Fuzzy Delphi method for evaluating hydrogen production technologies

Abstract The purpose of this research is to establish an evaluation model for selecting the most appropriate technology for development in Taiwan, based on 14 evaluation criteria. Due to the inherent uncertainty and imprecision associated with the mapping of decision makers’ perception to crisp values, linguistic variables are used to assess the weights of the criteria and the ratings of each technology with respect to each criterion. The criteria weights and technology ratings are collected through a seven-point linguistic scale using a Delphi questionnaire. The linguistic scores are then converted into fuzzy numbers, and a consensus of the decision makers’ opinions on weights and ratings is mathematically derived using fuzzy Delphi methodology. We have used the model to evaluate seven different hydrogen production technologies. The results indicate that hydrogen production via electrolysis by wind power and that via electrolysis by photovoltaic electricity are the two technologies that should be chosen for further development.

[1]  R. L. Sawhney,et al.  Comparison of environmental and economic aspects of various hydrogen production methods , 2008 .

[2]  Ying-Feng Kuo,et al.  Constructing performance appraisal indicators for mobility of the service industries using Fuzzy Delphi Method , 2008, Expert Syst. Appl..

[3]  V. E. Zhukovin,et al.  A Fuzzy Multicriteria Decision Making Model , 1987 .

[4]  Naim Afgan,et al.  MULTI-CRITERIA ASSESSMENT OF NEW AND RENEWABLE ENERGY POWER PLANTS , 2002 .

[5]  A. T. Holen,et al.  A Norwegian case study on the production of hydrogen from wind power , 2007 .

[6]  Madan M. Gupta,et al.  Introduction to Fuzzy Arithmetic , 1991 .

[7]  Norman C. Dalkey,et al.  Experimental Assessment of Delphi Procedures with Group Value Judgments , 1971 .

[8]  S. Dunn.  Hydrogen Futures: Toward a Sustainable Energy System , 2001 .

[9]  Naim Afgan,et al.  Sustainability assessment of hydrogen energy systems , 2004 .

[10]  Marc A. Rosen,et al.  Comparative efficiency assessments for a range of hydrogen production processes , 1998 .

[11]  George Wright,et al.  Delphi: A reevaluation of research and theory , 1991 .

[12]  Chiu-Yue Lin,et al.  Fermentative hydrogen production from xylose using anaerobic mixed microflora , 2006 .

[13]  Victor B. Kreng,et al.  The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection , 2010, Expert Syst. Appl..

[14]  M Momirlan,et al.  Current status of hydrogen energy , 2002 .

[15]  J. Murry,et al.  Delphi: A Versatile Methodology for Conducting Qualitative Research , 2017 .

[16]  R. Allen,et al.  A figure of merit assessment of the routes to hydrogen , 2005 .

[17]  Norman Crolee Dalkey,et al.  An experimental study of group opinion , 1969 .

[18]  Gwo-Jen Hwang,et al.  A Delphi-based approach to developing expert systems with the cooperation of multiple experts , 2007, Expert Systems with Applications.

[19]  N. Dalkey,et al.  An Experimental Application of the Delphi Method to the Use of Experts , 1963 .

[20]  Da Ruan,et al.  Evaluation of software development projects using a fuzzy multi-criteria decision approach , 2008, Math. Comput. Simul..

[21]  M. Adler,et al.  Gazing into the oracle : the Delphi method and its application to social policy and public health , 1996 .

[22]  Brian C. Twiss,et al.  Forecasting Technology for Planning Decisions , 1978 .

[23]  Naim Afgan,et al.  Energy system assessment with sustainability indicators , 2000 .

[24]  Naim Afgan,et al.  Multi-criteria evaluation of hydrogen system options , 2007 .

[25]  Ibrahim Dincer,et al.  Environmental and economic aspects of hydrogen production and utilization in fuel cell vehicles , 2006 .

[26]  G. Petrecca,et al.  A review of hydrogen applications: technical and economic aspects , 2008, 2008 International Symposium on Power Electronics, Electrical Drives, Automation and Motion.

[27]  Leo L. Pipino,et al.  A pilot study of fuzzy set modification of Delphi , 1985 .

[28]  Ching-Hsue Cheng,et al.  Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation , 2002, Eur. J. Oper. Res..

[29]  Tzeng Gwo-Hshiung,et al.  Application of multicriteria decision making to the evaluation of new energy system development in Taiwan , 1992 .

[30]  Madan M. Gupta,et al.  Fuzzy mathematical models in engineering and management science , 1988 .

[31]  M. Korpås,et al.  Value of combining hydrogen production with wind power in short-term electricity markets , 2008, 2008 IEEE 2nd International Power and Energy Conference.

[32]  P. A. Pilavachi,et al.  Evaluation of hydrogen production methods using the Analytic Hierarchy Process , 2009 .

[33]  Jiangjiang Wang,et al.  A fuzzy multi-criteria decision-making model for trigeneration system , 2008 .

[34]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[35]  Pei-Chann Chang,et al.  Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry , 2006, Expert Syst. Appl..

[36]  A. Ishikawa,et al.  The Max-Min Delphi method and fuzzy Delphi method via fuzzy integration , 1993 .