Title: Sequential Discrete Kalman Filter for Real-Time State Estimation in Power Distribution Systems: Theory and Implementation,
Abstract: This paper demonstrates the feasibility of implementing Real-Time State
Estimators (RTSEs) for Active Distribution Networks (ADNs) in
Field-Programmable Gate Arrays (FPGAs) by presenting an operational prototype.
The prototype is based on a Linear State Estimator (LSE) that uses
synchrophasor measurements from Phasor Measurement Units (PMUs). The underlying
algorithm is the Sequential Discrete Kalman Filter (SDKF), an equivalent
formulation of the Discrete Kalman Filter (DKF) for the case of uncorrelated
measurement noise. In this regard, this work formally proves the equivalence
the SDKF and the DKF, and highlights the suitability of the SDKF for an FPGA
implementation by means of a computational complexity analysis. The developed
prototype is validated using a case study adapted from the IEEE 34-node
distribution test feeder.