Unit commitment has been at the center of power system operation for well over 50 years. Yet, this problem cannot be considered solved due to its size and complexity. Today, operators rely on off-the-shelf optimization solvers to tackle this challenging problem, and often resort to simplifications to make the problem more tractable and solvable in a reasonable time. Nonetheless, despite the simplifications and advancements in commercial optimization solvers, solving the unit commitment in a timely manner is still difficult. Thus, in this work, we propose a parallel dual dynamic integer programming approach for solving this challenging problem. Different from what can be currently found in the literature, our parallel approach is applied to a deterministic problem and thus requires induced parallelization. Our strategy is assessed on 20 cases of a system with over 7,000 buses and it is able to solve all instances to a 0.1% gap in less than two hours with speed-ups up to 9.2 compared to a sequential strategy, while the current time limit to the problem at hand is three hours for the same gap. The results show that the strategy enables the operator to solve more realistic problems within reasonable times.
report 1, 03/2022
View Parallel Dual Dynamic Integer Programming for Large-Scale Hydrothermal Unit-Commitment