Real-time health-aware emergency optimisation scheduling under fault scenarios in PV-fuel cell microgrids

This study focuses on emergency scheduling for a photovoltaic-fuel cell hybrid microgrid under fault conditions, and proposes an online optimisation strategy that integrates model predictive control (MPC) and mixed-integer linear programming (MILP).The method coordinates the management of fuel cell output, energy storage charging/discharging constraints, photovoltaic power curtailment, and interruptible load shedding within a rolling time horizon.It also incorporates the fuel cell health cost into the objective function to mitigate the stress caused by frequent start-stop operations and rapid power ramping.Simulations based on MATLAB/ YALMIP/Gurobi demonstrate that the proposed strategy can restore power balance and ensure zero interruption for critical loads within 20 seconds under typical scenarios such as photovoltaic power drop, load surge, single machine outage, and multi-fault compound disturbances.Compared to the baseline droop strategy, the approach significantly reduces photovoltaic curtailment, maintains the state of charge (SOC) within a safe range, and substantially decreases health costs and power fluctuations (30-49%) reduction in representative scenarios), validating the efficiency and robustness of the method under complex disturbances.