Two-Stage Robust Optimal Scheduling of a Park Microgrid Considering Tiered Carbon Trading and Source-Load Uncertainty

Abstract

The high penetration of renewable energy exposes park microgrids to bilateral uncertainty from photovoltaic (PV) output and load demand. This paper proposes a two-stage robust optimal scheduling method for park microgrids considering tiered carbon trading and source-load uncertainty. Budget uncertainty sets are adopted to characterize the bilateral uncertainty; with the demand response and energy storage schedules as first-stage decisions and the tie-line power and curtailment/shedding adjustments as second-stage decisions, a two-stage robust optimization model incorporating tiered carbon-trading costs and tie-line capacity constraints is established. An improved column-and-constraint generation (C&CG) algorithm with a worst-case-scenario-predicted initial cut pool is developed. Results show that the proposed method cuts the worst-case total cost by 4.6% and load shedding by 91.5% while maintaining the base-scenario total cost unchanged, and the first-iteration gap drops from 22.4% to 0.1%.