中文摘要：

准确的太阳能辐照量预测对于光伏发电系统具有重要意义.提出一种基于经验模态分解（EMD）和ELM神经网络的逐时辐照量组合预测模型.首先,根据预测日的环境信息,构建相似日逐时辐照量时间序列;然后,将时间序列进行EMD,分解为具有不同频率的信号,并对每个信号建立ELM神经网络预测模型;最后,将不同信号的预测值相加便可得到原始辐照量序列的预测值.算例比较表明,所提方法比传统的预测方法具有更高的预测准确度和更快的运算速度.

英文摘要：

Accurate solar radiation forecasting is essential for photovoltaic generation system. An hourly solar radiation forecasting model based on EMD（Empirical Mode Decomposition） and ELM neural network is proposed. The hourly solar radiation sequence of similar days is built according to the environmental information of the forecast day,which is then decomposed to signals with different frequencies by EMD. An ELM neural network forecasting model is built for each signal. The forecasting value of original solar radiation sequence is obtained by that,compared with the traditional and faster computation speed. adding up the forecasting values forecasting methods,the proposed of different signals. Case study shows method has higher forecasting accuracy and faster computation speed.