoltaic system, Power System Technology, 37, 11, pp. 3030-3036, (2013)
  • [6] Zhang Y., Zhao J., Deng Z., Modeling and simulation of photovoltaic grid-connected power system, High Voltage Engineering, 36, 12, pp. 3097-3102, (2010)
  • [7] Gao Y., Xie K., Hu B., Et al., Photovoltaic power capacity credit evaluation model considering the correlation between photovoltaic power generation and system load, Power System Protection And Control, 41, 14, pp. 1-6, (2013)
  • [8] Liang S., Hu X., Zhang D., Et al., Probabilistic models based evaluation method for capacity credit of photovoltaic generation, Automation of Electric Power Systems, 36, 13, pp. 32-37, (2012)
  • [9] Wang M., Zong X., Yuan Y., Et al., Reliability analisys of generation systems with photovoltaic stations, Proceedings of the CSEE, 33, 34, pp. 42-49, (2013)
  • [10] Wang X., Wu Z., Qu C., Reliability and capacity value evaluation of photovoltaic generation systems, Proceedings of the CSEE, 34, 1, pp. 15-21, (2014)
12