Distributionally Robust Bidding Strategy for Co-Located and Integrated Wind–PV–Storage Hybrid Resources in Day-Ahead and Real-Time Electricity Markets

With the growing demand for flexibility in emerging power systems, hybrid-resources characterized by the coordinated deployment of renewable generation and energy storage have become an increasingly important form of renewable-energy development and market participation. However, in a day-ahead–real-time dual-settlement electricity market, uncertainties in wind and photovoltaic (PV) generation not only affect day-ahead bidding revenues but also influence revenue realization through real-time deviation settlement and energy-storage dispatch. Focusing on price-taking hybrid resource operators, this paper compares two representative market participation models: co-located hybrid resources (CHRs) and integrated hybrid resources (IHRs). Separate two-stage distributionally robust optimization (DRO) models are developed for the two configurations. In the first stage, day-ahead bidding schedules are determined based on wind and PV generation forecasts. In the second stage, real-time recourse decisions and energy-storage dispatch are implemented according to the actual available renewable output, thereby coordinating day-ahead revenues, real-time deviation revenues, and deviation-penalty risks. An initial set of representative scenarios is constructed using Latin hypercube sampling combined with a Wasserstein-distance-based scenario reduction method. A scenario-probability confidence set defined by combined 1-norm and infinity-norm constraints is then employed to characterize wind–PV uncertainty. Numerical results demonstrate the effectiveness of the proposed models and methodology.