A Probabilistic Analysis Approach for Large Power Systems with Renewable Resources

Probabilistic power flow has been widely used to manage uncertainties of demand, renewable energy sources and so on in power systems. Among many methods developed for probabilistic power flow, Monte Carlo simulation can give highly accurate results; however, it is usually computationally very intensive, and this makes it impractical for calculation and analysis of large power systems in practice. In this paper, we make use of data clustering techniques to group the input data to reduce the computation time, while maintaining an appropriate level of accuracy. The proposed approach is carried out on the modified IEEE-118 bus test system to demonstrate the performance of the proposed method in comparison with the result obtained by the traditional Monte Carlo simulation.