Autonomous marine pollution-monitoring platforms must operate for extended periods in remote, harsh sea environments with limited maintenance access, making power-source selection a critical design choice. This study develops a transparent multi-criteria decision-making (MCDM) framework to compare five candidate power options, hybrid systems, wave energy converters, photovoltaic modules, fuel cells, and small wind turbines, against criteria spanning technical performance, economic cost, and environmental impact. Criterion weights are derived objectively using the entropy method, and the alternatives are ranked using two complementary MCDM techniques: VIKOR, which identifies compromise solutions closest to an ideal point, and ELECTRE, an outranking approach based on concordance/discordance pairwise comparisons. Both methods consistently select hybrid power systems as the top option, with wave energy ranked second. Solar and fuel-cell solutions fall in intermediate positions, while small wind turbines rank lowest across evaluations. A sensitivity analysis that perturbs criterion weights by ± 10%, ± 20%, and ± 30% confirms that the ranking order remains stable over a broad range of weighting scenarios. The proposed entropy–VIKOR–ELECTRE framework provides a quantitative and defensible basis for selecting robust power systems for long-endurance autonomous marine pollution-monitoring deployments.
Qu et al. (Sat,) studied this question.