Two-stage robust co-optimization of energy and reserve scheduling for resilient distribution systems considering line reinforcement

In recent years, the resilience of distribution systems has faced challenges due to the increasing frequency of extreme weather events and the intensifying global effects of climate change. To mitigate the adverse effects of these weather occurrences, we propose a day-ahead energy scheduling and line reinforcement strategy designed to address day-ahead spare capacity scheduling during extreme weather conditions, while also accommodating the unpredictability associated with such events. Initially, we integrate a rapid power regulation model for photovoltaic (PV) power plants to enhance the swift regulation of new energy sources. Subsequently, we develop a two-stage robust planning approach aimed at minimizing both load shedding and dispatch costs amidst extreme weather uncertainties. It enhances the system resilience, lowering load shedding by 7.8 %. Finally, the proposed model is decomposed into master and subproblems and solved iteratively through the application of nested column-and-constraint generation (NC&CG) algorithm. Numerical results demonstrate that the proposed approach improves economic efficiency by reducing the total investment by 3.8 % and the day-ahead cost by 3.05 %, as well as enhancing the system resilience by mitigating potential load shedding under extreme conditions.