Sequential Discrete Kalman Filter for Real-Time State Estimation in Power Distribution Systems: Theory and Implementation

摘要

This paper demonstrates the feasibility of implementing Real-Time StateEstimators (RTSEs) for Active Distribution Networks (ADNs) inField-Programmable Gate Arrays (FPGAs) by presenting an operational prototype.The prototype is based on a Linear State Estimator (LSE) that usessynchrophasor measurements from Phasor Measurement Units (PMUs). The underlyingalgorithm is the Sequential Discrete Kalman Filter (SDKF), an equivalentformulation of the Discrete Kalman Filter (DKF) for the case of uncorrelatedmeasurement noise. In this regard, this work formally proves the equivalencethe SDKF and the DKF, and highlights the suitability of the SDKF for an FPGAimplementation by means of a computational complexity analysis. The developedprototype is validated using a case study adapted from the IEEE 34-nodedistribution test feeder.