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Selection of sustainable prime mover for combined cooling, heat, and power technologies under uncertainties: An interval multicriteria decision‐making approach
Author(s) -
Ren Jingzheng
Publication year - 2018
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.4050
Subject(s) - prime mover , sustainability , vagueness , interval (graph theory) , ranking (information retrieval) , multiple criteria decision analysis , prime (order theory) , selection (genetic algorithm) , ambiguity , computer science , engineering , process engineering , operations research , mathematics , mechanical engineering , artificial intelligence , fuzzy logic , programming language , ecology , biology , combinatorics
Summary This study aims at developing an interval multicriteria decision‐making method for helping the stakeholders to select the most sustainable prime mover for combined cooling, heat, and power (CCHP) technologies under uncertainties for promoting the sustainable development of CCHP system. The “interval best‐worst method,” which can address the vagueness and ambiguity existing in the judgments of the decision‐makers, has been developed for determining the weights of the evaluation criteria. The interval VIKOR method which can rank the alternatives with imprecise data has been used to prioritize the alternative prime movers for CCHP technologies. Four alternative prime movers including internal combustion engine, gas turbines, microturbines, and fuel cells were studied by the developed method, and the sustainability order of the 4 prime movers from the most sustainable to the least is fuel cells, microturbines, gas turbines, and internal combustion engine. Sensitivity analysis was also carried out to investigate the influences of the weights of the sustainability criteria on the sustainability ranking of the alternative prime movers, and the results reveal that the sustainability rankings are very sensitive to the weights of sustainability criteria.