4.7 Article

Study of decision framework of wind farm project plan selection under intuitionistic fuzzy set and fuzzy measure environment

Journal

ENERGY CONVERSION AND MANAGEMENT
Volume 87, Issue -, Pages 274-284

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2014.07.001

Keywords

Wind farm project plan selection; Multi-criteria decision making (MCDM); Intuitionistic fuzzy number; Fuzzy measure; Compensatory problem of performance scores

Funding

  1. Fundamental Research Funds for the Central Universities [2014XS59]
  2. National Nature Science Foundation of China [71271085]
  3. National philosophy and social science foundation of Beijing [12JGB044]

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Project selection plays an important role in the entire life cycle of wind farm project and the multi-criteria decision making (MCDM) methods are very important in the whole wind farm project plan selection process. There are problems in the present MCDM methods decrease evaluation quality of the wind farm project plans: first, the information loss exists in the wind farm project plan evaluation process. Second, it is difficult to satisfy the independent assumption of the multi-criteria decision making methods used in the wind farm project plan evaluation in fact. Third, the compensatory problem of performance scores of the wind farm project plans is processed unreasonably. Hence the innovation points of this paper are as follows: first, the intuitionistic fuzzy numbers are used instead of fuzzy numbers or numerical values to reflect the experts' intuitive preferences to decrease the probability of information loss; second, the fuzzy measure is used to rate the important degrees of criteria in order to avoid the independent assumption and to increase the reasonability; third, the partial compensatory problem of performance scores is well processed by using intuitionistic fuzzy Choquet (IFC) operator and generalized intuitionistic fuzzy ordered geometric averaging (GIFOGA) operator. These operators can deal with the compensatory performance scores and non-compensatory performance scores respectively. Finally, a case study demonstrates the effectiveness of decision framework. (C) 2014 Elsevier Ltd. All rights reserved.

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