基于改进相关向量机算法的太阳辐照度预测方法研究
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摘要
针对太阳辐照度的波动性和间歇性,文章提出了一种基于改进相关向量机算法的太阳辐照度预测方法。采用最优变分模态分解算法把太阳辐照度序列分解成为一些相对稳定的模态分量,将混沌蝗虫优化算法和相关向量机算法相结合,建立每个模态分量的预测模型,并通过实例验证预测模型的有效性和准确性。结果表明,该模型预测精度高,稳定性和实用性强。
Accurate prediction of solar irradiance is of great significance for the efficient use of solar energy. Aiming at the volatility and intermittentity of solar irradiance, a solar irradiance prediction method based on improved correlation vector machine is proposed. The solar irradiance sequence is decomposed into some relatively stable modal components by the optimal variational modal decomposition algorithm, and then the prediction model of each modal component is established by optimizing the correlation vector machine algorithm with the chaotic locust optimization algorithm, the validity and accuracy of the prediction model are verified by an example. The results show that the model has high prediction accuracy, strong stability and practicability.
Accurate prediction of solar irradiance is of great significance for the efficient use of solar energy. Aiming at the volatility and intermittentity of solar irradiance, a solar irradiance prediction method based on improved correlation vector machine is proposed. The solar irradiance sequence is decomposed into some relatively stable modal components by the optimal variational modal decomposition algorithm, and then the prediction model of each modal component is established by optimizing the correlation vector machine algorithm with the chaotic locust optimization algorithm, the validity and accuracy of the prediction model are verified by an example. The results show that the model has high prediction accuracy, strong stability and practicability.
引文
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[3]刘剑,曹美燕,高治军,等.一种基于随机森林的太阳能辐射预测模型[J].控制工程,2017,24(12):2472-2477.
[4]陶仁峰,李凤婷,李永东,等.基于云层分布规律与太阳光跟踪的光伏电站MPPT策略[J].电力系统自动化,2018,29(5):113-116.
[5]高亮,张新燕,张家军,等.基于拟合剔除的优化小波神经网络太阳辐射量预测[J].电测与仪表,2019,40(4):1-5.
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