A WLAV-based Robust Hybrid State Estimation using Circuit-theoretic Approach

TL;DR

This paper introduces a circuit-theoretic WLAV-based hybrid AC state estimation method that enhances robustness against bad data, guarantees convergence, and improves efficiency in large power grid cases.

Contribution

It develops a novel hybrid ACSE approach using WLAV and circuit theory, with guaranteed convergence and problem-specific heuristics for faster computation.

Findings

Outperforms WLS-based algorithms in large case studies.

Automatically rejects bad data and identifies suspicious measurements.

Demonstrates faster convergence and better runtime performance.

Abstract

For reliable and secure power grid operation, AC state-estimation (ACSE) must provide certain guarantees of convergence while being resilient against bad-data. This paper develops a circuit-theoretic weighted least absolute value (WLAV) based hybrid ACSE that satisfies these needs to overcome some of the limitations of existing ACSE methods. Hybrid refers to the inclusion of RTU and PMU measurement data, and the use of the LAV objective function enables automatic rejection of bad data while providing clear identification of suspicious measurements from the sparse residual vector. Taking advantage of linear construction of the measurement models in circuit-theoretic approach, the proposed hybrid SE is formulated as a LP problem with guaranteed convergence. To address efficiency, we further develop problem-specific heuristics for fast convergence. To validate the efficacy of the proposed approach, we run ACSE on large cases and compare the results against WLS-based algorithms. We further demonstrate the advantages of our solution methodology over standard commercial LP solvers through comparison of runtime and convergence performance.