Zhang, Can, Du, Yang, Chen, Xiaoyang, and Lim, Eng Gee (2018) Cloud Motion Forecasting and Cloud Base Height Estimation Using Two Low-Cost Sky Cameras. In: Proceedings of the 2nd IEEE Conference on Energy Internet and Energy System Integration. 8582657. From: EI2 2018: 2nd IEEE Conference on Energy Internet and Energy System Integration, 20-22 October 2018, Beijing, China.

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Abstract

Passing cloud results in rapid irradiance changes. The intermittency of PV output power has drawn serious concern as the PV system installation increases. Consequently, power ramp-rate control (PRRC) is introduced as the regulation to limit significant power fluctuations. These requirements are driving an increasing demand for ultra short-term PV power forecasting. Sky imager has been used as an effective tool to predict the cloud motion, then to forecast the PV power. However, the high cost of sky imager system and low update frequency are still hindering its application in PRRC. The estimation of cloud base height (CBH) is also a challenging using sky imager. In this paper, a low-cost cloud motion tracking system has been developed. Ultra short-term cloud motion forecasting has been achieved in seconds level which can be used in PRRC application. The proposed cloud tracking method improves the forecasting accuracy by multiple cloud centroid tracking. Secondly, a novel sky camera based CBH estimation method is proposed. The effectiveness of the proposed CBH estimation method has been verified by experiment results.

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