Synergistic integration of digital twins and sustainable industrial internet of things for new generation energy investments
[Display omitted] •Using DEMATEL for causal relationship analysis of determinants in digital twin performance.•Synergy of Quantum picture fuzzy rough sets & Quantum theory to enhance digital twin policies for renewables.•Criteria list based on TBL technique for evaluating social, environmental,...
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Veröffentlicht in: | Journal of advanced research 2024-12, Vol.66, p.39-46 |
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Format: | Artikel |
Sprache: | eng |
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•Using DEMATEL for causal relationship analysis of determinants in digital twin performance.•Synergy of Quantum picture fuzzy rough sets & Quantum theory to enhance digital twin policies for renewables.•Criteria list based on TBL technique for evaluating social, environmental, & economic impacts.•Importance of analyzing climatic conditions for risk identification & sustainable results.•Strong infrastructure & up-to-date tech crucial for accurate data analysis in digital twins.
This study aims to identify optimal digital twin policies for enhancing renewable energy projects. Through a comprehensive analysis, the research evaluates the potential of digital twins in the renewable energy sector while considering triple bottom line perspectives.
The study's main goal is to prioritize digital twin policies that can effectively boost renewable energy projects. The research aims to demonstrate the practical application and reliability of a proposed evaluation model.
Nine criteria, derived from literature review and triple bottom line viewpoints, are selected. Using the decision-making trial and evaluation laboratory (DEMATEL) methodology and Quantum picture fuzzy rough sets, criteria weights are determined. Quantum picture fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) evaluates sustainable industrial internet of things strategies in new-gen energy investments. VIsekriterijumska optimizcija i KOmpromisno Resenje (VIKOR) methodology enables a comparative assessment, and sensitivity analysis is conducted across nine cases.
Consistent outcomes across various methods validate the model's reliability. Ecosystem preservation carries the highest weight (0.1147), followed by resource policy optimization with digital twins (0.1139). Distributed energy resilience ranks first (RCi 0.576), closely followed by energy efficiency optimization (RCi 0.542).
This study underscores ecosystem preservation and efficient resource policies as pivotal for successful digital twin deployment in renewable energy projects. The findings highlight digital twins' potential contribution to environmental protection and ecosystem sustainability, emphasizing resource efficiency through their effective use. |
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ISSN: | 2090-1232 2090-1224 2090-1224 |
DOI: | 10.1016/j.jare.2023.11.023 |