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International Journal of Advanced Engineering Application

ISSN: 3048-6807

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State Estimation in Power Systems Using Kalman Filtering Techniques

Author(s):Rohit Kumar1, Divya Singh2, Nikhil Chauhan3, Pradeep Tiwari4, Kritika Sharma4

Affiliation: 1,2,3,4,5 Department of Electrical Engineering, Government Engineering College, Jabalpur, Madhya Pradesh, India

Page No: 6-10

Volume issue & Publishing Year: Volume 2 Issue 8 , Aug-2025

Journal: International Journal of Advanced Engineering Application (IJAEA)

ISSN NO: 3048-6807

DOI: https://zenodo.org/records/17623948

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Abstract:
State estimation is a vital function in modern power system operation and control, providing the system operator with accurate, real-time information about the network's operating condition. Conventional state estimation methods, such as Weighted Least Squares (WLS), often face challenges under dynamic conditions and in the presence of measurement noise. This paper presents a detailed investigation into the application of Kalman Filtering (KF) techniques for state estimation in power systems. Both standard Kalman Filter (KF) and Extended Kalman Filter (EKF) approaches are discussed in terms of their performance, accuracy, and computational efficiency. Simulation results demonstrate that Kalman filtering techniques offer significant improvements in accuracy and robustness compared to conventional methods, particularly under dynamic load variations and noisy measurement environments

Keywords: State estimation, Power systems, Kalman filter, Extended Kalman filter, Dynamic estimation, Smart grid

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