SITING STUDY OF WAVE ENERGY POWER PLANT BASED ON SWAN MODELING

Sun Shanxun; Yang Zhicong; Wang Zhuoheng; Qi Xiao; Deng Hui; Ouyang Jianyou

doi:10.19912/j.0254-0096.tynxb.2024-1593

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (1) : 730-737. DOI: 10.19912/j.0254-0096.tynxb.2024-1593

SITING STUDY OF WAVE ENERGY POWER PLANT BASED ON SWAN MODELING

Sun Shanxun¹, Yang Zhicong¹, Wang Zhuoheng¹, Qi Xiao¹, Deng Hui¹, Ouyang Jianyou²

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Abstract

To address the limitations of traditional siting strategies, a novel siting approach based on the SWAN numerical simulation model and the levelized cost of energy （LCOE） model is proposed. This method is validated using real-world data from the study area. Additionally, to mitigate potential grid instability issues caused by the integration of wave energy power stations, a hybrid neural network model, BiTCN-BiGRU-Attention, is employed to predict the short-term power generation at the optimal site, thereby enhancing the stability of subsequent operations. The results indicate that this siting strategy provides a scientific basis for the rational siting and stable operation of wave energy power stations.

Key words

wave power / neural networks / forecasting / levelized cost of electricity / SWAN model / power station siting

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Sun Shanxun, Yang Zhicong, Wang Zhuoheng, Qi Xiao, Deng Hui, Ouyang Jianyou. SITING STUDY OF WAVE ENERGY POWER PLANT BASED ON SWAN MODELING[J]. Acta Energiae Solaris Sinica. 2026, 47(1): 730-737 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1593

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