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An integrated intelligent decision support framework for the development of photovoltaic solar power.

Authors :
Bouraima, Mouhamed Bayane
Ayyıldız, Ertugrul
Badi, Ibrahim
Özçelik, Gökhan
Yeni, Fatma Betül
Pamucar, Dragan
Source :
Engineering Applications of Artificial Intelligence. Jan2024:Part A, Vol. 127, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

An emerging question for photovoltaic (PV) solar power development is how to ascertain the optimal choice from a finite set of available alternatives under numerous conflicting criteria as well as high levels of imprecise, vague, and uncertain information. For the first time, we investigate the prioritization of the alternatives for the development of PV solar power via the interval-valued intuitionistic fuzzy sets (IVIFSs), which show great power in capturing ambiguous, uncertain, and vague information, and mitigating information loss. This paper presents a novel integrated intelligent decision support system comprising of Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, Analytic Hierarchy Process (AHP), and Combined Compromise Solution (CoCoSo) within an interval-valued intuitionistic fuzzy (IVIF) framework. Four alternatives are considered. To rank these alternatives, twelve criteria are defined under four aspects of SWOT analysis based on literature review and discussion with decision-makers. Subsequently, the IVIF-AHP method is utilized to determine the weights assigned to each criterion and sub-criterion. Finally, the IVIF-CoCoSo method is employed to rank four alternatives. The results showed that giving proactive attention to mitigating potential adverse environmental impacts of PV solar systems is the most highly prioritized strategy for PV solar power development. The results of the comparative and sensitivity analyses showed that the proposed method generates highly robust outcomes. The formulated integrated intelligent decision support system can help energy policy authorities with a valuable resource to craft optimal techniques for developing PV solar power. • A novel integrated MCDM approach for the development of solar energy is presented. • Challenges to solar energy development are identified and evaluated. • Strategies to overcome these challenges are provided. • Sensitivity analysis is done to validate the stability of the integrated approach. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09521976
Volume :
127
Database :
Academic Search Index
Journal :
Engineering Applications of Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
173784932
Full Text :
https://doi.org/10.1016/j.engappai.2023.107253