A two-layer degradation-aware energy management framework for renewable power grids with battery and hydrogen storage

High renewable energy penetration supports sustainable power generation; however, intermittency, component aging, and long-term performance uncertainty may pose operational challenges for power systems. This study proposes a degradation-aware, two-layer framework that jointly evaluates short-term system operation and long-term component performance. In the first layer, the Tunicate Swarm Algorithm (TSA) determines system capacities and energy-sharing parameters for a 24-h period. An objective function includes operating costs, emissions costs, BESS costs, hydrogen system costs, demand response, and renewable energy curtailment. In the second layer, the optimized system and energy management strategy (EMS) parameters are transferred without re-optimization to a 365-day simulation under variable renewable generation and load. BESS energy/SOH, hydrogen inventory, PEM electrolyzer degradation, and PEM fuel-cell efficiency are updated continuously. The novelty lies in directly testing the long-term operational robustness of short-term optimized system and EMS decisions within a continuous annual power-balance model. Selected load and conventional generation data from the IEEE 24-bus RTS are used as reference inputs. At the same time, the RES capacities, BESS configuration, DRP parameters, and P2H–H₂ storage–PEMFC system are defined and adapted specifically for the present study. The results show that the BESS state of health decreases from approximately 1.00 to 0.9785 (yearly), while the average PEM electrolyzer effective conversion coefficient decreases from approximately 0.649 to 0.62. The integrated BESS and hydrogen storage structure also supports renewable power balancing under variable operating conditions. Thus, the proposed framework shows the long-term technical effects of short-term energy-management decisions in renewable power systems.