4.7 Article

Location selection of offshore wind power station by consensus decision framework using picture fuzzy modelling

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 202, Issue -, Pages 980-992

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.08.172

Keywords

Location selection; Offshore wind power station site; Picture fuzzy set; Relative projection model; Consensus reaching process

Funding

  1. National Natural Science Foundation of China [71571193]

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Under the double pressure of global energy tightening and energy saving, new renewable energy sources, especially offshore wind power, have become considerably popular. To promote the development of offshore wind power projects, there has been an urgent push towards the research on selecting a satisfactory offshore wind power station site. However, existing methods have ignored the consensus problem embedded in the selection process. With the aim of addressing this issue, we devote our effort to developing a consensus decision framework. To this end, we employ the picture fuzzy set (PFS) to collect and describe large amounts of uncertain evaluation information for distinctive sites. Then, some relative projection models for PFSs are developed to support the determination of importance weights of groups of decision makers who are invited to evaluate the performance of alternative sites. Subsequently, a consensus reaching process is presented to guarantee that each group is satisfied with the final selection. Finally, the classical technique for order preference by similarity to an ideal solution method is extended to reasonably select the most suitable site without a subjective supply for criteria weights. A case study on the location selection of offshore wind power station illustrates the validity and applicability of the framework. Through this work, we believe that the models and methods in different phases of our framework can be valuably applicable to similar problems and significantly beneficial to the promotion of PFS theory. (C) 2018 Elsevier Ltd. All rights reserved.

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