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含高比例分布式电源配电系统的参数辨识方法

魏炜 季文文 黄旭 靳小龙 黄盼

电力建设2025,Vol.46Issue(5):96-111,16.
电力建设2025,Vol.46Issue(5):96-111,16.DOI:10.12204/j.issn.1000-7229.2025.05.009

含高比例分布式电源配电系统的参数辨识方法

Parameter Identification Method for Distribution Systems with a High Proportion of Distributed Renewable Energy

魏炜 1季文文 1黄旭 2靳小龙 1黄盼1

作者信息

  • 1. 智能电网教育部重点实验室(天津大学),天津市 300072
  • 2. 国网天津市电力公司城东供电分公司,天津市 300250
  • 折叠

摘要

Abstract

[Objective]The integration of a high proportion of distributed generation into the distribution system leads to frequent and significant voltage fluctuations,which negatively affect the accuracy of voltage measurement data and increase the difficulty of parameter identification based on full measurement data of the distribution system.[Methods]This paper proposes a solution to the parameter identification challenge based on full measurement data in distribution systems by establishing an adaptive extended Kalman filtering(AEKF)model based on current measurements.Specifically,the state equations for the line parameters are derived by incorporating historical temperature data,whereas those for the transformer parameters are established using a first-order exponential smoothing method.By applying Kirchhoff's law,the current amplitude measurement equations for the lines and transformers are constructed.A voltage pseudomeasurement strategy is introduced to construct pseudomeasurement equations based on prior parameter estimates.An adaptive noise mechanism is designed in which the noise covariance matrix is dynamically estimated based on the differences in adjacent measurements,thereby enhancing the robustness of the algorithm against time-varying noise.[Results]The results showed that the relative mean identification errors for line resistance and reactance were 1.45%and 1.61%,respectively,a reduction of 61.2%and 61.7%compared with those of the traditional EKF method with errors of 3.7%and 4.2%.The maximum relative error decreased from 12.6%to 2.4%.The peak identification errors for transformer resistance and reactance were 5.2%and 5.53%,and the single iteration time was optimized from 2.2 to 1.04 s.[Conclusion]This method effectively addresses the impact of deficiencies in voltage measurement data quality on parameter identification by integrating current amplitude data with historical operational information.Pseudomeasurement modeling and adaptive noise estimation techniques work synergistically to enhance the stability and computational efficiency in complex power grid environments,helping address the challenges posed by the randomness and volatility of distributed generation and improving the fine-tuned control capabilities of the distribution system.

关键词

配电系统/参数辨识/扩展卡尔曼滤波/无相位量测/噪声处理

Key words

power distribution systems/parameter identification/extended Kalman filter/phase-angle-free measurements/noise processing

分类

信息技术与安全科学

引用本文复制引用

魏炜,季文文,黄旭,靳小龙,黄盼..含高比例分布式电源配电系统的参数辨识方法[J].电力建设,2025,46(5):96-111,16.

基金项目

国家自然科学基金项目(52207133) This work is supported by the National Natural Science Foundation of China(No.52207133). (52207133)

电力建设

OA北大核心

1000-7229

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