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Photovoltaic array power forecasting model based on energy storage

机译:基于储能的光伏阵列功率预测模型

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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.
机译:随着光伏(PV)发电系统容量的快速增加,如何处理系统中随机输出引起的问题变得越来越重要。一种可能的解决方案是使用能量存储。可以通过本文介绍的支持向量回归模型(SVR)获得预测输出,然后可以通过实际输出与预测输出之间的差异来优化能量存储的容量。也就是说,采用能量存储装置来补偿该差异,从而可以减小预测值与实际值之间的偏差。结果表明,所提出的算法ELSSVR是有效的,并且能量存储的装机容量大大降低。

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