Optimal market-based dispatch of hydrogen hybrid power plant under sequential market clearing and price uncertainty

Hydrogen Hybrid Power Plants (HHPPs) play a key role in the energy transition, as their ability to transfer electricity over time facilitates the integration of renewable energy sources and supports grid stability and seasonal resource adequacy. Ensuring their economic viability is a prerequisite for large-scale deployment and requires operational strategies that are both optimal and market-consistent. This study proposes a deterministic multi-step Mixed-Integer Linear Programming (MILP) framework that explicitly reflects the sequential structure of European electricity markets, including wholesale markets (day-Ahead and intraday) and ancillary services such as Frequency Containment Reserve (FCR) and automatic Frequency Restoration Reserve (aFRR). Unlike deterministic simultaneous co-optimization approaches, the proposed model emulates real short-Term operation by solving consecutive market stages based on ex-Ante price forecasts, thereby capturing the temporal ordering and commitment constraints inherent to actual market participation. The framework derives realistic optimal dispatching and bidding strategies that maximize revenues across multiple markets while enhancing system flexibility and enabling effective peak load mitigation. The results highlight the importance of explicitly modelling market sequencing, as sequential clearing induces systematic deviations from pre-clearing schedules, requiring dynamic flexibility reallocation, and identifies ancillary services markets as the primary revenue driver.