Grid impedance estimation using recursive least squares algorithm

Abstract

Framework impedance assessment is a vital errand in present day power frameworks for keeping up with soundness, unwavering quality, and proficiency. This paper proposes a strategy for estimating the impedance of a grid by making use of a dataset that can be obtained for free and the Recursive Least Squares (RLS) algorithm. Our strategy utilizes phasor estimation units (PMUs) and synchronized estimations from the IEEE 123-transport framework dataset to appraise the matrix impedance at different areas in the power framework. The proposed strategy is fit for dealing with non-linearity and aggravations in the power framework and gives exact outcomes. Additionally, the proposed technique can be coordinated with existing observing and control frameworks to advance situational mindfulness and the general presentation of the power framework. The proposed method's theoretical foundation is presented, and its performance is evaluated through simulation studies. The simulated results demonstrate that the suggested approach can estimate grid impedance accurately under a wide range of operating conditions. Power system planners and operators may utilize the suggested grid impedance estimation technique, which employs the RLS algorithm and a readily available dataset, to estimate grid impedance and improve power system performance.