Two-stage Multi-level Early Warning for Power System Frequency Safety Based on Improved Residual Network

被引：0
作者：
Li L. [1 ]
Wu J. [1 ]
Li B. [1 ]
Wang Y. [1 ]
Wang C. [2 ]
Dong X. [2 ]
机构：
[1] School of Electrical Engineering, Beijing Jiaotong University, Beijing
[2] Central China Branch, State Grid Corporation of China, Wuhan
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2023年 / 47卷 / 01期
关键词：
frequency safety; multi-level early warning; new power system; renewable energy; residual network;
D O I：
10.7500/AEPS20211119003
中图分类号：
学科分类号：
摘要：
With the proposal of the “carbon emission peak and carbon neutrality” goal and the large-scale grid connection of renewable energy clusters, the problem of power system frequency safety is highlighted again. Therefore, by referring to the deep learning method, a two-stage multi-level early warning model for power system frequency safety based on improved residual network is proposed. Firstly, the multi-level fine division for power system frequency safety is carried out, and the multi-level early warning model for power system frequency safety is proposed and constructed. In the first stage, the proposed model uses the classification evaluator based on the improved residual network to evaluate whether the disturbed frequency will exceed early warning value for the safety, and gives the early warning level. In the second stage, the regression predictor is used to further give the risk degree of early warning samples. Finally, the improved IEEE 10-machine 39-bus system and Illinois 200-bus system are taken as examples to test the model. The results show that the model has high early warning accuracy for the safety, which is not only better than other shallow learning methods and deep learning models, but also can accurately forecast the frequency risk degree, and has good robustness and anti-noise ability. © 2023 Automation of Electric Power Systems Press. All rights reserved.
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页码：22 / 34
页数：12
相关论文
共 32 条
  • [1] HAN Xiaoqing, LI Tingjun, ZHANG Dongxia, Et al., New issues and key technologies of new power system planning under double carbon goals［J］, High Voltage Engineering, 47, 9, pp. 3036-3046, (2021)
  • [2] ZHOU Xiaoxin, CHEN Shuyong, LU Zongxiang, Et al., Technology features of the new generation power system in China ［J］, Proceedings of the CSEE, 38, 7, pp. 1893-1904, (2018)
  • [3] DONG Xuzhu, HUA Zhuhu, SHANG Lei, Et al., Morphological characteristics and technology prospect of new distribution system ［J］, High Voltage Engineering, 47, 9, pp. 3021-3035, (2021)
  • [4] SONG Xinli, TANG Yong, LIU Wenzhuo, Et al., Mixed numerical integral algorithm for full dynamic simulation of the power system［J］, Proceedings of the CSEE, 29, 28, pp. 23-29, (2009)
  • [5] ANDERSON P M，, MIRHEYDAR M., A low-order system frequency response model［J］, IEEE Transactions on Power Systems, 5, 3, pp. 720-729, (1990)
  • [6] DUNLOP R D，, SCHWEPPE F., Dynamic equivalents for average system frequency behavior following major disturbances［J］, IEEE Transactions on Power Apparatus and Systems, PAS-91, 4, pp. 1637-1642, (1972)
  • [7] SHEN J K, LIU L，, Et al., Frequency response model and its closed-form solution of two-machine equivalent power system［J］, IEEE Transactions on Power Systems, 36, 3, pp. 2162-2173, (2021)
  • [8] WANG W K, CHEN C，, Et al., Fast and accurate frequency response estimation for large power system disturbances using second derivative of frequency data［J］, IEEE Transactions on Power Systems, 35, 3, pp. 2483-2486, (2020)
  • [9] WANG Qi, LI Feng, TANG Yi, Et al., On-line prediction method of transient frequency characteristics for power grid based on physical-statistical model［J］, Automation of Electric Power Systems, 42, 19, pp. 1-9, (2018)
  • [10] WEN Yunfeng, YANG Weifeng, LIN Xiaohuang, Review and prospect of frequency stability analysis and control of low-inertia power systems［J］, Electric Power Automation Equipment, 40, 9, pp. 211-222, (2020)
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