Real-Time Equality-Constrained Hybrid State Estimation in Complex Variables

TL;DR

This paper introduces a real-time hybrid state estimation method for complex power networks using Wirtinger calculus, demonstrating superior speed and accuracy over existing methods, suitable for large-scale transmission systems.

Contribution

It extends the complex normal equations approach with equality constraints via Wirtinger calculus, enabling efficient real-time state estimation in large power networks.

Findings

Achieves state estimation in under 300 ms for large networks

Outperforms previous methods in speed and accuracy

Effective handling of zero injection measurements

Abstract

The hybrid power system state estimation problem requires computing the state of the power network using data from both legacy and phasor measurements. Recent research has shown that the normal equations approach in complex variables is computationally advantageous, particularly in the presence of phasor measurement values, and that its software implementation is best suited to modern processors that employ single instruction multiple data (SIMD) processor extensions. The complex normal equations approach is however not ideal for handling zero injection measurements, as it requires their modeling as pseudo-measurements with high weights. This paper employs Wirtinger calculus for extending the complex normal equations approach to include equality constraints, and contrasts it with two previously published implementations: the normal equations approach in complex variables and the hybrid equality constrained state estimator in real variables. Numerical results are reported on transmission networks having up to 9241 nodes; they show that the complex variable equality constrained hybrid state estimator exhibits superior performance as compared to the above two techniques in terms of both computational time and accuracy. Moreover, the execution time on the largest network is less than 300 ms, which makes the proposed implementation commensurate with the requirements of real-time applications.