Fuzzy AHP-GRA approach to evaluating energy sources: a case of Turkey

Since the demand for energy has dramatically increased in the countries which have fast-growing population and economy, they have faced with a critical problem of how to evaluate a set of potential energy sources (i.e. nuclear, natural gas, bio, geothermal, hydro, wind and solar) and choose the ultimate energy source for their needs. On the other hand, this critical problem turns into a multiple-criteria decision-making (MCDM) in the presence of a set of energy source alternatives and evaluation criteria. In literature, there are many MCDM methods introduced to solve for different kinds of problems. The purpose of this paper is to present an integrated approach for evaluating energy sources using fuzzy AHP and GRA, with a case for Turkey.,In this paper, the analytic hierarchy process (AHP) and grey relational analysis (GRA) methods are used because of their advantages for similar problems. On the other hand, due to the fact that the conventional AHP by a nine-point scale and GRA method using a scale with crisp values can be unable to handle to capture the right judgments of a decision-maker(s), to reflect the vagueness and uncertainty on the judgments of a decision-maker, the fuzzy logic is integrated with the AHP and GRA.,The contributions of the paper to the literature are given in two dimensions as follows: it presents an integrated approach for complex decision processes with subjective data or vague information; the proposed approach, the fuzzy AHP-GRA method for energy source selection, is unique for the related problem in literature. The results of the proposed model from the case of Turkey will help practitioners and experts of how to apply it to the similar problems in the field of energy management.,In short, in this paper, an integrated approach is proposed through the fuzzy AHP and the fuzzy GRA methods. As the fuzzy AHP is used to determine the weights of evaluation criteria, the fuzzy GRA is used to rank energy source alternatives.,In addition, a case study for Turkey is presented to show the applicability of the proposed approach for potential practitioners who are authority in the field of energy in public and private sectors.,On the other hand, the proposed approach, the fuzzy AHP-GRA for energy source selection can also be an intelligent tool for public and private energy companies in Turkey, as well as others in the world.,On the other hand, in this paper, to the best of the authors’ knowledge, the study contributes to the literature that the first time, they use the fuzzy alpha-cut AHP and GRA in fuzzy environment for energy source evaluation problem.

[1]  Peter I. Cowling,et al.  Fuzzy grey relational analysis for software effort estimation , 2010, Empirical Software Engineering.

[2]  Wen-Hui Chen,et al.  A grey‐based approach for distribution network reconfiguration , 2005 .

[3]  D. K. Banwet,et al.  Enlightening grey portions of energy security towards sustainability , 2017 .

[4]  Edmundas Kazimieras Zavadskas,et al.  Sustainable and Renewable Energy: An Overview of the Application of Multiple Criteria Decision Making Techniques and Approaches , 2015 .

[5]  M. Kabak,et al.  Prioritization of renewable energy sources for Turkey by using a hybrid MCDM methodology , 2014 .

[6]  Vipul Jain,et al.  An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis , 2012 .

[7]  Gui-Wu Wei,et al.  Gray relational analysis method for intuitionistic fuzzy multiple attribute decision making , 2011, Expert Syst. Appl..

[8]  Fatih Tüysüz,et al.  An Integrated Grey Based Multi-Criteria Decision Making Approach for the Evaluation of Renewable Energy Sources , 2016 .

[9]  Narges Banaeian,et al.  Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry , 2018, Comput. Oper. Res..

[10]  T. C. Chang,et al.  Grey relation analysis of carbon dioxide emissions from industrial production and energy uses in Taiwan , 1999 .

[11]  Yu-Jie Wang,et al.  Combining grey relation analysis with FMCGDM to evaluate financial performance of Taiwan container lines , 2009, Expert Syst. Appl..

[12]  Ruey-Hsun Liang Application of grey relation analysis to hydroelectric generation scheduling , 1999 .

[13]  Asha B. Chelani,et al.  Optimal selection of full scale tannery effluent treatment alternative using integrated AHP and GRA approach , 2011, Expert Syst. Appl..

[14]  San-yang Liu,et al.  A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection , 2011, Expert Syst. Appl..

[15]  Razman Mat Tahar,et al.  Selection of renewable energy sources for sustainable development of electricity generation system using analytic hierarchy process: A case of Malaysia , 2014 .

[16]  Wen-Shing Lee,et al.  Evaluating and ranking energy performance of office buildings using Grey relational analysis , 2011 .

[17]  Sue J. Lin,et al.  Grey relation analysis of motor vehicular energy consumption in Taiwan , 2008 .

[18]  M. G. Bhatt,et al.  A multi-attribute selection of automated guided vehicle using the AHP/M-GRA technique , 2011 .

[19]  Ümran Şengül,et al.  Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey , 2015 .

[20]  K. Palanikumar,et al.  Analysis on Drilling of Glass Fiber–Reinforced Polymer (GFRP) Composites Using Grey Relational Analysis , 2012 .

[21]  Alev Taskin Gumus,et al.  A Combined Fuzzy-AHP and Fuzzy-GRA Methodology for Hydrogen Energy Storage Method Selection in Turkey , 2013 .

[22]  Gin-Shuh Liang,et al.  Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment , 2011, Expert Syst. Appl..

[23]  G. Tonkay,et al.  Application of modified fuzzy ahp method to analyze bolting sequence of structural joints , 1995 .

[24]  I-Shuo Chen,et al.  A network hierarchical feedback system for Taiwanese universities based on the integration of total quality management and innovation , 2012, Appl. Soft Comput..

[25]  José Luis Míguez,et al.  The use of grey-based methods in multi-criteria decision analysis for the evaluation of sustainable energy systems: A review , 2015 .

[26]  Peng Wang,et al.  A hybrid method using experiment design and grey relational analysis for multiple criteria decision making problems , 2013, Knowl. Based Syst..

[27]  Cengiz Kahraman,et al.  Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul , 2010 .

[28]  M. Ramachandran,et al.  Application of multi-criteria decision making to sustainable energy planning--A review , 2004 .

[29]  K. Chiang,et al.  Optimization of the WEDM process of particle-reinforced material with multiple performance characteristics using grey relational analysis , 2006 .

[30]  Prasanta Kumar Dey,et al.  Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis , 2016, Comput. Oper. Res..

[31]  Ediz Atmaca,et al.  Evaluation of power plants in Turkey using Analytic Network Process (ANP) , 2012 .

[32]  Gui-Wu Wei,et al.  GRA method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting , 2010, Knowl. Based Syst..

[33]  Thomas L. Saaty,et al.  Decision Making, Scaling, and Number Crunching , 1989 .

[34]  Ching-Ter Chang Multi-choice goal programming model for the optimal location of renewable energy facilities , 2015 .

[35]  Zenonas Turskis,et al.  Multi-criteria analysis of electricity generation technologies in Lithuania , 2016 .

[36]  Heracles Polatidis,et al.  Renewable energy projects: structuring a multi-criteria group decision-making framework , 2003 .

[37]  Z. Ayağ,et al.  An analytic network process-based approach to concept evaluation in a new product development environment , 2007 .

[38]  Ming-Lang Tseng,et al.  Using linguistic preferences and grey relational analysis to evaluate the environmental knowledge management capacity , 2010, Expert Syst. Appl..

[39]  Shu-Ling Lin,et al.  Is grey relational analysis superior to the conventional techniques in predicting financial crisis? , 2011, Expert Syst. Appl..