Managing minority opinions in micro-grid planning by a social network analysis-based large scale group decision making method with hesitant fuzzy linguistic information

Abstract

The growth of global electricity demand has put forward higher requirements for power distribution networks. The high cost of the large-scale power system and the voice for the use of renewable energy impel the birth of the micro-grid which plays a complementary role in the power generation of large-scale power system. The construction of micro-grid planning is complex and many stakeholders’ opinions should be considered for a comprehensive evaluation. Furthermore, the development of social big data techniques, such as e-marketplace and e-democracy, makes experts have social relationships among them. This study aims to develop a consensus model to manage minority opinions for large-scale group decision making with social network analysis for micro-grid planning. To deal with the vague and uncertain features in complex micro-grid planning problems, experts are supposed to use hesitant fuzzy linguistic term sets to express their opinions. A social network analysis-based clustering method is introduced to classify experts. Besides, in a large-scale group decision making problem, the opinions of experts should be fully considered, especially the minority opinions. This model considers the minority opinions in a micro-grid planning problem and provides an approach to manage these opinions. Finally, we use an illustrative example concerning the micro-grid planning decision making in Ali district in Tibet to demonstrate the effectiveness and practicability of the proposed model.