Assessing technology portfolios of clean energy-driven desalination-irrigation systems with interval-valued intuitionistic fuzzy sets

Abstract In arid and semi-arid regions, there exist great potential for supplementing irrigation water with brackish water desalinated by clean energies. Determining technology portfolio is essential for the establishment of clean energy-driven desalination-irrigation (CEDI) systems, requiring multi-criteria group decision-making. Unfortunately, few existing methods were capable of assessing such a complex problem that involves multiple technologies and uncertainties. During multi-criteria group decision-making, uncertainty arising from linguistic information and varying confidence in estimation is usually available as interval-valued intuitionistic fuzzy sets (IVIFSs). Previous studies relied on the direct provision of IVIFSs by experts, which made them inapplicable in real-world problems because experts’ understanding over IVIFSs might be limited and inconsistent. Therefore, an easy-to-operate method for collection and conversion of IVIFSs was proposed in this study to avoid misunderstanding and facilitate realistic reflection of expert judgements. Duplex rating sets (DRSs) were proposed to express uncertain estimates and the associated confidence levels, and transformation equations were established to convert DRSs into IVIFSs. Based on the introduction of DRSs and transformation equations, an entropy-weighted TOPSIS approach with IVIFSs information was then developed. The developed method was then applied to northwest China for supporting the assessment of CEDI technology portfolios. The most desirable portfolio was screened out under the criteria of agriculture, ecology, economy, and system performance. Moreover, results of sensitivity analysis showed that the selected portfolio would perform the best in twelve of the total twenty scenarios. Without loss of generality, the developed method is also applicable for other decision-making problems involving multiple criteria, stakeholders and uncertainties.

[1]  Jun Zhang,et al.  Intuitionistic Fuzzy Multiple Criteria Group Decision Making: A Consolidated Model With Application to Emergency Plan Selection , 2019, IEEE Access.

[2]  E. Zavadskas,et al.  Performance evaluating of rural ICT centers (telecenters), applying fuzzy AHP, SAW-G and TOPSIS Grey, a case study in Iran , 2012 .

[3]  Mujahed Al-Dhaifallah,et al.  Fuel cell as an effective energy storage in reverse osmosis desalination plant powered by photovoltaic system , 2019, Energy.

[4]  R. Ragab,et al.  Strategies for managing saline/alkali waters for sustainable agricultural production. , 2005 .

[5]  A. Tenza-Abril,et al.  Agricultural irrigation of vine crops from desalinated and brackish groundwater under an economic perspective. A case study in Siġġiewi, Malta. , 2019, The Science of the total environment.

[6]  Zeshui Xu,et al.  Interval multiplicative transitivity for consistency, missing values and priority weights of interval fuzzy preference relations , 2010, Inf. Sci..

[7]  Cengiz Kahraman,et al.  A Comparison of Wind Energy Investment Alternatives Using Interval-Valued Intuitionistic Fuzzy Benefit/Cost Analysis , 2016 .

[8]  Giri Venkataramanan,et al.  Generation unit sizing and cost analysis for stand-alone wind, photovoltaic, and hybrid wind/PV systems , 1998 .

[9]  Bart Kosko,et al.  Fuzzy entropy and conditioning , 1986, Inf. Sci..

[10]  Jun Ye Multiple Attribute Group Decision-Making Methods with Completely Unknown Weights in Intuitionistic Fuzzy Setting and Interval-Valued Intuitionistic Fuzzy Setting , 2013 .

[11]  Ting-Yu Chen,et al.  Determining objective weights with intuitionistic fuzzy entropy measures: A comparative analysis , 2010, Inf. Sci..

[12]  M. Taha,et al.  Application potential of small-scale solar desalination for brackish water in the Jordan Valley, Palestine , 2018 .

[13]  Zeshui Xu,et al.  A VIKOR-based method for hesitant fuzzy multi-criteria decision making , 2013, Fuzzy Optimization and Decision Making.

[14]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[15]  George P. Huber,et al.  Multi-Attribute Utility Models: A Review of Field and Field-Like Studies , 1974 .

[16]  Rajesha Kumar,et al.  Desalination for agriculture: water quality and plant chemistry, technologies and challenges , 2018 .

[17]  Evangelos Triantaphyllou,et al.  An examination of the effectiveness of multi-dimensional decision-making methods: A decision-making paradox , 1989, Decis. Support Syst..

[18]  C. F. Schutte,et al.  Capacitive Deionization Technology™: An alternative desalination solution , 2005 .

[19]  J. R. Selman,et al.  Solar desalination with humidification-dehumidification cycle : Review of economics , 2006 .

[20]  Shoji Kimura,et al.  Analysis of data in reverse osmosis with porous cellulose acetate membranes used , 1967 .

[21]  Jean Pierre Brans,et al.  HOW TO SELECT AND HOW TO RANK PROJECTS: THE PROMETHEE METHOD , 1986 .

[22]  Khalid Z. Al-Subaie Precise way to select a desalination technology , 2007 .

[23]  Jun Ye Multicriteria fuzzy decision-making method using entropy weights-based correlation coefficients of interval-valued intuitionistic fuzzy sets , 2010 .

[24]  Deng-Feng Li,et al.  TOPSIS-Based Nonlinear-Programming Methodology for Multiattribute Decision Making With Interval-Valued Intuitionistic Fuzzy Sets , 2010, IEEE Transactions on Fuzzy Systems.

[25]  M. Nagaraju Naik,et al.  Review of solar photovoltaic water pumping system technology for irrigation and community drinking water supplies , 2015 .

[26]  Yanpeng Cai,et al.  Inexact fuzzy chance-constrained programming for community-scale urban stormwater management , 2018 .

[27]  Zeshui Xu,et al.  Entropy/cross entropy-based group decision making under intuitionistic fuzzy environment , 2012, Inf. Fusion.

[28]  Z. S. Xu,et al.  An Overview of Distance and Similarity Measures of Intuitionistic Fuzzy Sets , 2008, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[29]  Tadeusz Gerstaenkorn,et al.  Correlation of intuitionistic fuzzy sets , 1991 .

[30]  Volker Presser,et al.  Water desalination via capacitive deionization : What is it and what can we expect from it? , 2015 .

[31]  Massoud Tabesh,et al.  PROMETHEE with Precedence Order in the Criteria (PPOC) as a New Group Decision Making Aid: An Application in Urban Water Supply Management , 2012, Water Resources Management.

[32]  Renuka Mahajan,et al.  New measures of weighted fuzzy entropy and their applications for the study of maximum weighted fuzzy entropy principle , 2008, Inf. Sci..

[33]  Cengiz Kahraman,et al.  A novel Multiple Attribute Group Decision Making methodology based on Intuitionistic Fuzzy TOPSIS , 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[34]  Zeshui Xu,et al.  On distance and correlation measures of hesitant fuzzy information , 2011, Int. J. Intell. Syst..

[35]  M. Sabahi,et al.  Modeling and Control of a New Three-Input DC–DC Boost Converter for Hybrid PV/FC/Battery Power System , 2012, IEEE Transactions on Power Electronics.

[36]  Wei Yang,et al.  Climatic and anthropogenic impacts on water and sediment generation in the middle reach of the Jinsha River Basin , 2020, River Research and Applications.

[37]  C. Dai,et al.  Agricultural Water Management Model Based on Grey Water Footprints under Uncertainty and its Application , 2019, Sustainability.

[38]  Jian-qiang Wang,et al.  Some geometric aggregation operators based on log-normally distributed random variables , 2014, Int. J. Comput. Intell. Syst..

[39]  Humberto Bustince,et al.  Correlation of interval-valued intuitionistic fuzzy sets , 1995, Fuzzy Sets Syst..

[40]  L. Brownlow A General View , 1941 .

[41]  Yanpeng Cai,et al.  A non-probabilistic programming approach enabling risk-aversion analysis for supporting sustainable watershed development , 2016 .

[42]  Zeshui Xu,et al.  Intuitionistic Fuzzy Aggregation Operators , 2007, IEEE Transactions on Fuzzy Systems.

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

[45]  Humberto Bustince,et al.  Entropy on intuitionistic fuzzy sets and on interval-valued fuzzy sets , 1996, Fuzzy Sets Syst..

[46]  K. Atanassov,et al.  Interval-Valued Intuitionistic Fuzzy Sets , 2019, Studies in Fuzziness and Soft Computing.

[47]  B. Roy THE OUTRANKING APPROACH AND THE FOUNDATIONS OF ELECTRE METHODS , 1991 .

[48]  Peide Liu,et al.  A competency evaluation method of human resources managers based on multi-granularity linguistic variables and VIKOR method , 2012 .

[49]  Wei Wang,et al.  Estimation of spatiotemporal PM1.0 distributions in China by combining PM2.5 observations with satellite aerosol optical depth. , 2019, The Science of the total environment.

[50]  Joseph Shalhevet,et al.  Using water of marginal quality for crop production: major issues , 1994 .

[51]  Xu Xinwen,et al.  Effect of drip irrigation with saline water on the construction of shelterbelts for soil and groundwater protection in the hinterland of the Taklimakan Desert, China , 2017 .

[52]  Dražen Barković Decision making analysis , 1996 .

[53]  Jan T. Bialasiewicz,et al.  Power-Electronic Systems for the Grid Integration of Renewable Energy Sources: A Survey , 2006, IEEE Transactions on Industrial Electronics.

[54]  Qian Tan,et al.  A robust multi-objective model for supporting agricultural water management with uncertain preferences , 2020 .

[55]  J. F. Medeiros,et al.  NITROGEN, PHOSPHORUS AND POTASSIUM ACCUMULATION IN WATERMELON CULTIVARS IRRIGATED WITH SALINE WATER , 2018, Engenharia Agrícola.

[56]  Brian W. Baetz,et al.  Expert Systems in Municipal Solid Waste Management Planning , 1990 .

[57]  Chao Mei,et al.  Feasibility assessment of renewable energies for cassava irrigation in China , 2017 .

[58]  S. Camposeo,et al.  Ripening Indices, Olive Yield and Oil Quality in Response to Irrigation With Saline Reclaimed Water and Deficit Strategies , 2019, Front. Plant Sci..

[59]  C. Breyer,et al.  Assessing the potential for renewable energy powered desalination for the global irrigation sector. , 2019, The Science of the total environment.

[60]  Jian-qiang Wang,et al.  An outranking method for multi-criteria decision making with duplex linguistic information , 2012, Fuzzy Sets Syst..

[61]  Y. Oren,et al.  Capacitive deionization (CDI) for desalination and water treatment — past, present and future (a review) , 2008 .

[62]  Lini Mathew,et al.  Techno economic feasibility analysis of different combinations of PV-Wind-Diesel-Battery hybrid system for telecommunication applications in different cities of Punjab, India , 2017 .

[63]  Zeshui Xu,et al.  Projection Models for Intuitionistic Fuzzy Multiple Attribute Decision Making , 2010, Int. J. Inf. Technol. Decis. Mak..

[64]  J. Fletcher,et al.  Low cost desalination of brackish groundwaters by Capacitive Deionization (CDI) – Implications for irrigated agriculture , 2019, Desalination.

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

[66]  I. Karagiannis,et al.  Water desalination cost literature: review and assessment , 2008 .

[67]  Jun Ye,et al.  Two effective measures of intuitionistic fuzzy entropy , 2010, Computing.

[68]  Frédérique Bouvart,et al.  Comparison of life cycle GHG emissions and energy consumption of combined electricity and H2 production pathways with CCS: Selection of technologies with natural gas, coal and lignite as fuel for the European HYPOGEN Programme , 2009 .

[69]  S.A. Daniel,et al.  A novel hybrid isolated generating system based on PV fed inverter-assisted wind-driven induction Generators , 2004, IEEE Transactions on Energy Conversion.

[70]  Jin-Han Park,et al.  Correlation coefficient of interval-valued intuitionistic fuzzy sets and its application to multiple attribute group decision making problems , 2009, Math. Comput. Model..

[71]  D. Zarzo,et al.  Desalination and energy consumption. What can we expect in the near future , 2018 .

[72]  Zacharias B. Maroulis,et al.  Short-cut structural design of reverse osmosis desalination plants , 1997 .

[73]  Yanpeng Cai,et al.  An enhanced radial interval programming approach for supporting agricultural production decisions under dual uncertainties and differential aspirations , 2017 .

[74]  Jun Ye,et al.  Fuzzy decision-making method based on the weighted correlation coefficient under intuitionistic fuzzy environment , 2010, Eur. J. Oper. Res..

[75]  Janusz Kacprzyk,et al.  Entropy for intuitionistic fuzzy sets , 2001, Fuzzy Sets Syst..

[76]  Qian Tan,et al.  Robust fractional programming approach for improving agricultural water-use efficiency under uncertainty , 2018, Journal of Hydrology.

[77]  Zeshui Xu,et al.  Some similarity measures of intuitionistic fuzzy sets and their applications to multiple attribute decision making , 2007, Fuzzy Optim. Decis. Mak..

[78]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[79]  Yanpeng Cai,et al.  An export coefficient based inexact fuzzy bi-level multi-objective programming model for the management of agricultural nonpoint source pollution under uncertainty , 2018 .

[80]  V. Belessiotis,et al.  Water shortage and renewable energies (RE) desalination — possible technological applications , 2001 .

[81]  中華人民共和国国家統計局 China statistical yearbook , 1988 .

[82]  Jun Ye,et al.  Multicriteria fuzzy decision-making method based on a novel accuracy function under interval-valued intuitionistic fuzzy environment , 2009, Expert Syst. Appl..

[83]  Miguel A. Mariño,et al.  Fuzzy TOPSIS Multi-Criteria Decision Analysis Applied to Karun Reservoirs System , 2011 .

[84]  Gagandeep Kaur,et al.  Generalized Cubic Intuitionistic Fuzzy Aggregation Operators Using t-Norm Operations and Their Applications to Group Decision-Making Process , 2018, Arabian Journal for Science and Engineering.

[85]  I. Turksen Interval valued fuzzy sets based on normal forms , 1986 .

[86]  Zeshui Xu,et al.  Some geometric aggregation operators based on intuitionistic fuzzy sets , 2006, Int. J. Gen. Syst..

[87]  Hongfei Zheng,et al.  Energy analysis and experimental verification of a solar freshwater self-produced ecological film floating on the sea , 2018, Applied Energy.

[88]  S. P. Deshmukh,et al.  Performance Assessment of Solar Agricultural Water Pumping System , 2016 .

[89]  Wei Sun,et al.  Risk assessment of hydropower stations through an integrated fuzzy entropy-weight multiple criteria decision making method: A case study of the Xiangxi River , 2015, Expert Syst. Appl..

[90]  G. W. Murphy,et al.  Mathematical theory of electrochemical demineralization in flowing systems , 1967 .

[91]  Shahzad Faizi,et al.  Group Decision-Making for Hesitant Fuzzy Sets Based on Characteristic Objects Method , 2017, Symmetry.

[92]  Qiang Liu,et al.  Hydrological Responses to Climate and Land Use Changes in a Watershed of the Loess Plateau, China , 2019, Sustainability.