Sun-blocking index from sky image to estimate solar irradiance

Abstract

To optimize the balance between indoor comfort and minimal energy usage, several automated methods have been proposed for smart window control systems. However, owing to the high variability of solar irradiance, it is difficult for window controllers to operate properly. The variability of solar irradiance is mostly caused by cloud motion in the sky. Cloud information can be obtained from human observations, satellite images, and sky images, and parameters such as cloud amount, cloud fraction, and cloud cover (CC) have been conventionally used for considering cloud effects. These conventional parameters focus only on the amount of cloud over the entire sky while failing to account for the amount of cloud locally around the sun disk. Consequently, rapid changes in the cloud at short time scales have not been considered properly, and the high variability of solar irradiance has not been addressed accurately. Therefore, in this study, a new parameter, the sun-blocking index (SBI), is introduced to model the partial blocking of the sun by clouds and hence enhance the estimation accuracy of solar irradiance under fickle weather. In addition, an image processing model to calculate SBI using sky images was proposed. Once the correlation between the clearness index and SBI is established, the SBI-dependent clearness index is applied to solar radiation models. The results showed that the global horizontal irradiance was estimated with a relative root-mean-square error (rRMSE) of 16.21%. Remarkably, when direct normal irradiance (DNI) was estimated, the proposed model outperformed conventional models with rRMSE of less than 28%. • Partial blocking of the sun by cloud is considered for assessing solar irradiance. • The sun-blocking index (SBI) is proposed to measure the partial blocking. • A methodology for calculating the SBI from sky images is developed. • The relationship between SBI and clearness index is investigated. • Solar irradiance is more accurately estimated via the SBI-dependent clearness index.