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Targeting the high frequency tail of wave spectra for energy harvesting in marine sensor networks

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  • Davidson, Josh
  • Nava, Vincenzo

Abstract

While the conventional philosophy of wave energy conversion is to target the large amounts of power in the peak of the input wave spectrum, this study proposes that for the application of powering marine sensor networks (MSNs), it is advantageous to target the high frequency tail of the wave spectrum. This strategy is predicated on two primary advantages: the spatial and temporal persistence of the wave energy resource in the high-frequency region and its compatibility with the resonance characteristics of smaller MSN devices. To identify the optimal frequency range for energy harvesting, we conducted a detailed analysis of wave spectra across multiple coastal locations. This involved calculating and comparing the power spectra at different frequencies, using data from long-term wave measurements. The high-frequency tail was defined by determining the frequency above which the energy content showed consistent temporal and spatial stability across all study sites. The quantification of available power was achieved by integrating the wave power spectrum over the identified frequency range. Our case study, focusing on the coast of Queensland, Australia, reveals that frequencies above 2.5 rad/s consistently offer a stable and persistent energy resource. The available power in this range is quantified, totalling an average of 60 W/m, with additional analysis provided within narrower sub-bandwidths to address the inherent narrow-bandedness of wave energy harvesters. This research provides critical insights for the design of efficient wave energy harvesters tailored to the needs of diverse marine environments.

Suggested Citation

  • Davidson, Josh & Nava, Vincenzo, 2024. "Targeting the high frequency tail of wave spectra for energy harvesting in marine sensor networks," Renewable Energy, Elsevier, vol. 237(PA).
    • Handle: RePEc:eee:renene:v:237:y:2024:i:pa:s0960148124016185
    DOI: 10.1016/j.renene.2024.121550
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    References listed on IDEAS

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    1. Shaikh, Faisal Karim & Zeadally, Sherali, 2016. "Energy harvesting in wireless sensor networks: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 1041-1054.
    2. Pelc, Robin & Fujita, Rod M., 2002. "Renewable energy from the ocean," Marine Policy, Elsevier, vol. 26(6), pages 471-479, November.
    3. Folley, M. & Whittaker, T.J.T., 2009. "Analysis of the nearshore wave energy resource," Renewable Energy, Elsevier, vol. 34(7), pages 1709-1715.
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