A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems

Abstract

Hybrid energy systems (HESs) are becoming popular for standalone applications due to global concern regarding green house gas (GHG) emissions and depletion of fossil fuel resources. Research in the optimal design of HESs is ongoing, with numerous optimization techniques giving special emphasis to Pareto optimization, incorporating conflicting objectives. The subsequent decision-making process including the non-dominant set of solutions has yet to be addressed.

This work focuses on combining multi-objective optimization with a multi-criterion decision making (MCDM) technique to support decision makers in the process of designing HESs. Four different objectives, i.e., levelized energy cost (LEC), unmet load fraction, wasted renewable energy (WRE) and fuel consumption are used to obtain the Pareto front. A decision support tool based on Fuzzy TOPSIS and level diagrams is proposed to analyze the Pareto front and support the subsequent decision-making activity. A case study is used to illustrate the applicability of the proposed method. The study shows that the novel method is useful when determining the relative weights of objectives, providing a detailed picture of the objective space to the designer when coming up with the optimum system. The technique proposed in this study can be further extended to analyze similar problems in energy system design where MCDM is necessary after multi-objective optimization.