Smart Grid State Estimation with PMUs Time Synchronization Errors

TL;DR

This paper addresses the challenge of state estimation in smart grids using PMUs with time synchronization errors, proposing a Kalman-based method that improves accuracy by compensating for these errors in real-time.

Contribution

It introduces a recursive Kalman filter algorithm that explicitly accounts for and corrects PMU time-synchronization errors in power system state estimation.

Findings

The proposed method outperforms existing approaches on synthetic IEEE data.

It effectively compensates for synchronization errors in real-field measurements.

The approach enhances the accuracy and reliability of grid state estimation.

Abstract

We consider the problem of PMU-based state estimation combining information coming from ubiquitous power demand time series and only a limited number of PMUs. Conversely to recent literature in which synchrophasor devices are often assumed perfectly synchronized with the Coordinated Universal Time (UTC), we explicitly consider the presence of time-synchronization errors in the measurements due to different non-ideal causes such as imperfect satellite localization and internal clock inaccuracy. We propose a recursive Kalman-based algorithm which allows for the explicit offline computation of the expected performance and for the real-time compensation of possible frequency mismatches among different PMUs. Based on the IEEE C37.118.1 standard on PMUs, we test the proposed solution and compare it with alternative approaches on both synthetic data from the IEEE 123 node standard distribution feeder and real-field data from a small medium voltage distribution feeder located inside the EPFL campus in Lausanne.