Copula-Monte Carlo Based Probabilistic Oscillatory Stability Analysis of Microgrid

This paper investigates effects of wind speed and solar irradiance uncertainties on oscillatory stability of Microgrid (MG). Novel estimation technique based on Student's t-Copula is applied to estimate the probability distribution function (PDF) of wind speed and solar irradiance by taking into account the stochastic dependencies between those energy resources. A detailed MG system comprising of Wind Energy Conversion System (WECS), PV system and Diesel Engine (DE) based distributed generation (DG) units is considered to provide a complete dynamic response of the investigated MG. Distribution of critical modes damping ratio is thoroughly investigated by means of Monte Carlo Simulation (MCS). Probabilistic study of small signal stability in MG implies that the renewable energy resources (RES) uncertainties result in a dynamic change of power-sharing strategies and introduce adverse effects on small signal stability. In addition, the damping value is variated from critical damped (with probability around 0.004), well damped and under damped. Moreover, it was monitored that wind speed fluctuation brings more severe impact on system damping than irradiance variation. Consequently, the MG experienced more oscillatory conditions and even lead to unstable situation at high wind speed circumstances. While under solar irradiance change, the investigated MG system can maintain its stable operation.