Nowadays, the world is facing the dual crisis of the energy and environment, and renewable energy, such as wave energy, can contribute to the improvement of the energy structure of the world, enhance energy supply and improve the environment in the framework of sustainable development. Longterm prediction of the significant wave height (SWH) is indispensable in SWH-related engineering studies and is exceedingly important in the assessment of wave energy in the future. In this paper, the spatial and temporal characteristics of wave energy in the South China Sea (SCS), and adjacent waters are analyzed. The results show that there are abundant wave energy resources in the waters around the Taiwan Strait, the Luzon Strait, and the north part of the SCS with annual average SWH (SWH) of over 1.4 m and obvious increasing trend. Then, the SARIMA approach considers the relationship between the current time and the values, residuals at some previous time and the periodicity of the SWH series are proposed to forecast the SWH in the SCS and adjacent waters. The results obtained are promising, showing good performance of the prediction of monthly average SWH in the SCS and adjacent waters. INDEX TERMS SARIMA, long-term prediction, significant wave height (SWH). I. INTRODUCTION
In this study, a long-term assessment of the wave energy in the China Sea was performed for a 30-year time interval (1988–2017), using the model WAVEWATCH-III. The reliability of the wave simulation results was increased by means of longer time horizon data compared to other relevant studies in the China Sea. This analysis provided information on the regional distribution as well as on the monthly and seasonal variability. The exploitation and stability of wave energy were taken into consideration, so as to find the advantage of resource exploitation. Results indicated that values of significant wave height and wave power density had obviously differences compared with different months, especially in December with a maximum significant wave height of 2.7 m and 35 kW/m of wave power density. The minimum value of them appeared in May, was 1.0 m and 4.5 kW/m, respectively. The distribution of wave energy was abundant in winter and the poorest in summer. In winter, the significant wave height in most areas was above 1.8 m, while the maximum wave energy density in summer was only 1.2 m. As for the wave power density, in winter values in most areas were above 18 kW/m, while the maximum value in summer was only 12 kW/m. In sight of regional distribution, the highest wave energy potential was located in the Northern South China Sea, the East China Sea, the Ryukyu Islands waters, east of the Taiwan Island and the Luzon Strait, with coefficient of variation was within 2.0 and occurrence of exploitation was above 80%, whereas the Bohai Sea, the northern part of the Yellow sea, the Gulf of Thailand, and the Northern Bay were in poor contribution, with occurrence of exploitation was within 50%.
With increasing energy shortages and global warming, clean and renewable energy sources, such as wind and wave energy, have gained widespread attention. In this study, the third-generation wave model WAVEWATCH-III (WW3) is used to simulate wave height in the North Indian Ocean (NIO), from 2008 to 2017, using the wind data from the European Centre for Medium-Range Weather Forecasts Renalysis datasets. The simulated results show good correlation with data obtained from altimetry. Analysis of wind and wave energy resources in the NIO is carried out considering energy density, the exploitable energy, the energy density stability, and monthly and seasonal variability indices. The results show that most areas of the NIO have abundant wind energy and at the Somali Waters are rich in wave energy resources, with wind energy densities above 200 W/m2 and wave energy densities above 15 KW/m. The most energy-rich areas are the Somali Waters, the Arabian Sea, and the southern part of the NIO (wind energy density 350–650 W/m2, wave energy density 9–24 KW/m), followed by the Laccadive sea (wind energy density 150–350 W/m2, wave energy density 6–9 KW/m), while the central part of the NIO is relatively poor (wind energy density less than 150 W/m2, wave energy density below 6 KW/m).
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