Estimation method of power system nodal inertia based on multi-innovation identification

被引：0
|
作者：
Li Y. [1 ]
Wen Y. [1 ]
Ye X. [2 ]
Jiang X. [3 ]
Lin X. [1 ]
机构：
[1] College of Electrical and Information Engineering, Hunan University, Changsha
[2] State Grid Sichuan Electric Power Company, Chengdu
[3] State Grid Henan Electric Power Company, Economic Research Institute, Zhengzhou
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2022年 / 42卷 / 08期
基金：
中国国家自然科学基金;
关键词：
electric power systems; frequency stability; multi-innovation identification; nodal inertia; output error moving average model; spatial distribution of inertia;
D O I：
10.16081/j.epae.202201031
中图分类号：
学科分类号：
摘要：
With a high proportion of new energy sources connected to the grid，intensive access to large-capacity DC and continuous shutdown of conventional power sources，the originally relatively balanced inertia resource distribution pattern of the power system has been broken，and new changes in the spatial distribution of rotational inertia have occurred. In order to enable system operators to sense the spatial distribution of inertia in time and locate the weak nodes of inertia accurately，an estimation method of power system nodal inertia based on multi-innovation identification is proposed. Firstly，based on the analysis of the system inertia resources to nodal inertia support role，the inertia spatial distribution estimation model is built based on the output error moving average model. Then，the parameters to be identified in the model are solved using a multi-innovation identification method to derive the equivalent inertia of all nodes in the system and to evaluate the spatial distribution of inertia of the whole system. Finally，simulations are carried out on the IEEE 39-node system to verify the effectiveness of the proposed method and its adaptability to faults of different scales and locations. © 2022 Electric Power Automation Equipment Press. All rights reserved.
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收藏
页码：89 / 95
页数：6
相关论文
共 20 条
  • [1] WEN Yunfeng, YANG Weifeng, WANG Ronghua, Et al., Review and prospect of toward 100 % renewable energy power systems［J］, Proceedings of the CSEE, 40, 6, pp. 1843-1856, (2020)
  • [2] 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)
  • [3] YAN R F, MASOOD N A, KUMAR S T，, Et al., The anatomy of the 2016 South Australia blackout：a catastrophic event in a high renewable network［J］, IEEE Transactions on Power Systems, 33, 5, pp. 5374-5388, (2018)
  • [4] XIAO Youqiang, LIN Xiaohuang, WEN Yunfeng, Multi-dimensional assessment of the inertia level of power systems with high penetration of HVDCs and renewables［J］, Electric Power Construction, 41, 5, pp. 19-27, (2020)
  • [5] HAN Shuai, ZHANG Feng, DING Lei, Et al., Available inertia evaluation method of wind farm based on mixed Copula function［J］, Electric Power Automation Equipment, 41, 3, pp. 189-195, (2021)
  • [6] YOU S T, Et al., Non-invasive identification of inertia distribution change in high renewable systems using distribution level PMU［J］, IEEE Transactions on Power Systems, 33, 1, pp. 1110-1112, (2018)
  • [7] INOUE T, TANIGUCHI H, Et al., Estimation of power system inertia constant and capacity of spinning-reserve support generators using measured frequency transients［J］, IEEE Transactions on Power Systems, 12, 1, pp. 136-143, (1997)
  • [8] TERZIJA V., Simultaneous estimation of the time of disturbance and inertia in power systems［J］, IEEE Transactions on Power Delivery, 29, 4, pp. 2018-2031, (2014)
  • [9] ORTEGA R., Online estimation of power system inertia using dynamic regressor extension and mixing［J］, IEEE Transactions on Power Systems, 34, 6, pp. 4993-5001, (2019)
  • [10] YANG D Y，, Et al., Inertia estimation based on observed electromechanical oscillation response for power systems［J］, IEEE Transactions on Power Systems, 34, 6, pp. 4291-4299, (2019)
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