On the importance of degradation modeling for the robust design of hybrid energy systems including renewables and storage

Due to additional complexity and computational cost, most of the techno-economic analyses presented to date on hybrid energy systems overlooked the long-term performance decay of components. This study introduces a novel simulation approach that accounts for degradation effects while maintaining a reasonable computational cost, achieving a 88.5 % time reduction in comparison to complete physics-based models, while introducing only a 0.015 % error in estimating long-term impacts. The proposed approach is tested against standard simulation methods using a real-world case study, i.e., the upgrade of the hybrid energy system on the island of Tilos to achieve full energy self-sufficiency through photovoltaic and wind power, supported by a combination of Lithium-Ion batteries and a hydrogen chain (electrolyzer, compressor, tank, and fuel cell). The novel simulation approach was integrated into a stochastic optimization framework aimed at minimizing the cost of supplying the entire energy request from the island. The economic analysis is also supported by an in-depth market review of average prices for RES and storage components. First, and most importantly, the study demonstrates that accounting for components' degradation is an absolute requirement to get robust and sustainable energy systems capable of meeting the long-term demands of renewable energy systems. The proposed approach is shown to perfectly fit this scope. Results on then selected case study indicate that incorporating a hydrogen chain as seasonal storage leads to more cost-effective solutions, reducing the cost by 17.5 %. The comparison with a simplified method reveals that ignoring degradation can lead to substantial errors in estimating the energy cost (by an average of 10.2 %) and undersized designs: 103.1 % on average for the electrolyzer, 31.5 % for the H2 tank, 59.6 % for the battery, and up to 7.7 % for the fuel cell.