Post-disaster time-series load restoration method for distribution network considering dynamic uncertainty of distributed renewable energy

被引：0
|
作者：
Liu F. [1 ]
Lin C. [1 ]
Chen C. [1 ]
Liu R. [1 ]
Li G. [1 ]
Bie Z. [1 ]
机构：
[1] State Key Laboratory of Electrical Insulation and Power Equipment, Institute of Power System and Its Resilience, Xi'an Jiaotong University, Xi'an
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2022年 / 42卷 / 07期
基金：
中国国家自然科学基金;
关键词：
dynamic microgrid; load restoration; resilient distribution network; rolling update; uncertainty of renewable energy;
D O I：
10.16081/j.epae.202204019
中图分类号：
学科分类号：
摘要：
Current studies regarding the load restoration of resilient distribution network have seldom considered the uncertainty of grid-connected distributed renewable energy output and the impact of its dynamic updating on load restoration strategy. Meanwhile，the emerging dynamic microgrid technology can flexibly adjust the network topology according to the forecasting curve of uncertain factors，and therefore further improving system resilience. Therefore，a post-disaster time-series load restoration method for distribution system considering dynamic uncertainty of distributed renewable energy is proposed. The rolling update model of forecasting probability distribution of uncertain factors based on Gaussian Copula is established，and the scenario generating method based on slice sampling method is proposed to formulate the typical scenarios of distributed renewable energy output and load. Then，the multi-period load restoration model is established considering the division of dynamic microgrid. Furthermore，the rolling update is combined with the load restoration model to form the framework of online load restoration decision for resilient distribution system. The proposed method is validated on the modified IEEE 37-bus feeder test system，and the case results show that the method can fully consider the impact of dynamic change uncertainty and flexible topology changing ability of distribution network on load restoration strategy，thus effectively improving system restoration ability. © 2022 Electric Power Automation Equipment Press. All rights reserved.
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收藏
页码：159 / 167
页数：8
相关论文
共 20 条
  • [1] (2019)
  • [2] BIE Zhaohong, LIN Yanling, QIU Aici, Concept and research prospects of power system resilience［J］, Automation of Electric Power Systems, 39, 22, pp. 1-9, (2015)
  • [3] BIE Zhaohong, LIN Chaofan, LI Gengfeng, Et al., Development and prospect of resilient power system in the context of energy transition［J］, Proceedings of the CSEE, 40, 9, pp. 2735-2744, (2020)
  • [4] YU Hao, LIU Jiakai, SONG Guanyu, Et al., Multi-time-period load restoration method for active distribution networks based on SOCP［J］, Journal of Tianjin University（Science and Technology, 52, 12, pp. 1303-1311, (2019)
  • [5] SANG Y R., Networked microgrids with roof-top solar PV and battery energy storage to improve distribution grids resilience to natural disasters［J］, International Journal of Electrical Power & Energy Systems, 123, (2020)
  • [6] HAO Lili, WANG Hui, WANG Guodong, Et al., Influence factor tracing of operation risk for distribution network with distributed generations［J］, Electric Power Automation Equipment, 41, 1, pp. 27-37, (2021)
  • [7] LIU Jiayu, ZHANG Qiqi, WANG Ying, Et al., Service restoration strategy for distribution systems considering renewable-energy-based distributed generators［J］, Journal of Global Energy Interconnection, 3, 6, pp. 600-606, (2020)
  • [8] Zhiwen WANG, Chen SHEN, Yin XU, Et al., Risk-limiting load restoration for resilience enhancement with intermittent energy resources［J］, IEEE Transactions on Smart Grid, 10, 3, pp. 2507-2522, (2019)
  • [9] Chaofan LIN, Zhaohong BIE, Chaoqiong PAN, Et al., Fast cumu-lant method for probabilistic power flow considering the nonlinear relationship of wind power generation［J］, IEEE Transactions on Power Systems, 35, 4, pp. 2537-2548, (2020)
  • [10] Jun LIU, HAO Xudong, CHENG Peifen, Et al., Probabilistic load flow method combining M-Copula theory and cumulants［J］, Power System Technology, 42, 2, pp. 578-584, (2018)
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