Stochastic Unit Commitment via Progressive Hedging - Extensive Analysis of Solution Methods

Owing to the massive deployment of renewablepower production units over the last couple of decades, the useof stochastic optimization methods to solve the unit commitmentproblem has gained increasing attention. Solving stochastic unitcommitment problems in large-scale power systems requires high computational power, as stochastic models are dramaticallymore complex than their deterministic counterparts. This paperprovides new insight into the potential of Progressive Hedgingto decrease the solution time of the stochastic unit commitmentproblem with a relatively small trade-off in terms of thesuboptimality of the solution. Computational studies show thatthe run-time is at most half of what is needed to solve theoriginal extensive formulation of the problem, when more thanten wind power scenarios are utilized. These studies demonstrategreat potential for solving real-world stochastic unit commitmentproblems using the Progressive Hedging algorithm.