基于地基云图的光伏功率超短期预测模型

A Very Short-term Prediction Model for Photovoltaic Power Based on Ground-based Cloud Images

以地基云图采集设备提供的实时日间彩色天空状况图像为研究对象，通过数字图像处理技术对时间序列图像进行了处理和分析，运用云团提取算法和跟踪学习算法实现对云团未来运动状况的预估，结合一天中太阳在云图像上的位置计算，预测未来时刻太阳的遮挡情况，进而预测辐照度和光伏功率的变化。研究结果表明，文中所述模型具有很好的可行性和实用性，为光伏电站0～4h超短期功率精确预测提供了方法。

The real-time and daytime color sky images captured by ground-based cloud imager are object of study, the time series images are processed and analyzed by digital image processing technologies. The estimation of cloud future motion is realized by using cloud extraction algorithm and cloud tracking and learning algorithm. The obstruction state of sun in the future time is predicted combining the location of sun in the cloud images in a day, and then the change of irradiance and photovoltaic power are predicted. The results show that the very short-term prediction model based on the ground-based images is feasible and practical, which provides a significant way to forecast for the photovoltaic power output within 0-4 hours.