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An enhanced cloud segmentation algorithm for accurate irradiance forecasting
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DOI：10.1016/j.solener.2021.03.061.png)
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Abstract
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This paper presents a novel approach to calculate cloud cover under any illumination conditions for short-term irradiance forecasting. A sky-imaging system, in parallel with an irradiance measurement, is set up to collect a database of sky images and irradiance readings. The colour space operations and various image segmentation methods are investigated to improve the visual contrast of the cloud component. Experimental results shows the effectiveness of applying the Normalized Blue-to-Red Ratio (NBRR) colour operation for high-illumination condition and the Red/Green channel for the low-illumination condition. The pre-processed sky images are then fed into Minimum Cross Entropy (MCE) adaptive thresholding segmentation, which effectively differentiates the sky and cloud components for all-sky images. The cloud fraction calculation is employed for the segmented images as an indication of cloud coverage. The proposed method demonstrates a positive linear correlation between cloud fraction and real-time irradiance data.
Keywords:
Sky-cloud segmentation
Solar irradiance forecasting
Cloud fraction
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