基于卡尔曼滤波的电力系统时滞负荷参数辨识方法

Q2 Social Sciences
Shuangling Wang, Shudong He
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引用次数: 0

摘要

针对现有负荷参数辨识方法精度低、辨识误差大的问题,提出了一种基于卡尔曼滤波的电力系统时滞负荷参数辨识方法。首先,根据时滞环节与系统电压变化的关系,分析了时滞电力系统的运行特性。其次,采用幂函数法和电机等效电路法对不同特性参数进行表征,完成了含时滞电力系统负载参数的特性分析;最后,构造了负载参数状态预测方程,并计算了负载参数的卡尔曼增益值。为了完成电力系统负荷参数辨识,建立了卡尔曼滤波器的参数辨识模型。实验结果表明,该方法可以减小负载参数辨识的误差,最小误差仅为0.11%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Load parameter identification method of power system with time delay based on Kalman filter
Aiming at the problems of low accuracy and large identification error of existing load parameter identification methods, a load parameter identification method of power system with time delay based on Kalman filter is proposed. Firstly, according to the relationship between the time-delay link and the voltage variation in the system, the operation characteristics of the time-delay power system are analysed. Secondly, power function and motor equivalent circuit method are used to characterise different property parameters, and the property analysis of load parameters of power system with time delay is completed. Finally, the load parameter state prediction equation is constructed, and the Kalman gain value of the load parameter is calculated. The parameter identification model of Kalman filter is constructed to complete the power system load parameter identification. The experimental results show that the proposed method can reduce the error of load parameter identification, and the minimum error is only 0.11%.
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来源期刊
International Journal of Energy Technology and Policy
International Journal of Energy Technology and Policy Social Sciences-Geography, Planning and Development
CiteScore
1.50
自引率
0.00%
发文量
16
期刊介绍: The IJETP is a vehicle to provide a refereed and authoritative source of information in the field of energy technology and policy.
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