A marine-based hybrid renewable energy optimization framework for cost and emission reduction in nearly zero-energy ports

Abstract This study investigates a marine-based hybrid renewable energy system (HRES) for port electrification, integrating wave and tidal energy with battery storage to support sustainable coastal infrastructure. A multi-objective optimization framework, utilizing a Genetic Algorithm (GA), is employed to simultaneously minimize the levelized cost of energy (LCOE) and the lifecycle carbon footprint (CF). The model is applied to a realistic port load profile and localized marine resource dataset, evaluating six system configurations under technical, economic, and environmental constraints. Results show that the optimal configuration achieves a 50.25% reduction in LCOE and an 88% reduction in CF compared to a conventional grid-based scenario, with a payback period of 7.64 years. Sensitivity analysis highlights system robustness against financial uncertainty, while emphasizing high sensitivity to marine resource variability and load dynamics. In contrast to previous studies centered on solar and wind energy, this research focuses exclusively on marine energy sources and integrates full lifecycle emissions, including embodied carbon, within the optimization process. A modular port archetype is introduced to facilitate replication across coastal sites with spatial limitations. The findings support marine-based HRES as a viable pathway for decarbonizing port operations within site-specific environmental boundaries.