Identification of Efficient Sampling Techniques for Probabilistic Voltage Stability Analysis of Renewable-Rich Power Systems

This paper presents a comparative analysis of six sampling techniques to identify an efficient and accurate technique be applied probabilistic voltage stability assessment in large-scale power systems. In this study, different are investigated compared each other terms their accuracy efficiency, including Monte Carlo (MC), three versions Quasi-Monte (QMC), i.e., Sobol, Halton, Latin Hypercube, Markov Chain MC (MCMC), importance (IS) technique, evaluate suitability for application with uncertain The coefficient determination (R2) root mean square error (RMSE) calculated measure the efficiency other. All provide more than 99% by producing large number wind speed random samples (8760 samples). on hand, QMC most techniques, providing 96% only small generated (150 samples) techniques.