A Subspace Identification Technique for Real-Time Stability Assessment of Droop Based Microgrids

Abstract

Real-time detection of the microgrid stability is crucial for determining and adjusting the power-sharing droop control's gains to maintain a sufficient stability margin. Maintaining minimum relative stability should be ensured at different operating conditions to accommodate sudden system changes. This article develops a novel subspace-based identification technique to assess microgrid stability in real-time without relying on offline analytical small or large-signal models. Unlike conventional system identification techniques that require the introduction of external excitation (signal probing, load switching, or contingency event), the proposed method employs a simple internal routine through small and short-duration perturbations in the active power droop gain of inverter-based distributed generation (IBDG). The use of subspace identification does not require pre-defining the system's order, avoids the exhaustive computations associated with iterative identification methods and can handle a change of microgrid's network configuration. The proposed stability assessment method has been tested on an IBDG microgrid considering different operating conditions in MATLAB/Simulink. The accuracy of the proposed real-time stability assessment tool is determined by comparing the results to the analytically-derived small-signal model as well as the Matrix pencil and Prony methods.