Fuzzy multi-objective optimization of the energy transition towards renewable energies with a mixed methodology

Abstract

Paper aims: the combination of the quality indices, a novel model called “Dynamic Growth Allocation Model (DGAM)”, Fuzzy Decision Making Theory (FDM), Analytical Hierarchy Process (AHP) and the Evolutive Particle Swarm Optimization (EPSO) is proposed. Originality: the multi-objective optimization (with uncertainty) of the Argentine energy transition is not sufficiently studied. This combined methodology in this problem was not published and it had good, relatively easy and fast results. Research method: the optimization indices (EROI, CO2, IC and RP), the methodology used (DGAM, FDM, AHP and EPSO) and its results are analyzed. Main findings: (i) the nuclear energy allowed the renewable transition; (ii) the fossil dismantling and the investment in biomass and wind are needed; (iii) the EROI depends on the good load factor, useful life and performance. Implications for theory and practice: It is sought a minimum Renewable Participation (RP) of 20% of Argentina with a sustainable energy matrix.