基于特征模型的电力系统在线动态等效建模
作者:
作者单位:

(国网江苏省电力有限公司,江苏 南京211100 )

作者简介:

江叶峰(1976—),男,高级工程师,硕士,主要从事电力调度运行管理研究。E-mail: jyf1976@sina.cn

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中图分类号:

TM743

基金项目:

国网江苏省电力有限公司科技项目(J2020110)


Online dynamic equivalent modeling of power system based on characteristic model
Author:
Affiliation:

(State Grid Jiangsu Electric Power Maintenance Branch Company, Nanjing 211100, China )

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    摘要:

    针对现有基于元件机理进行动态等效建模可能导致模型结构复杂及参数辨识难度大的问题,在对电网进行分层分区建模时,引入模型结构简单、工程实现容易的特征建模方法,对下层电网(或区域电网)进行在线的动态等效建模。通过理论分析和仿真对比,确定了特征模型的输入量为电压,输出量为电流实部、虚部;针对实际电网运行工况随时发生变化的问题,当元件机理模型发生慢时变时,采用递推最小二乘算法辨识特征模型的慢时变参数。算例结果表明,该模型拟合误差小且参数平稳性高。

    Abstract:

    Aiming at the problems that the existing dynamic equivalent modeling based on component mechanism may lead to the complex model structure and the difficult parameter identification, by introducing a feature modeling method with simple model structure and easy engineering implementation, this paper models the dynamic equivalence of the lower-level grid (or regional grid) online and realizes the hierarchical and zonal modelling of modern power grids. Firstly, the input and output variables of the characteristic model are determined by theoretical analysis and simulation comparison. Voltage is selected as the input variable, while the real part and imaginary part of current are selected as output variables. Then, to address the problem that the operating conditions of actual grid change at any time, the recursive least squares algorithm is used to identify the slowly-time-varying parameters of the characteristic model, when the component mechanism model undergoes slow time-varying. The results show that the fitting error of this kind of characteristic model is small, and the parameters have high stability.

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江叶峰,熊浩,付伟.基于特征模型的电力系统在线动态等效建模[J].河海大学学报(自然科学版),2022,50(5):139-143.(JIANG Yefeng, XIONG Hao, FU Wei. Online dynamic equivalent modeling of power system based on characteristic model[J]. Journal of Hohai University (Natural Sciences),2022,50(5):139-143.(in Chinese))

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  • 收稿日期:2021-08-26
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  • 在线发布日期: 2022-09-24
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