Least Squares based Estimation of Thevenin Equivalent in Noisy Distribution Grid

TL;DR

This paper introduces a new adaptive method combining extremum seeking and least squares techniques to accurately estimate Thevenin equivalent parameters in noisy, dynamic distribution grids in real-time.

Contribution

It presents a novel hybrid approach that enhances real-time Thevenin parameter estimation by integrating extremum seeking with least squares in noisy environments.

Findings

Effective real-time Thevenin parameter estimation demonstrated in simulations.

Robustness of the method in noisy and fluctuating grid conditions.

Potential for improved grid monitoring and control.

Abstract

This work presents a novel approach that synergizes the extremum seeking method with an online least squares estimation technique to accurately estimate Thevenin equivalent circuit being seen at each node in distribution grids. Thevenin's theorem offers a simplified representation of electrical networks, critical for the effective monitoring, control, and optimization of grid operations. However, real-time identification of Thevenin parameters, particularly impedance, poses significant challenges due to the dynamic nature of distribution grids. By integrating extremum seeking algorithms, which are adept at locating optima in dynamic systems without explicit model information, with the robustness of least squares estimation, we develop a novel methodology that continuously adapts to grid fluctuations. These fusion harnesses the strengths of both techniques: the extremum seeking method's non-model-based optimization capabilities and the least squares method's proficiency in estimating parameter value in a noisy environment. The result is a robust, adaptive algorithm capable of delivering reliable Thevenin parameter estimations in real-time. Our simulation results demonstrate the efficacy of the proposed method, showcasing its potential as a tool for enhanced grid management and resilience.