System-level maintenance strategy for offshore hybrid renewable energy systems based on cyclic non-homogeneous Markov Chain modelling

Abstract

The reliability of offshore hybrid renewable energy systems (HRES) is critical due to seasonal environmental variability, and mechanical degradation. In this paper, a HRES that integrates wind, wave and solar power into an offshore platform is considered. The system is modeled using a Cyclic Non-Homogeneous Markov Chain (Cyclic NHMC), which unlike Homogeneous Continuous Time Markov Chains (HCTMC) with constant transition rates, the Cyclic NHMC incorporates season-dependent degradation, failure, maintenance, and environmental transitions. Building on this model, a Seasonal Energy Demand-Based Maintenance (SEDBM) strategy is introduced to allocate preventive maintenance according to seasonal demand criticality and environmental stress. The framework is validated through an experimental case study using in situ Aegean Sea environmental data, together with technical system data and expert-supported degradation and maintenance rates. System performance is assessed using Expected Energy Produced (EEP), Loss of Load Probability (LOLP), and Expected Energy Not Supplied (EENS). The results show that the Cyclic NHMC provides season-specific adequacy insights that are not captured by a homogeneous benchmark. Under SEDBM, EEP increases across all seasons, while LOLP and EENS are reduced during the critical seasonal periods. A modest increase in load loss in spring is observed, reflecting the deliberate reallocation of maintenance effort.