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An overview of medium- to long-term predictions of global wave energy resources

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  • Zheng, Chong Wei
  • Wang, Qing
  • Li, Chong Yin

Abstract

Against a backdrop of increasing energy demand, the development of wave energy technology is a logical means of both meeting this demand and mitigating the environmental degradation associated with conventional power generation. Previous research has made considerable progress in the climatic characterization and short-term forecasting of wave energy. However, medium- to long-term predictions of wave energy resources, which are central to the development of future operating and trading strategies, remain scarce. This study provides an overview of long-term climatic trends and medium- to long-term predictions of wave energy, before discussing the focus of future predictions. Finally, a new method is proposed for predicting wave energy resources on a medium- to long-term basis that incorporates the swell index and propagation characteristics of swell energy. This model was developed with the aim of improving the precision of wave energy predictions, thereby providing a reference for the effective utilization of wave resources. The results of this study demonstrate that long-term climatic trend analysis should include not only variations in wave power density (WPD), but also long-term variability in wave energy stability, energy level occurrence, and variability in the occurrence of effective significant wave height (SWH). The medium- to long-term prediction of wave energy should also synthetically consider the above factors. We conclude that monitoring the propagation of swell energy and calculating the swell index constitutes a robust theoretical basis for predicting the WPD of mixed wave.

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  • Zheng, Chong Wei & Wang, Qing & Li, Chong Yin, 2017. "An overview of medium- to long-term predictions of global wave energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1492-1502.
    • Handle: RePEc:eee:rensus:v:79:y:2017:i:c:p:1492-1502
    DOI: 10.1016/j.rser.2017.05.109
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