Techno-economic analysis of offshore renewable energy farms in Western Spain using fuzzy AHP & TOPSIS methodology

Fuzzy logic offers a novel solution to tackle uncertainty and complexity in selecting offshore energy systems. Unlike traditional methods that require precise data, fuzzy logic accommodates uncertain and subjective information, making it particularly useful for evaluating energy resources where factors like sea conditions, energy efficiency, cost, and environmental impacts are often imprecise. This study uniquely integrates fuzzy multi-criteria decision-making methods with regional data to evaluate offshore renewable energy options, addressing a gap in the literature regarding site-specific energy farm selection. Applying this framework to a real-life case study, the selection of the best offshore renewable energy farm (solar, wave, or wind) for the Cabo de Penas area in Spain is investigated due to its balanced potential across all three energy alternatives, as indicated by global atlases. Based on surveys with five academic experts, the study found that the most crucial criteria for investment were carbon footprint reduction (weight = 0.216) and GDP impact (weight = 0.091), while the least important were distance from shore (weight = 0.013) and shipping density (weight = 0.010). Among the main categories, technical factors were most significant (weight = 0.322) and social factors were least significant (weight = 0.081). The study aims to offer a model applicable to high-potential regions globally.