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

Abstract 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.

[1]  M. Sugeno.  FUZZY MEASURES AND FUZZY INTEGRALS—A SURVEY , 1993 .

[2]  Birol Kılkış,et al.  An energy source policy assessment using analytical hierarchy process , 2012 .

[3]  M. Sugeno,et al.  Fuzzy Measures and Integrals: Theory and Applications , 2000 .

[4]  A. Clarke.  Wind farm location and environmental impact , 1989 .

[5]  Tyson John Weaver,et al.  Financial appraisal of operational offshore wind energy projects , 2012 .

[6]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[7]  Xiaohong Chen,et al.  Intuitionistic fuzzy Choquet integral operator for multi-criteria decision making , 2010, Expert Syst. Appl..

[8]  Amy H. I. Lee,et al.  Strategic selection of suitable projects for hybrid solar-wind power generation systems , 2010 .

[9]  Kang Sun,et al.  Using the analytic network process (ANP) to determine method of waste energy recovery from engine , 2013 .

[10]  Chunqiao Tan,et al.  Generalized intuitionistic fuzzy geometric aggregation operator and its application to multi-criteria group decision making , 2011, Soft Comput..

[11]  Keith W. Hipel,et al.  A fuzzy multicriteria model for comparing energy projects , 1987 .

[12]  Amy H. I. Lee,et al.  Multi-criteria decision making on strategic selection of wind farms , 2009 .

[13]  Jin-Soo Kim,et al.  Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP , 2010 .

[14]  Adiel Teixeira de Almeida,et al.  Minimizing the Compensatory Effect of MCDM Group Decision Additive Aggregation Using the Veto Concept , 2013, EMO.

[15]  Fausto Cavallaro,et al.  Fuzzy TOPSIS approach for assessing thermal-energy storage in concentrated solar power (CSP) systems , 2010 .

[16]  Denis Bouyssou,et al.  Some remarks on the notion of compensation in MCDM , 1986 .

[17]  Feargal Brennan,et al.  Multi-criteria assessment of offshore wind turbine support structures , 2011 .

[18]  David Arditi,et al.  Total quality management in the construction process , 1997 .

[19]  Divakaran Liginlal,et al.  Modeling attitude to risk in human decision processes: An application of fuzzy measures , 2006, Fuzzy Sets Syst..

[20]  Maurizio Cellura,et al.  Decision making in energy planning: the ELECTRE multicriteria analysis approach compared to a FUZZY-SETS methodology , 1998 .

[21]  Giuseppe Munda,et al.  The problem of windfarm location: A social multi-criteria evaluation framework , 2007 .

[22]  Ali Shanian,et al.  TOPSIS multiple-criteria decision support analysis for material selection of metallic bipolar plates for polymer electrolyte fuel cell , 2006 .

[23]  Ronald R. Yager,et al.  Intuitionistic fuzzy interpretations of multi-criteria multi-person and multi-measurement tool decision making , 2005, Int. J. Syst. Sci..

[24]  Wen Lea Pearn,et al.  A wind turbine evaluation model under a multi-criteria decision making environment , 2012 .

[25]  Amy H. I. Lee,et al.  A model for strategic selection of feeder management systems: A case study , 2010 .

[26]  D. Whitfield,et al.  Upland raptors and the assessment of wind farm impacts , 2006 .

[27]  Shahram Jadid,et al.  Economic-environmental energy and reserve scheduling of smart distribution systems: A multiobjective mathematical programming approach , 2014 .

[28]  Erwin Schmid,et al.  Assessing the economic wind power potential in Austria , 2013 .

[29]  M. Grabisch.  Fuzzy integral in multicriteria decision making , 1995 .

[30]  Diyar Akay,et al.  A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method , 2009, Expert Syst. Appl..

[31]  Francisco Rodrigues Lima Junior,et al.  A fuzzy inference and categorization approach for supplier selection using compensatory and non-compensatory decision rules , 2013, Appl. Soft Comput..