Resilient Unit Commitment for Day-Ahead Market Considering Probabilistic Impacts of Hurricanes
Tianyang Zhao, Huajun Zhang, Xiaochuan Liu, Shuhan Yao, Peng Wang
Abstract
In the face of extreme events, e.g., hurricanes, the transmission systems, especially the transmission lines, are affected across time and space. To mitigate these impacts on the day-ahead market from a probabilistic perspective, a resilient unit commitment (UC) problem is formulated as a two-stage distributionally robust and robust optimization (DR&RO) problem. In the first stage, the commitment, energy, and reserves of generators are pre-scheduled to minimize the operational cost, responding to the worst load forecasting and line failure scenario in the operating day. The operating status of transmission lines are depicted by a novel uncertainty set with a distributionally chance constraint considering the repair of failed lines. This chance constraint is reformulated to its deterministic equivalence. Using both load shedding and generation curtailment, recourse problems are formulated in the second stage considering the time-varying operating status of transmission lines. The formulated DR&RO problem is solved using a hybrid Benders decomposition and column-and-constraint generation scheme. Simulations are conducted on the modified IEEE reliability test system (RTS) and two-area IEEE RTS-96 under hurricanes. Results verify the effectiveness of the proposed method, in comparison with prevalent two-stage stochastic and robust optimization methods.