An evaluation method for the maximum penetration of wind power of district power grid based on the self-organization criticality

被引:0
|
作者
Zhang Y. [1 ]
Wang Z. [2 ]
Lei Y. [2 ]
Wu D. [2 ]
Cheng R. [1 ]
Hua D. [3 ]
机构
[1] Shenzhen Power Supply Bureau Co., Ltd., Shenzhen
[2] College of Electrical and Information Engineering, Hunan University, Changsha
[3] School of Electric Power Engineering, South China University of Technology, Guangzhou
基金
中国国家自然科学基金;
关键词
Cascading failures; Interval power flow; Risk metrics; Self-organized criticality; Wind energy penetration;
D O I
10.7667/PSPC201863
中图分类号
学科分类号
摘要
With the increase of installation of wind energy in power systems, it has become a great challenge to evaluate the maximum wind energy limit penetration of a given regional power grid. By analyzing the self-organized criticality of complex power systems, a method based on interval Optimal Power Flow (OPF) cascading failure model to evaluate the maximum wind penetration is proposed. This method models the wind power output uncertainty as an interval number to form the interval cascading failure model based on interval OPF of power grids. With the increasing wind power penetration, the rules between the probability and scale of cascading failures can be discovered. The maximum wind power penetration is determined by the average of wind power when the power grid exhibits the self-organized criticality. Simulation experiments on IEEE 30-bus system and IEEE 118-bus system verify that the proposed method is a reasonable quantitative measurement method for assessing the wind power penetration limit of a power system. © 2019, Power System Protection and Control Press. All right reserved.
引用
收藏
页码:9 / 15
页数:6
相关论文
共 28 条
  • [1] Gonzalez A., Mckeogh E., Gallachoir B., The role of hydrogen in high wind energy penetration electricity systems: The Irish case, Renewable Energy, 29, 4, pp. 471-489, (2004)
  • [2] Zhao J., Gao W., Shangguan M., Et al., Overview of wind power participation in power system frequency modulation, Power System Protection and Control, 45, 21, pp. 157-169, (2017)
  • [3] Li J., Feng X., Yan G., Et al., Summary of power system frequency modulation research under high wind power penetration rate, Power System Protection and Control, 46, 2, pp. 163-170, (2018)
  • [4] Li Z., Ye L., Zhao Y., Et al., Short-term wind power prediction based on extreme learning machine with error correction, Protection and Control of Modern Power Systems, 1, 1, pp. 9-16, (2016)
  • [5] Stavros A., Nikos G., Power limitations and energy yield evaluation for wind farms operating in island systems, Renewable Energy, 31, 4, pp. 457-479, (2006)
  • [6] Tsouchnikas A.I., Hatziargyriou N.D., Probabilistic analysis of isolated power systems with wind power penetration limitations, 2006 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS, pp. 1-6, (2006)
  • [7] Weisser D., Garcia R.S., Instantaneous wind energy penetration in isolated electricity grids: concepts and review, Renewable Energy, 30, 8, pp. 1299-1308, (2005)
  • [8] Luo C., Far H.G., Banakar H., Et al., Estimation of wind penetration as limited by frequency deviation, IEEE Transactions on Energy Conversion, 22, 3, pp. 783-791, (2007)
  • [9] Vittal E., Mccalley J.D., Ajjarapu V., Et al., Wind penetration limited by thermal constraints and frequency stability, 200739th North American Power Symposium, pp. 353-359, (2007)
  • [10] Bak P., Tang C., Wiesenfeld K., Self-organized criticality: an explanation of 1/f noise, Physical Review Letters, 59, 4, pp. 381-384, (1987)