Parameter Identification of Time-varying Exponential Load Model Based on Improved RLS Algorithm

CHEN Han; HAO Ruixiang; LIU Yingying; WANG Hui; WANG Tongxun; LI Dalu

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Parameter Identification of Time-varying Exponential Load Model Based on Improved RLS Algorithm

更新时间：2025-12-08

- Parameter Identification of Time-varying Exponential Load Model Based on Improved RLS Algorithm
- Vol. 46, Issue 7, Pages: 2380-2388(2020)
- 作者机构：
  
  1. 北京交通大学电气工程学院
  2. 全球能源互联网研究院有限公司
  3. 先进输电技术国家重点实验室
  4. 华北电力大学(保定)电力工程系
  5. 特变电工股份有限公司
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published Online：31 July 2020，
  
  Published：2020
- 稿件说明：
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CHEN Han, HAO Ruixiang, LIU Yingying, et al. Parameter Identification of Time-varying Exponential Load Model Based on Improved RLS Algorithm[J]. 2020, 46(7): 2380-2388.
DOI：

CHEN Han, HAO Ruixiang, LIU Yingying, et al. Parameter Identification of Time-varying Exponential Load Model Based on Improved RLS Algorithm[J]. 2020, 46(7): 2380-2388. DOI：

摘要

考虑到实际配电网负荷的组成会随着用户行为、天气状况以及系统运行方式而发生变化

负荷模型的参数与外界影响因子之间的关系是复杂且非线性的

并应随时间发生变化

因此

提出采用考虑时变性的幂函数模型来描述配电网负荷和电压随时间变化的情况。此外

为了提高模型参数辨识的准确性

提出基于三阶累积量的可变遗忘因子递推最小二乘法

用于自适应跟踪模型的时变参数。基于数字仿真算例和电网实际采样数据

对改进算法和传统递推最小二乘法的负荷模型参数辨识结果进行了仿真比较

从各类误差评价指标来看

改进算法估计精度优于传统递推最小二乘法

具有良好的跟踪性能和抑噪性能。

Abstract

The load consumption always changes with time due to factors such as human behaviors

weather conditions and continuous on/off switches of different kinds of loads

thus the relationship parameters of the load model with external factors is complex and nonlinear

and the parameters are not constants. Therefore

the load voltage characteristics exponential model in which time-varying is taken into consideration is proposed to describe the load and voltage variation with time in distribution network. Moreover

the improved recursive least square（RLS） algorithm based on the cumulant and variable forgetting factor is proposed to estimate time-varying exponential model parameters. The identification results of the improved algorithm and the traditional RLS algorithm are compared based on the digital simulation example and the actual sampling data of the power grid.From the angles of all kinds of error evaluation indexes

the estimation accuracy of the improved algorithm is better than that of the traditional RLS algorithm

which proves that the improved algorithm has good tracking performance and noise suppression performance.

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Related Institution

Liaocheng Power Supply Company, State Grid Shandong Power Corporation

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