An Optimization-Based Robust Dynamic State Estimation for Power Systems with Synchronized Phasor Measurement Units, Involving Disturbance Rejection

Author:

Hakimian Vahid1ORCID,Seifi Hossein1ORCID

Affiliation:

1. Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

State estimation provides the best estimate of the system states using a set of measurements that is divided into two main classes; static and dynamic types. The state estimator should provide an acceptable response in the presence of system changes and/or disturbances. To achieve this aim, considering the high rate of data changes and the high volume of exchanging information, the phasor measurement units could play an outstanding role. Furthermore, due to the inevitable errors of the measurements, and to provide an authentic estimate of the system states using the measured data, a state estimator should be able to eliminate or decrease the undesirable effect of bad data or outliers on the final output of the process. This type of state estimator is called a robust type. In this paper, a dynamic state estimator for a system with the synchronized phasor measurement units is utilized, which is capable of decreasing the effect of disturbances. Simultaneously, the robustness of the state estimation process in the presence of outliers is considered, which enables the state estimation process to reduce the negative effect of outliers on its final output. Therefore, the implemented process is called a robust dynamic state estimation method. By defining different scenarios and utilizing numerical indices, simulation results are thoroughly analyzed based on an explanatory three-bus network and the IEEE standard 14-bus and 57-bus networks using the MATPOWER tool.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Modeling and Simulation

Reference56 articles.

1. Power System Dynamic State Estimation With Synchronized Phasor Measurements

2. Comparison of state estimation algorithms for extreme contingencies;S. Kamireddy

3. The Wide World of Wide-area Measurement

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