Multi-Criteria Decision-Making for Sustainable Energy Solutions
Summary
Multi‐Criteria Decision‐Making (MCDM) for sustainable energy integrates quantitative and qualitative factors to guide investments, policy and technology choices. By assessing economic costs, environmental impacts, technical performance and social acceptance, decision makers can balance trade‐offs and uncover optimal pathways. Advanced weighting methods—ranging from entropy‐based techniques to fuzzy logic—enable the explicit handling of uncertainty and stakeholder preferences. MCDM frameworks support diverse applications, from national energy transition planning to local microgrid design, and facilitate transparent deliberation among engineers, policymakers and community groups. Recent advances in computational implementation, such as parallel processing of high‐dimension data, have improved scalability and robustness. This holistic approach underpins the global drive towards decarbonisation by enabling evidence‐based selection of renewable sources, storage technologies and system configurations that align with sustainability objectives.
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Multi-Criteria Decision-Making for Sustainable Energy Solutions publication trend
The graph below shows the total number of articles in multi-criteria decision-making for sustainable energy solutions across all publications each year (not limited to Nature Index journals).
Technical terms
Multi‐Criteria Decision‐Making (MCDM): A structured process for evaluating alternatives against multiple, often conflicting, criteria.
Fuzzy Logic: A mathematical approach that models uncertainty and vagueness by allowing partial membership in sets.
Analytic Hierarchy Process (AHP): A method that decomposes complex decisions into hierarchies, using pairwise comparisons to derive criterion weights.
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS): A ranking method that identifies alternatives closest to the ideal solution and furthest from the nadir.
Entropy Weighting: An objective technique that computes criterion weights based on the diversity of data information.
References
- New distributed-topsis approach for multi-criteria decision-making problems in a big data context. Journal of Big Data (2023).
- Imprecise Shannon’s Entropy and Multi Attribute Decision Making. Entropy (2010).
- Integrating Multi-Criteria Decision-Making Methods with Sustainable Engineering: A Comprehensive Review of Current Practices. Eng (2023).
- Sustainable Energy Source Selection for Industrial Complex in Vietnam: A Fuzzy MCDM Approach. IEEE Access (2022).
- Sustainable prime movers selection for biogas-based combined heat and power for a community microgrid: A hybrid fuzzy multi criteria decision-making approach with consolidated ranking strategies. Energy Conversion and Management X (2022).
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