A Two-Stage Robust Optimization For Pjm Look-Ahead Unit Commitment

Robust optimization recently becomes a state-of-the-art approach to solve decision-making under uncertainty problems in the power system operations. To better quantify and highlight the significance of the robust optimization for reliable unit commitment runs, PJM and Alstom Grid have collaborated to develop a two-stage robust optimization (TSRO) prototype since 2012. In this paper, we present a computational tractable TSRO framework for the PJM Look-Ahead Unit Commitment (LAUC) with the consideration of load uncertainty. Instead of only covering limited number of scenarios in the uncertainty set, TSRO provides a robust solution that immunizes all possible scenario realizations. Linear decision rule (LDR) and two-stage decomposition approaches are considered respectively to solve TSRO in this research. We test the scalability and sensitivity of the proposed models and algorithms with the PJM market data. Finally, the computational results indicate that the proposed TSRO framework provides sufficient ramping capability and improves the security of the large-scale power grid system.