A techno-economic and reliability-based co-optimization framework for wave energy technology selection and deployment

The selection of wave energy converters (WECs) and deployment locations presents a complex multi-criteria challenge that cannot be adequately solved by a single-objective optimization. This study introduces a multi-criteria techno-economic optimization framework that combines a calibrated SWAN model with multi-objective particle swarm optimization to optimize annual energy production, levelized cost of energy (LCOE), and a new resource stability index. The SWAN model achieved 𝑅 2 = 0.893 for significant wave height and 𝑅 2 = 0.957 for wave period in calibration. The framework has been applied to seven WEC technologies, including OWC, Pelamis, WaveDragon, CorPower, AquaBuoy, Oyster, and CETO. The resulting data indicate that optimal deployment sites favor intermediate-depth waters featuring lower wave flux rather than offshore zones with maximum wave energy, because deep-water locations are heavily penalized when minimizing the LCOE. Furthermore, a clear three-tier performance hierarchy emerged from the analysis. Tier 1, which includes OWC and WaveDragon, achieves the best overall balance across all three objectives. Tier 2 (CorPower, Oyster) and Tier 3 (CETO, Pelamis, AquaBuoy) technologies remain below the EER = 1 breakeven threshold across the full 40 to 80 $/MWh tariff range tested, with CETO’s EER of 0.88 at 80 $/MWh the closest to breakeven. A standalone financial assessment further confirmed negative net present values and a floor internal rate of return of −100% for WECs, indicating that none—including the Tier 1 technologies—is currently financially viable under the assumed conditions. This region-agnostic, transferable framework enables stakeholders to replace subjective scoring with rigorous, quantitative trade-off evaluation for emerging wave energy markets.