A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes

Mehdi AHMADI JIRDEHI; Reza HEMMATI; Vahid ABBASI; Hedayat SABOORI

doi:10.1631/FITEE.1500301

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A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes

Regular Papers | Updated：2022-05-19

- A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes
- 一种针对测试误差、参数误差和负荷突变故障分析的多功能动态状态估计器
- Frontiers of Information Technology & Electronic Engineering Vol. 17, Issue 11, Pages: 1218-1227(2016)
- Affiliations：
  
  Department of Electrical Engineering, Kermanshah University of Technology, Kermanshah 63766-67178, Iran
- Author bio：
  
  E-mail:m.ahmadi@kut.ac.ir
  E-mail:reza.hematti@gmail.com
  E-mail:v_abbasi@kut.ac.ir
  E-mail:h.saboori@kut.ac.ir
- Funds：
- DOI：10.1631/FITEE.1500301
  CLC： TM921
- Received：15 September 2015，
  
  Accepted：15 November 2015，
  
  Published：2016-11
- Accepted：
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Mehdi AHMADI JIRDEHI, Reza HEMMATI, Vahid ABBASI, et al. A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(11): 1218-1227.
DOI：

Mehdi AHMADI JIRDEHI, Reza HEMMATI, Vahid ABBASI, et al. A multi-functional dynamic state estimator for error validation: measurement and parameter errors and sudden load changes[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(11): 1218-1227. DOI： 10.1631/FITEE.1500301.

摘要

本文提出了一种基于卡尔曼滤波理论的动态状态估计新算法，可有效探测、识别并校正电力系统中的测试误差和支路参数误差。同时，该算法亦可成功探测和识别电力系统中的负荷突变。该方法在每段取样时间内，采用三种归一化向量对误差进行处理，包括归一化测量残差，归一化拉格朗日乘子，以及归一化新息向量。在IEEE14节点测试系统上对所提出的算法进行了可行性和效能验证，并通过对数值结果的呈示和讨论，说明了该方法的精确度。

Abstract

We propose a new and efficient algorithm to detect

identify

and correct measurement errors and branch parameter errors of power systems. A dynamic state estimation algorithm is used based on the Kalman filter theory. The proposed algorithm also successfully detects and identifies sudden load changes in power systems. The method uses three normalized vectors to process errors at each sampling time: normalized measurement residual

normalized Lagrange multiplier

and normalized innovation vector. An IEEE 14-bus test system was used to verify and demonstrate the effectiveness of the proposed method. Numerical results are presented and discussed to show the accuracy of the method.

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references

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