光伏系统辐照度预测

Jiaming Li, J. Ward
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引用次数: 12

摘要

全球变暖已经成为一个关键的环境问题,使用可再生能源是减少温室气体排放最令人兴奋的方法之一。光伏(PV)发电是一种重要的可再生能源,特别是在小规模,如家庭中。为了提高小型可再生能源发电机组的价值,一种有效的方法是对其输出进行汇总和控制,并将其分组。这样做的一个挑战是对每个PV输出的精确预测。本文介绍了我们开发的基于天空相机数据的辐照度预测算法。利用支持向量机回归技术生成未来辐照度与其他可用信息之间的回归曲线。通过一系列的实验结果来评价和证明我们的预测的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Irradiance forecasting for the photovoltaic systems
Global warming has emerged as a key environmental issue, with one of the most exciting approaches to greenhouse gas reductions being the use renewable energy. Photovoltaic (PV) generation of electricity is an important renewable energy source, especially at small scale, such as in homes. To increase the value of small-scale renewable generators, one efficient way is to aggregate and control their output and group them in zones. One challenge of doing this is the precise forecasting of each PV output. This paper introduces our developed irradiance forecasting algorithm based on the data from a sky camera. A SVM regression technique is used to generate regress curves between future irradiance and other available information. A series of experimental results are presented to evaluate and demonstrate our forecasting accuracy.
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