A Planning Scenario Clustering Method based on Monte-Carlo Simulation

A large number of renewable energy are connected to the power system to increase the uncertainty of the power system. In the past, the planning evaluation conducted a systematic safety and stability analysis for deterministic events in a typical operation scenario, for example, the winter max load scenario and summer max load scenario. However, the traditional approach did not consider the fluctuations of renewable energies, making the planning evaluation ignore some high probability scenarios that may lead to risk. In this paper, the renewable energy output fluctuation model and multi-state model are established. The equivalent load stochastic model based on k-means clustering algorithm is proposed. Based on the time series operation scenarios generated by Monte Carlo simulation, the planning scenario generation method based on clustering algorithm is finally proposed. The planning scenario generation method solves the problem that the planning evaluation has insufficient research on the operation condition, and can effectively guide the planning and evaluation of the power system.