An integrated energy system modeling and decision support approach under uncertainty for refining National Commitments

Introduction Achieving climate neutrality is a central goal of European climate policy, with Member States establishing legally binding National Commitments (NCs) for decarbonization through their National Energy and Climate Plans (NECPs). However, achieving these commitments efficiently while accounting for national contexts, policy preferences, and uncertainties remains challenging. This study develops an operational framework to refine national decarbonization strategies by prioritizing investments in key measures. Methods A Decision Support System is developed by integrating highly granular simulations of the Greek energy system using the Low Emissions Analysis Platform (LEAP), under different NECP-based measures, with two fuzzy multicriteria analysis techniques. The Fuzzy Analytic Hierarchy Process (AHP) is used to assign weights to emissions, cost, energy dependency, and energy consumption criteria while accounting for uncertainty in preferences. The Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is then applied to rank simulated measures, accounting for data and/or modeling uncertainty. The framework is further assessed through robustness analyses of criterion weights and costs and comparisons with alternative multicriteria analysis methods. Results In a proof-of-concept application to Greece, using criterion weights provided by the modeling team, the prioritized package of decarbonization measures achieves the NECP's 2050 emissions level with fewer measures, lower cumulative emissions over the planning horizon, and lower implementation costs than the alternative strategy considered. Discussion The proposed framework supports the systematic prioritization of decarbonization investments while incorporating multiple policy criteria and uncertainties. Robustness analyses and comparisons with alternative multicriteria methods further assess the reliability of the resulting priorities. Since the criterion weights in this proof-of-concept application reflect the modeling team's preferences rather than those of policymakers or stakeholders, the prioritized package should be interpreted as an indicative set of options to inform and support policy deliberation, rather than as a substitute for it.