A comparative study of stochastic unit commitment and security-constrained unit commitment using high performance computing

The large-scale integration of renewable resources has recently raised interest in systematic methods for committing locational reserves in order to secure the system against contingencies and the unpredictable and highly variable fluctuation of renewable energy supply, while accounting for power flow constraints imposed by the transmission network. In this paper we compare two approaches for committing locational reserves: stochastic unit commitment and a hybrid approach of scenario-based security-constrained commitment. Parallel algorithms are developed for solving the resulting models, based on Lagrangian relaxation and Benders decomposition. The proposed algorithms are implemented in a high performance computing environment and the performance of the resulting policies is tested against a reduced model of the California ISO interconnected with the Western Electricity Coordinating Council.