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Application of statistical charts, multi-criteria decision making and polynomial neural networks in monitoring energy utilization of wave energy converters

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  • Tilottama Chakraborty

    (National Institute of Technology Agartala)

  • Mrinmoy Majumder

    (National Institute of Technology Agartala)

Abstract

The rise in the demand for energy from the burgeoning population has enhanced the importance of renewable energy resources to substitute conventional energy resources. In this regard, energy extracted from ocean waves is found to be one of the most reliable but expensive alternatives. The cost of installation and monitoring of wave energy converters are the reasons why it is not a popular alternative to replace fossil fuels. One of the major reasons for higher cost lies in the subjective methods adopted to monitor or predict the wave energy potential. Also very few studies were conducted to monitor the efficiency of the converters in utilization of the available potential. The present investigation is an attempt to propose an objective, unbiased and adaptive procedure to monitor as well as estimate the utilization efficiency of the wave energy converters. The method was experimented on the coastal regions of India, and the results encourage further application of the novel method.

Suggested Citation

  • Tilottama Chakraborty & Mrinmoy Majumder, 2019. "Application of statistical charts, multi-criteria decision making and polynomial neural networks in monitoring energy utilization of wave energy converters," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(1), pages 199-219, February.
    • Handle: RePEc:spr:endesu:v:21:y:2019:i:1:d:10.1007_s10668-017-0030-x
    DOI: 10.1007/s10668-017-0030-x
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    Cited by:

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    2. Dong, Lijun & Kang, Xiaojun & Pan, Mengqi & Zhao, Man & Zhang, Feng & Yao, Hong, 2020. "B-matching-based optimization model for energy allocation in sea surface monitoring," Energy, Elsevier, vol. 192(C).
    3. Francisco Haces-Fernandez & Hua Li & David Ramirez, 2022. "Analysis of Wave Energy Behavior and Its Underlying Reasons in the Gulf of Mexico Based on Computer Animation and Energy Events Concept," Sustainability, MDPI, vol. 14(8), pages 1-23, April.
    4. Javad Adeli & Mohammadreza Niknejadi & Davood Toghraie, 2020. "Full repowering of an existing fossil fuel steam power plant in terms of energy, exergy, and environmen for efficiency improvement and sustainable development," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(6), pages 5965-5999, August.

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