Optimizing wave energy converter benchmarking with a fuzzy-based decision-making approach

  • 0College of Technology and Design, University of Economics Ho Chi Minh City, Ho Chi Minh City, Vietnam.

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Summary

This summary is machine-generated.

This study ranks wave energy converter (WEC) technologies using MEREC and SF-CoCoSo methods. Grid connectivity and adaptability to wave conditions are key factors for successful marine renewable energy generation.

Area Of Science

  • Marine renewable energy
  • Ocean wave energy conversion
  • Sustainable energy technologies

Background

  • Growing demand for sustainable energy solutions drives interest in marine renewables.
  • Wave Energy Converters (WECs) are crucial for harnessing ocean wave power for electricity generation.
  • Objective assessment and benchmarking of WEC technologies are needed.

Purpose Of The Study

  • To objectively assess and benchmark Wave Energy Converter (WEC) technologies.
  • To provide a definitive ranking of WEC technologies based on defined criteria.
  • To identify key factors influencing the success of WEC technologies.

Main Methods

  • Utilized an integrated approach combining the MEthod based on the Removal Effects of Criteria (MEREC) and Spherical Fuzzy Combine Compromise Solution (SF-CoCoSo).
  • MEREC was used to systematically determine the importance of benchmarking criteria.
  • SF-CoCoSo synthesized complex decision-making data for technology evaluation.

Main Results

  • A definitive ranking of WEC technologies was established.
  • Grid connectivity emerged as a pivotal factor for WEC success.
  • Adaptability to various wave conditions was identified as crucial for WEC performance.

Conclusions

  • The study provides a robust framework for benchmarking WEC technologies.
  • Grid connectivity and environmental adaptability are critical for the viability of wave energy.
  • Future research should incorporate evolving market dynamics and explore additional multi-criteria decision-making (MCDM) methods.

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