TY - JOUR
TI - Evaluation of wave energy converters based on integrated ELECTRE approach
AU - Kang, D
AU - Suvitha, K
AU - Narayanamoorthy, S
AU - Sandra, M
AU - Pamucar, D
T2 - Expert Systems with Application
AB - The demand for renewable energy sources is growing rapidly as a result of increasing energy consumption, fossil fuel depletion, climate change, and environmental degradation. The tide is one of the main sources of renewable energy in the ocean because of its huge potential to be harnessed. Wave-energy converters (WECs) are a potential alternative to present energy sources, with an emphasis on improving efficiency and increasing energy. With the goal of improving the uncertainty inherent in data representation, the literature gradually uses various fuzzy extensions that handle fuzzy information in subjective evaluations and decision-making processes. single-valued neutrosophic probabilistic hesitant fuzzy sets (SVNPHFS), a recent extension of neutrosophic fuzzy sets, address limitations associated with membership functions and the representation of hesitancy in multi-criteria decision-making (MCDM) approaches. In the decision-making process, uncertainty is successfully handled by SVNPHFS. The objective of this study is to investigate and select a potential converter for a WEC power plant using SVNPHFS. Seven criteria for WECs are selected as potential sites for establishing a wave-energy power plant. The paper proposes a novel hybrid MCDM methodology. Fuzzy SWARA (Stepwise Weighted Assessment Ratio Analysis) is utilized for assigning weights to the criteria for WEC selection, and fuzzy ELECTRE (Elimination and Choice Expressing Reality) is used to determine the most suitable alternative using these criteria weights. The proposed technique identifies the point absorber in the first rank for the best wave-to-energy converter power plant as it generates a high amount of electricity compared to other alternatives. The result shows that the proposed model is more robust compared to other approaches.
DA - 2024/05//
PY - 2024
VL - 242
SP - 15
UR - https://www.sciencedirect.com/science/article/pii/S0957417423032955
DO - 10.1016/j.eswa.2023.122793
LA - English
KW - Wave
KW - Modeling
KW - Performance
ER -