Distributed Gauss-Newton Method for AC State Estimation: A Belief Propagation Approach

TL;DR

This paper introduces a fully distributed Gauss-Newton algorithm for AC state estimation in power systems, leveraging belief propagation on factor graphs to achieve solutions equivalent to traditional methods.

Contribution

It develops a novel distributed approach using belief propagation for AC state estimation, with explicit message expressions and convergence analysis.

Findings

Algorithm matches traditional weighted least-squares results.

Demonstrated effectiveness on IEEE 14 bus test case.

Provides detailed step-by-step implementation.

Abstract

In this paper, we propose a solution to an AC state estimation problem in electric power systems using a fully distributed Gauss-Newton method. The proposed method is placed within the context of factor graphs and belief propagation algorithms and closed-form expressions for belief propagation messages exchanged along the factor graph are derived. The obtained algorithm provides the same solution as the conventional weighted least-squares state estimation. Using a simple example, we provide a step-by-step presentation of the proposed algorithm. Finally, we discuss the convergence behaviour using the IEEE 14 bus test case.