基于卫星遥感的辐照度时空关联映射与预测建模

王飞; 李娜; 苏营; 孙勇; 杨恒; 甄钊

doi:10.19912/j.0254-0096.tynxb.2022-1827

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (3) : 1-9. DOI: 10.19912/j.0254-0096.tynxb.2022-1827

基于卫星遥感的辐照度时空关联映射与预测建模

王飞¹, 李娜^1,2, 苏营³, 孙勇³, 杨恒³, 甄钊¹

作者信息 +

SPATIOTEMPORAL CORRELATION MAPPING AND PREDICTION MODELING OF IRRADIANCE BASED ON SATELLITE REMOTE SENSING

Wang Fei¹, Li Na^1,2, Su Ying³, Sun Yong³, Yang Heng³, Zhen Zhao¹

Author information +

文章历史 +

摘要

常规光伏电站仅能依赖局地地表气象观测信息进行辐照度预测,难以挖掘电站周边广域光伏资源的时空关联特性,限制了光伏电站辐照度以及发电功率的预测精度。针对上述问题,该文提出基于卫星遥感的光伏电站广域辐照度空间分布映射方法,并建立基于图卷积网络（GCN）的地表辐照度超短期时空关联预测模型,在充分利用多通道卫星数据的同时,考虑时空关联特性提高地表辐照度超短期预测精度。通过某光伏场站实例仿真分析,验证地表辐照度反演模型的可行性以及在此基础上所构建的辐照度时空关联预测模型的先进性。

Abstract

Conventional PV power stations can only rely on local surface meteorological observation information for irradiance forecasting, and it is difficult to tap the spatio-temporal correlation characteristics of wide area photovoltaic resources around the power station for these kinds of stations, which limits the forecasting accuracy of irradiance and PV power. To solve the above problems, this paper proposes a mapping method for the spatial distribution of wide area irradiance around PV power station based on satellite remote sensing, and establishes an ultra-short-term spatio-temporal correlation forecasting model for surface irradiance based on graph convolutional network （GCN）. The method makes full use of multi-channel satellite data and considers the spatio-temporal correlation characteristics to improve the ultra-short-term prediction accuracy of surface irradiance. The feasibility of the inversion model of surface irradiance is verified through the simulation analysis of a photovoltaic station, and the progressiveness of the corresponding spatial-temporal correlation prediction model is also proved.

导出引用

王飞, 李娜, 苏营, 孙勇, 杨恒, 甄钊. 基于卫星遥感的辐照度时空关联映射与预测建模[J]. 太阳能学报. 2024, 45(3): 1-9 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1827

Wang Fei, Li Na, Su Ying, Sun Yong, Yang Heng, Zhen Zhao. SPATIOTEMPORAL CORRELATION MAPPING AND PREDICTION MODELING OF IRRADIANCE BASED ON SATELLITE REMOTE SENSING[J]. Acta Energiae Solaris Sinica. 2024, 45(3): 1-9 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1827

中图分类号： TM615

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