基于SWAN模型的波浪能发电站选址研究

孙单勋; 杨智聪; 王卓恒; 綦晓; 邓慧; 欧阳建友

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

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (1) : 730-737. DOI: 10.19912/j.0254-0096.tynxb.2024-1593

基于SWAN模型的波浪能发电站选址研究

孙单勋¹, 杨智聪¹, 王卓恒¹, 綦晓¹, 邓慧¹, 欧阳建友²

作者信息 +

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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文章历史 +

摘要

针对现有波浪能电站选址策略单一的问题,提出一种基于SWAN数值模拟模型和平准化度电成本模型的新型波浪能电站选址策略,并应用研究区域的实际数据验证了该方法的可行性;为了进一步解决波浪能电站并网后可能对电网造成的不稳定性问题,采用BiTCN-BiGRU-Attention组合神经网络对最佳选址点的发电功率进行短期预测,可提高波浪能电站后期运营的稳定性。结果表明,该选址策略可为波浪能电站的合理选址与稳定运行提供科学依据。

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.

导出引用

孙单勋, 杨智聪, 王卓恒, 綦晓, 邓慧, 欧阳建友. 基于SWAN模型的波浪能发电站选址研究[J]. 太阳能学报. 2026, 47(1): 730-737 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1593

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

中图分类号： TM612

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