An overview of medium- to long-term predictions of global wave energy resources
Chong Wei Zheng,
Qing Wang and
Chong Yin Li
Renewable and Sustainable Energy Reviews, 2017, vol. 79, issue C, 1492-1502
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.
Keywords: Wave energy; Climatic long-term trend; Medium- to long-term prediction; Wave power density; Wave energy stability; Energy level occurrence (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (27)
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DOI: 10.1016/j.rser.2017.05.109
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