Prioritization of renewable energy for offshore ship charging stations based on intuitionistic fuzzy GLDS method: A case of China
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Summary
This summary is machine-generated.Selecting the best renewable energy for offshore ship charging stations (OSCS) is crucial. A fuzzy multi-criteria decision-making (MCDM) framework identified wind energy as the optimal choice, followed by solar and wave power.
Area Of Science
- Marine engineering
- Renewable energy systems
- Decision science
Background
- Offshore ship charging stations (OSCS) are essential for the growing demand for electric maritime transport.
- Selecting the optimal renewable energy source for OSCS is complex due to decision-making uncertainties and conflicting criteria.
Purpose Of The Study
- To develop a robust fuzzy multi-criteria decision-making (MCDM) framework for selecting the best renewable energy source for OSCS.
- To address challenges like ambiguous environments, diverse expert assessments, and criterion conflicts.
Main Methods
- Constructed a comprehensive criteria system for energy source evaluation.
- Utilized intuitionistic fuzzy sets (IFS) to model expert uncertainty.
- Introduced a novel expert weighting method based on evaluation quality.
- Employed generalized intuitionistic fuzzy weighted geometric interaction averaging (GIFWGIA) for aggregation.
- Determined criteria weights using CRITIC and SWARA II methods.
- Applied the gained and lost dominance score (GLDS) method for final ranking.
Main Results
- The proposed fuzzy MCDM framework effectively handled decision-making complexities.
- Wind energy was identified as the most suitable renewable energy source for OSCS.
- Solar and wave energy were ranked as secondary alternatives.
Conclusions
- The developed framework provides a reliable approach for selecting renewable energy for offshore infrastructure.
- Wind energy presents the most promising solution for powering offshore ship charging stations.
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