Solar irradiance prediction with ground-based sky images to solve solar intermittencies - Goh, Kuen Luen (2016)
Solar intermittency is a critical issue that pullbacks the applications of solar photovoltaic generation in modern power systems. High precision short-term solar irradiance prediction is essential to foresee the ramp-down events due to weather change so that the system will be able to react accordingly and maintain the system stability and power quality. This thesis describes one of the methods for forecasting solar irradiance based on micro-scale information, i.e. sky images captured by Total Sky Imager (TSI). The sky images will be processed to determine the cloud cover and compared with 1-minute-ago sky image to analyze the cloud movement by using the optical flow algorithm. The cloud condition of the next minute will be predicted and consequently the solar irradiance values will be calculated based on the program developed in this program. The sample results taken in this project show that the program is able to forecast solar irradiance for the 1-minute forecast horizon with mean prediction error of 8.15%. Depending on different locations and applications, the same algorithm can be applied accordingly by calibrating the threshold value for the cloud determination algorithm and kt value for the solar irradiance calculation.