COMBINED FORECASTING APPROACH OF PHOTOVOLTAIC POWER BASED ON CLOUD IMAGES AND CHAOTIC CHARACTERISTICS

Wang Yufei; Hao Deyang; Xue Hua; Mi Yang

doi:10.19912/j.0254-0096.tynxb.2022-1236

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (12) : 74-81. DOI: 10.19912/j.0254-0096.tynxb.2022-1236

COMBINED FORECASTING APPROACH OF PHOTOVOLTAIC POWER BASED ON CLOUD IMAGES AND CHAOTIC CHARACTERISTICS

Wang Yufei, Hao Deyang, Xue Hua, Mi Yang

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Abstract

To further improve the accuracy of ultra-short-term prediction of PV power under mutant irradiation scenarios caused by moving clouds, a combined prediction approach based on cloud images and chaotic characteristics is proposed. Firstly, by combining different ground-based cloud image feature extraction and matching algorithms, a two-stage calculation model of cloud motion velocity is established to precisely predict cloud distribution. Secondly, by taking advantage of the chaotic characteristics of irradiance time series, a dynamic modeling method of “ground-based cloud images-PV power” mapping relationship is proposed to accurately quantify the impact of cloud distribution on PV power. Finally, a cloud classification model based on support vector machines is used to develop the combined prediction method, and the effectiveness of the proposed approach is verified by simulation experiments.

Key words

photovoltaic power / forecasting / chaos theory / ground-based cloud images / cloud motion velocity / irradiance mapping model

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Wang Yufei, Hao Deyang, Xue Hua, Mi Yang. COMBINED FORECASTING APPROACH OF PHOTOVOLTAIC POWER BASED ON CLOUD IMAGES AND CHAOTIC CHARACTERISTICS[J]. Acta Energiae Solaris Sinica. 2023, 44(12): 74-81 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1236

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