SOLAR IRRADIANCE FORECASTING MODEL BASED ON EMD-TCN FOR MULTI-ENERGY HEATING SYSTEMS

Yan Wenjie; Xu Zhijie; Xue Guixiang; Song Jiancai; Du Xinyu

doi:10.19912/j.0254-0096.tynxb.2022-1074

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (11) : 182-188. DOI: 10.19912/j.0254-0096.tynxb.2022-1074

SOLAR IRRADIANCE FORECASTING MODEL BASED ON EMD-TCN FOR MULTI-ENERGY HEATING SYSTEMS

Yan Wenjie¹, Xu Zhijie¹, Xue Guixiang¹, Song Jiancai², Du Xinyu³

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Abstract

Aiming at the problem that the non-stationary and non-linear of solar irradiance affects the operation efficiency and reliability of multi-energy heating system, this paper proposes a hybrid forecasting model of solar irradiance based on empirical mode decomposition （EMD） and temporal convolutional network （TCN） named EMD-TCN, which can extract the hidden features of non-linear and non-stationary of solar irradiance from meteorological data more accurately, and obtain better prediction accuracy. The proposed EMD-TCN model is used to predict solar irradiance at different time scales using hourly meteorological data, and compared with four mainstream deep learning prediction algorithms. The results show that the proposed solar irradiance prediction model has higher prediction accuracy and generalization ability.

Key words

temporal convolutional network / empirical mode decomposition / solar irradiance forecasting / multi-energy heating systems

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Yan Wenjie, Xu Zhijie, Xue Guixiang, Song Jiancai, Du Xinyu. SOLAR IRRADIANCE FORECASTING MODEL BASED ON EMD-TCN FOR MULTI-ENERGY HEATING SYSTEMS[J]. Acta Energiae Solaris Sinica. 2023, 44(11): 182-188 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1074

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