Parameter identification method of composite load model using small disturbance signal of PMU

被引:0
|
作者
Diao H. [1 ]
Li P. [1 ]
Guo S. [2 ]
Lin S. [3 ]
Su H. [1 ]
Shen Y. [1 ]
机构
[1] College of Electrical and Information Engineering, Hunan University, Changsha
[2] State Grid Hunan Electric Power Company Limited Research Institute, Changsha
[3] Guangzhou Power Supply Bureau, CSG Guangdong Electric Power Company, Guangzhou
基金
中国国家自然科学基金;
关键词
composite load model; parameter identification; PMU data processing; small disturbance signals;
D O I
10.19783/j.cnki.pspc.221680
中图分类号
学科分类号
摘要
Small disturbance signals similar to noise always exist in the daily operation of power systems, and their use for load parameter identification can solve a problem of time-varying and distributed loads that cannot be handled by traditional overall measurement and identification methods. This paper proposes a parameter identification method of a "Z+IM" comprehensive load model based on a small perturbation signal measured by PMU. This method adopts the rolling identification framework of PMU measurement data, and divides rolling identification into two steps: data processing and load parameter identification. First, from the characteristics of small disturbance signals measured by PMUs, relatively high quality small disturbance data sets of PMUs are obtained through the steps of initial screening, preprocessing, coarse screening of identifiable sets and denoising. Then, the time-varying, electromagnetic and mechanical parameters of the load are identified by a two-stage identification strategy based on the idea of prediction error. The load parameters obtained by the proposed method can be directly applied to domestic mainstream simulation programs such as PSASP and BPA without conversion. This has practical engineering application value. Finally, the effectiveness and robustness of the proposed method are verified by the simulation of a 3-machine 9-bus system and the actual grid in Hunan province. © 2023 Power System Protection and Control Press. All rights reserved.
引用
收藏
页码:37 / 49
页数:12
相关论文
共 29 条
  • [1] QU Xing, LI Xinran, LI Peiqiang, Et al., Load modeling considering voltage regulation of the distribution network, Proceedings of the CSEE, 38, 6, pp. 1695-1705, (2018)
  • [2] YANG Zijun, DING Xiaoye, LU Xiao, Et al., Inverter air conditioner load modeling and operational control for demand response, Power System Protection and Control, 49, 15, pp. 132-140, (2021)
  • [3] WU Haijiang, CHEN Jinrong, Construction of the load demand side response model for distribution networks, Power System and Clean Energy, 37, 9, pp. 77-82, (2021)
  • [4] WANG Chen, YE Jiangming, HE Jiahong, Short-term user load forecasting based on GARCH-M family model with different distributions, Electric Power Engineering Technology, 41, 5, pp. 110-115, (2022)
  • [5] (2012)
  • [6] GUO Cheng, XIE Hao, MENG Xian, Et al., Research on parameter identification of load model based on GWO algorithm, Journal of Electric Power Science and Technology, 37, 2, pp. 30-37, (2022)
  • [7] PANG Chuanjun, ZHANG Bo, YU Jianming, Et al., Probabilistic interval forecasting of power load based on structured load model, Electric Power, 54, 9, pp. 89-95, (2021)
  • [8] TONG Ruining, LI Peng, LANG Xun, Et al., Non-intrusive power load identification model based on FPCA and KELM, Electric Power Construction, 42, 2, pp. 85-92, (2021)
  • [9] (2008)
  • [10] LI Ying, HE Renmu, XU Yanhui, Research of PMU-based load model parameters identification of Guangdong power grid, Southern Power System Technology, 3, 1, pp. 16-19, (2009)