Planning for offshore wind: An integrated smart approach combining NREL classification and TOPSIS - Badr El Kihel; Nacer Eddine El Kadri Elyamani (Results in Engineering, 2025)
Development of offshore wind farms requires consideration of complex parameters, including maritime conditions, coastal distance, water depth, and seabed stability, with significant differences compared to onshore configurations. The current assessment evaluates offshore wind energy potential through integration of critical technical and economic factors. Evaluation covers 25 selected locations, including five operational sites: P1(China), P6 (Denmark), P8 (USA_01), P11 (England), and P19 (France). The proposed analytical framework combines statistical modelling with multi-criteria decision analysis for comprehensive site evaluation. Wind potential is classified according to NREL standards, and sites with insufficient energy output are excluded. Wind modelling is based on the Weibull distribution. Among the nine methods evaluated for estimating the k and c parameters, the Maximum Likelihood Method, the Least Squares Method, and the WAsP Method provided the most accurate performance. Derived parameters are incorporated into a TOPSIS-based multi-criteria analysis using indicators such as wind speed, power density, capacity factor, water depth, and proximity to shore. Evaluation results confirm strong alignment between predictions and operational values for sites such as P6 and P19. Substantial positive deviations are observed for sites P1 and P11, reflecting underutilized wind resources with potential for optimization through advanced turbine technology. Production costs range between 0.008 and 0.028 $/kWh, revealing economic disparities among sites. Site P4 (Canada) demonstrates consistent top-tier performance across five sensitivity scenarios with varying weightings. Integration of NREL classification with TOPSIS proves effective in offshore wind prioritisation. The system enhances sustainable energy planning through high-precision assessment and balanced evaluation of technical and economic indicators.