ADVANCE IN PREDICTION METHODS FOR SOLAR IRRADIANCE BASED ON MULTIPLE-FACTORS

Lan Kun; Wu Zhanbo; Zhao Zeni; Jia Lingyun; Yang Liu; Yun Sining

doi:10.19912/j.0254-0096.tynxb.2023-0148

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (5) : 593-601. DOI: 10.19912/j.0254-0096.tynxb.2023-0148

ADVANCE IN PREDICTION METHODS FOR SOLAR IRRADIANCE BASED ON MULTIPLE-FACTORS

Lan Kun¹, Wu Zhanbo², Zhao Zeni², Jia Lingyun², Yang Liu³, Yun Sining^2,4

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Abstract

Considering the instability and intermittent output of solar irradiance, the current research status of solar irradiance prediction was summarized and analyzed in this review paper. From the perspectives of prediction methods, fprediction procedures, input parameters, and evaluation metrics, this work conducts a detailed comparison and analysis of solar irradiance predictions across various regions and time scales. It has been found that the prediction methods based on time series, machine learning and hybrid system are the popular methods in the field of solar irradiance prediction.

Key words

solar irradiance / prediction / machine learning / time series / deterministic prediction

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Lan Kun, Wu Zhanbo, Zhao Zeni, Jia Lingyun, Yang Liu, Yun Sining. ADVANCE IN PREDICTION METHODS FOR SOLAR IRRADIANCE BASED ON MULTIPLE-FACTORS[J]. Acta Energiae Solaris Sinica. 2024, 45(5): 593-601 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0148

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