MODELING AND VALIDATION OF MINUTE-SCALE SOLAR IRRADIANCE DIRECT AND DIFFUSE SEPARATION BASED ON MLP-GARSON MODEL

Zhang Qiyuan; Wang Lei; Chen Tianpeng; Xie Peng; Zhang Zhen; Quan Peng

doi:10.19912/j.0254-0096.tynxb.2022-0735

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (4) : 531-538. DOI: 10.19912/j.0254-0096.tynxb.2022-0735

MODELING AND VALIDATION OF MINUTE-SCALE SOLAR IRRADIANCE DIRECT AND DIFFUSE SEPARATION BASED ON MLP-GARSON MODEL

Zhang Qiyuan^1,2, Wang Lei¹, Chen Tianpeng¹, Xie Peng¹, Zhang Zhen^2,3, Quan Peng⁴

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Abstract

In order to simulate the solar radiation fluctuation on the minute scale, based on the 2018—2021 minute-scale radiation data of Changzhou city, Jiangsu province, the Garson weight algerithm is used to optimize the input characteristics of the model, and the time series data of the first 10-minute clearness index k_t are introduced as additional features to establish a new minute-scale separation model based on time series data and MLP neural network. On this basis, the parameters of three newly proposed minute-scale separation models, which are Engerer2 model, Starke model and Yang model, respectively, are locally optimized and verified by test experiments. The verification results show that the new model using time series data and MLP neural network can effectively extract solar radiation fluctuation information in a short time. The normalized root mean square error （e_nRMSE） of the new model is 10.690%. The accuracy of the new model is 17.08% higher than the Yang model.

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solar radiation / machine learning / neural network / separation modeling / volatility

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Zhang Qiyuan, Wang Lei, Chen Tianpeng, Xie Peng, Zhang Zhen, Quan Peng. MODELING AND VALIDATION OF MINUTE-SCALE SOLAR IRRADIANCE DIRECT AND DIFFUSE SEPARATION BASED ON MLP-GARSON MODEL[J]. Acta Energiae Solaris Sinica. 2023, 44(4): 531-538 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0735

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