Distributed Generation Monitoring for Hierarchical Control Applications in Smart Microgrids

Abstract

Hierarchical control/protection applications in smart microgrids require knowledge of real-time status of distributed generation (DG) systems. Lack or failure of communications with the microgrid central controller (MGCC) can significantly undermine performance of such applications since the MGCC cannot determine the number of operational energy sources. To overcome these challenges, the MGCC needs a secondary mechanism in order to track presence or absence of DG systems. This paper proposes a new monitoring approach that empowers the MGCC to estimate the number of operational DG systems and thus determine the total generation capacity of the microgrid. A parameter estimator is developed to extract an autoregressive model for the synchrophasors of current symmetrical components (CSC) of the main point of common coupling (PCC). The extracted model is used by an adaptive algorithm that identifies abrupt changes in DG by evaluating the norm of forward prediction error. The proposed approach uses real-time synchrophasor data to dynamically update the criterion for event detection and is very robust against abrupt load changes. The performance is verified using extensive simulations of the IEEE 13-Bus benchmark with four photovoltaic (PV) units.