Optimising sustainable renewable energy portfolios using a multi-tolerance fuzzy goal programming approach

The application of fuzzy multi-objective decision-making (F-MODM) to the optimization problems of renewable energy (RE) planning with uncertainties has become increasingly popular, although it is still rare in contrast to the use of traditional multi-attribute decision-making (MADM) methods. This study contributes to the domain of F-MODM modeling and the empirical applications of RE. Methodologically, as a recent trend to enhance the solution quality of fuzzy goal programming (FGP) in F-MODM is to introduce the "tolerance" (or admissible violation) concept to membership functions (MFs), this study proposes a novel 'FGP-MT' (multi-tolerance FGP) model to overcome the limitations of 'single tolerance' during FGP modeling (i.e. being unable to fit complicated 'multitolerance' decision contexts and running the risk of missing better optimality). The model is first verified using a numerical example from the F-MODM literature. Empirically, an application of the FGP-MT model is then considered for a SREPO (sustainable renewable energy portfolio optimization) decision, searching for the optimal electricity generation portfolio from multiple RE resources in Algeria for sustainable RE development, subject to the special preference structure of the decision-maker (DM) that involves manifesting two or more tolerances for a fuzzy goal. As the model performs well or even better in determining the most suitable SREPO decision under this condition, insights are gained for the studied case, and future applications of the model are therefore expected.