Online Probabilistic Static Security Assessment for Power Systems Considering High Renewable Penetration

Abstract With the rapid development of renewable energy, a large number energy stations are connected to power system, which leads decrease in inertia system and an increase safety risks suffered. Thus, online static security assessment (SSA) is increasingly necessary. However, because uncertainty it not feasible check all possible scenarios SSA. To reduce calculations achieve SSA short time, new method based on scenario clustering for future ultra-short-term proposed this paper. In offline stage, key set constructed by Markov Chain Monte Carlo K-means with historical data. application, initial probability distribution outputs calculated joint output previous interval corrected weather Then load flow calculation N-1 criteria executed, safe operation calculated. The effectiveness scheme has been verified IEEE-300 where one generators replaced station.