Linear diophantine uncertain linguistic-based prospect theory approach for performance evaluation of islanded microgrid-system scenarios.

Renewable-energy-based hybrid microgrids can aid in achieving one of the United Nations Sustainable Development Goals, i.e. 'Affordable and clean energy'. However, experts may be faced with the challenge of selecting the best one for the electrification of an area. To avoid the challenge and realize the ultimate goal of the United Nations, the present study, therefore, proposes a novel prospect theory-based decision-making approach to help experts in opting for the best microgrid scenario. The proposed decision-making framework considers the risk appetite of the decision-maker, a quintessential aspect of the process. Linear diophantine uncertain linguistic sets are used to model the linguistic evaluations from the experts. The information from different experts is aggregated using a linear diophantine uncertain linguistic power Einstein-weighted geometric operator. Finally, the prospect-theory-based TOmada de Decisao Interativa Multicriterio approach is employed to evaluate the performance of the available microgrid scenarios and hence opt for the best microgrid scenario. The proposed framework has been used to evaluate the performance of seven possible microgrid scenarios and hence select the best one that can be implemented for rural electrification of a remote village in Assam, India. The microgrid scenario consisting of a photovoltaic–wind turbine–fuel cell–battery converter (MG₃) has been revealed to be the best scenario among the seven considered microgrid scenarios. The validity of the obtained ranking results has been adjudged through a comprehensive evaluation regarding the attenuation factor and the weights of the criteria. Moreover, previous case studies have also been solved using the proposed methodology and the results reveal a good correlation between the obtained ranking results. [ABSTRACT FROM AUTHOR]