A Comparative Analysis of Weighting and Multi-Criteria Ranking Methods in Evaluating Onshore Wind Farm Siting

This research presents a comparative analysis of criteria weighting and multi-criteria decision-making methods in the framework of onshore wind farm siting. Nine criteria weighting and four multi-criteria decision-making ranking methods, constituting a total of thirty-six models, are assessed for the relative spatial siting suitability ranking of onshore wind farms in the Regional Unit of Euboea, Greece. To determine the weights of five selected assessment criteria (wind velocity, distance from protected areas, distance from road networks, distance from electricity network, and distance from settlements), five subjective methods, namely the Analytic Hierarchy Process, Rank Order Centroid, the Simos method, the Best–Worst method, and the Equal-Weight Method, and four objective methods, namely the standard deviation, the statistical variance procedure, Criteria Importance Through Inter-criteria Correlation, and the Entropy Weight Method, are used. Using each of the assessment criteria weights provided by these nine methods, the suitability ranking of onshore wind farms in the Regional Unit of Euboea (Greece) is obtained through four multi-criteria decision-making methods: the weighted sum method, the weighted product method, the Technique for Order Preference by Similarity to Ideal Solution, and the VIseKriterijumska Optimizacija I Kompromisno Resenje method. Spearman’s rank correlation coefficient measures the consistency among criteria priorities and alternative rankings, while weighting scheme scenario analysis assesses the impact of different weighting schemes on the final outcomes. Heatmap analysis and Borda count consensus ranking are employed to identify stable alternatives across various model combinations and reduce the influence of method-specific ranking extremes. Subjective methods for determining criterion weights yield the same prioritization of the assessment criteria, whereas the results from objective methods differ substantially. The selection of both criteria weighting and multi-criteria decision-making ranking methods influences the final prioritization of alternatives. The proposed methodological framework can help decision-makers detect uncertainty, prioritize cases for further assessment, and justify spatial siting decisions of wind farms more transparently.