An Integrated Single-Valued Neutrosophic Combined Compromise Solution Methodology for Renewable Energy Resource Selection Problem

被引:32
|
作者
Rani, Pratibha [1 ]
Ali, Jabir [2 ]
Krishankumar, Raghunathan [3 ]
Mishra, Arunodaya Raj [4 ]
Cavallaro, Fausto [5 ]
Ravichandran, Kattur S. [6 ]
机构
[1] Natl Inst Technol, Dept Math, Warangal 506004, Telangana, India
[2] SRM Inst Sci & Technol, Fac Engn & Technol, Dept Comp Sci & Engn, NCR Campus, Ghaziabad 201204, Uttar Pradesh, India
[3] Amrita Sch Engn, Dept Comp Sci & Engn, Coimbatore 641112, Tamil Nadu, India
[4] Govt Coll Jaitwara, Dept Math, Jaitwara 485221, Madhya Pradesh, India
[5] Univ Molise, Dept Econ, I-86100 Campobasso, Italy
[6] Rajiv Gandhi Natl Inst Youth Dev, Sriperumbudur 602105, Tamil Nadu, India
关键词
single-valued neutrosophic set; MCDM; SWARA; CoCoSo; renewable energy source selection; MULTICRITERIA DECISION-MAKING; FUZZY TOPSIS; ELECTRICITY-GENERATION; ENTROPY; TECHNOLOGIES; SYSTEMS; MODEL; SWARA; AHP; ALTERNATIVES;
D O I
10.3390/en14154594
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Optimal renewable energy source (RES) selection needs a strategic decision for reducing environmental pollutions, use of conventional resources, and improving economic development. In the process of RESs evaluation, several aspects like environmental, economic, social, and technical requirements play an important role. In addition, diverse factors affect the appropriate RES selection problem which adheres to uncertain and imprecise data. Thus, this selection process can be considered as a complex uncertain multi-criteria decision making (MCDM) problem. This study aims to introduce a novel integrated methodology based on Step-wise Weight Assessment Ratio Analysis (SWARA) and Combined Compromise Solution (CoCoSo) methods within single-valued neutrosophic sets (SVNSs) context, wherein the decision-makers and criteria weights are completely unknown. In the proposed approach, the criteria weights are determined by the SWARA method, and the most suitable RES alternative is determined by an improved CoCoSo method under the SVN context. Further, an illustrative case study of RES selection is considered to demonstrate the thorough execution process of the proposed method. Moreover, a comparison with existing methods is discussed to analyze the validity of the obtained result. This study performs sensitivity analysis with a various set of criteria weights to reveal the robustness of the developed approach. The strength of the proposed method is its practical applicability and ability to provide solutions under uncertain, imperfect, indeterminate, and inconsistent information.
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页数:23
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