Multi-Criteria Decision Making in Wind Energy Systems

Multi-Criteria Decision Making (MCDM) in wind energy systems addresses the complex task of evaluating and ranking alternative sites, technologies and operational strategies according to a range of technical, economic, environmental and social criteria. Decision makers must balance wind resource quality, grid connection and infrastructure costs, environmental impact and community acceptance, often under conditions of deep uncertainty. Advances in spatial data analytics, fuzzy logic and stakeholder-driven preference elicitation have enabled more robust site suitability assessments and turbine selection processes. Life-cycle assessment and cost-benefit analysis have been integrated into multi-objective optimisation frameworks, supporting planners in selecting configurations that minimise carbon footprints, maximise energy yield and satisfy regulatory or land-use constraints. The global expansion of both onshore and offshore wind capacity has driven the development of decision-support platforms that combine geospatial information systems with interactive weighting tools, ensuring that investments align with sustainability targets and local priorities.

Research from Nature Portfolio

Recent studies have demonstrated the power of hybrid multi-objective optimisation frameworks in guiding offshore wind farm design. One approach integrates life-cycle assessment, capital and operational expenditures, and reliability metrics into a unified decision model, revealing trade-offs between environmental sustainability and cost efficiency. Another contribution introduced a spatial decision-support platform combining high-resolution meteorological and marine data with participatory stakeholder weighting, enabling planners to prioritise turbine layouts that reduce ecological impact and improve local acceptance. A further study applied an artificial intelligence-driven fuzzy decision framework to onshore wind site selection, automating the assignment of criteria weights based on historical project performance and expert judgements, thereby streamlining the evaluation of complex land-use, noise and visual-impact constraints.

Multi-Criteria Decision Making in Wind Energy Systems publication trend

The graph below shows the total number of articles in multi-criteria decision making in wind energy systems across all publications each year (not limited to Nature Index journals).

Technical terms

Analytic Hierarchy Process (AHP): A structured technique for organising and analysing complex decisions by decomposing them into a hierarchy of criteria and sub-criteria and deriving weights through pairwise comparisons.

Fuzzy Logic: A mathematical approach that handles uncertainty and imprecision by allowing partial membership of elements in sets, used to model expert judgements and linguistic assessments.

GIS (Geographic Information System): A computer system for capturing, storing, analysing and visualising spatial and geographic data, often employed in site suitability analyses.

Multi-Objective Optimisation: A process of finding solutions that simultaneously satisfy multiple objectives, typically involving trade-offs and Pareto-optimal frontiers.

Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS): A ranking method that identifies the alternative closest to the ideal solution and farthest from the nadir solution based on distance measures in a normalized decision space.

Life-Cycle Assessment (LCA): A methodology for assessing environmental impacts associated with all stages of a product’s life, from raw material extraction through to disposal.

References

1. A High-Resolution Wind Farms Suitability Mapping Using GIS and Fuzzy AHP Approach: A National-Level Case Study in Sudan. Sustainability (2021).
2. Multi-Criteria Decision-Making Approach for Selecting Wind Energy Power Plant Locations. Sustainability (2019).