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Wave Energy Resource Availability Assessment in the Philippines Based on 30-Year Hindcast Data

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Abstract

With the goal of evaluating the wave and wave energy conditions in the Philippines, the simulated wave nearshore (SWAN) model was used to estimate the wavefield using 30 years of cross-calibrated multi-platform (CCMP) wind field data (1987–2016). The spatiotemporal patterns of annual and monthly averaged significant wave heights and wave energy in the Philippines were analyzed based on the simulated data. Results showed that they had similar values; in particular, significant wave heights and wave energy were smaller in the south and southwest and higher in the north and northeast. A total of 12 representative points along the Philippine coast were selected to draw wave and wave energy roses. A directional analysis showed that the dominant wave was in the north north-east (NNE), northeast (NE), and east north-east (ENE) directions. Wave energy was mainly distributed in regions with an energy period between 1 and 10 s and significant wave heights between 0 and 4 m. To better utilize wave energy data in the Philippines, this paper studied the available and rich area of wave energy and analyzed the annual and monthly variability index of wave energy in the country. Moreover, the available significant wave heights of wave energy conversion devices (WECs) were set as 0.5–4 m, and the maximum annual average available wave energy occurred in the eastern Philippine Sea area, reaching 13 kW m−1. For the safety of WECs, extreme typhoon-induced wave conditions must be considered. Furthermore, the results showed that the maximum significant wave height and mean period over the 50-year return period reached 18 m and 15 s, respectively.

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Acknowledgements

The study was supported by the National Natural Science Foundation of China — Shandong Joint Fund (No. U17062 26), and the National Natural Science Foundation of China (No. 52171284).

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Correspondence to Sheng Dong.

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Wang, Z., Jiang, D., Dong, S. et al. Wave Energy Resource Availability Assessment in the Philippines Based on 30-Year Hindcast Data. J. Ocean Univ. China 22, 349–364 (2023). https://doi.org/10.1007/s11802-023-5044-4

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  • DOI: https://doi.org/10.1007/s11802-023-5044-4

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