Weighted Least Squares State Estimation Algorithm with Code Implementation

This article provides a comprehensive explanation of the Weighted Least Squares State Estimation Algorithm implementation. The program demonstrates high flexibility by supporting varying numbers of nodes with minimal constraints, while maintaining a straightforward and easily understandable structure. The implementation employs a matrix-based approach using key MATLAB functions like mldivide (\) for efficient equation solving and includes configurable outputs for tracking objective function values and residual norms at each iteration. This allows users to monitor convergence behavior and optimize algorithm performance. We will systematically break down the algorithm's workflow, covering measurement modeling, weight matrix configuration, and the iterative solving process using the normal equation approach (J'*W*J)*Δx = J'*W*r, ensuring readers gain thorough understanding of both theoretical foundations and practical implementation for power system state estimation applications.