New Stochastic Scheduling Framework Optimizes Variable-Speed Pumped Storage Hydropower

Variable-speed pumped storage hydropower (VS-PSH) offers long-duration energy storage but faces operational challenges due to head-dependent nonlinearities, discrete mode transitions, and energy-continuity constraints. A new study by Kyung-bin Kwon, SangWoo Park, and Dam Kim presents a stochastic framework that uses a multi-segment bidding structure to generate market-consistent energy and synchronized reserve offers. The framework is formulated as a stochastic mixed-integer linear programming (MILP) problem that explicitly models physical constraints, including head-dependent capability limits, discrete pumping and generating modes, and state-of-charge (SoC) and head dynamics. Price uncertainty is captured through scenario-based modeling that scales base-case prices and allows variations in charging/discharging incentives.

The stochastic MILP produces optimal energy and mode schedules that maintain feasible SoC trajectories across all scenarios, ensuring physically realizable operating strategies. Case studies under different levels of price variability demonstrate that the framework effectively coordinates energy arbitrage with reserve provision, proving operational feasibility and market applicability. The results highlight the significant operational and economic value of VS-PSH as a grid-scale energy storage resource, particularly in managing uncertainty while providing both energy and ancillary services.