Parameter Estimator

Accurate network parameters are essential for reliable state estimation, yet they are often uncertain or outdated in practice. Line impedances, transformer parameters, and other branch characteristics may deviate from their nominal values due to modeling errors, aging, equipment replacement, or incomplete records. Traditional parameter estimation methods are highly sensitive to bad data, leverage points, and insufficient measurement redundancy, making reliable parameter identification difficult in real operating environments.

SE+ enables a robust and practical approach to parameter estimation through repeated, consistency-based analysis. In each SE+ run, parameters of selected branches with sufficient measurement redundancy can be estimated together with system states. Because SE+ rejects inconsistent measurements and focuses on the most reliable data, each run produces high-quality parameter estimates for those branches. By collecting parameter estimates from multiple SE+ runs over time and applying statistical analysis, true parameter values can be identified with high confidence while filtering out the influence of bad data, topology errors, and transient operating conditions. This SE+-based Parameter Estimator provides utilities with a reliable way to validate, correct, and maintain network models using real operating data—without relying on perfectly clean measurements or intrusive testing.