We formalized the idea using an optimization model that blends predefined protocols over time to minimize operating cost under real market conditions. Because structured candidate protocols limit per-device flexibility, combined operation inevitably sacrifices some idealized flexibility; accordingly, we evaluate candidate protocols so that resulting schedules reflect operational realities rather than idealized “fully flexible” scenarios. To further approach the ideal without exceeding device constraints, we also introduce time partitioning: within coarse scheduling “slots,” each device follows its assigned routine or remains offline. Case studies with electrolyzer fleets show that coordinating parallel devices under structured protocols can approach the performance of an ideal, fully flexible resource. As fleet size increases, the economic gap to the fully flexible benchmark narrows, suggesting that combinations of simple load shapes can approximate complex demand trajectories. Such behavior is examined across day-ahead and real-time markets and regions such as ERCOT and CAISO, with comparisons of protocol types (rectangular, triangular, Gaussian-like) indicating where each performs best under prevailing price signals and operational priorities. Adjusting slot duration and device participation balances baseload-like steadiness and greater responsiveness, improving economic outcomes relative to a pure baseload approach without subjecting individual units to continuous, high-frequency ramping. Together, these case studies serve one objective: to demonstrate that structured, fleet-based operation can approximate a fully flexible resource across diverse price signals and regions.
As future work, we aim to develop a practical, durability-aware basis for monetizing flexibility. We will integrate real-world degradation data into market scheduling to align grid requirements with asset longevity and quantify and explore the trade-off between flexibility and durability from the economic viewpoint. Specifically, we aim to assess whether durability improvements can compensate for the inherent flexibility limits of structured protocols.