基于储能的光伏阵列功率预测模型

Jun Tian, Yonghuai Zhu, Jianfang Tang
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引用次数: 3

摘要

随着光伏发电系统容量的迅速增加,如何处理系统中随机输出所带来的问题变得更加重要。一个可能的解决方案是使用能量存储。利用本文介绍的支持向量回归模型(SVR)得到预测输出,然后根据实际输出与预测输出的差值进行储能容量的优化。也就是说,采用储能装置来补偿差异,从而减小预测值与实际值之间的偏差。结果表明,提出的ELSSVR算法是有效的,储能装机容量显著降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Photovoltaic array power forecasting model based on energy storage
With the rapid increase of the capacity in photovoltaic (PV) generated systems, how to deal with the problem caused by the random output in the system becomes more significant. One possible solution could be the use of energy storage. The forecasting output can be obtained by the support vector regression model (SVR) introduced in this article, then the capacity of energy storage can be optimized by the difference between actual and predicting outputs. That is to say, energy storage devices are taken to compensate the difference, so that the deviation between predictions and actual values can be decreased. The results show that the proposed algorithm ELSSVR is effective and the installed capacity of energy storage is reduced significantly.
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