Solar Irradiance Forecasting Based on Electromagnetism-like Neural Networks

Ke-Hung Lee, Ming-Wei Hsu, Yih-Guang Leu
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引用次数: 5

Abstract

This paper studies the forecasting of solar irradiance using electromagnetism-like neural networks. First, a solar irradiance information platform is set up to collect the relevant data for the solar irradiance forecasting. The solar irradiance information platform includes a pyranometer, a single board computer, a camera and a cloud server. By integrating the software and hardware of the solar irradiance information platform, real-time solar irradiances and sky images can be captured and stored in the MySQL database of the cloud server. Then, these solar irradiances and sky images are used to establish a neural network forecasting system. An improved electromagnetism-like algorithm is used to optimize the neural network prediction system. Finally, some comparison results are given to verify the effectiveness of the method proposed in this paper.
基于类电磁神经网络的太阳辐照度预测
本文研究了利用类电磁神经网络预测太阳辐照度的方法。首先,建立太阳辐照度信息平台,为太阳辐照度预报收集相关数据;太阳辐照度信息平台包括一个太阳辐射计、一个单板计算机、一个摄像头和一个云服务器。通过集成太阳辐照度信息平台的软硬件,可以实时捕获太阳辐照度和天空图像,并存储在云服务器的MySQL数据库中。然后,利用这些太阳辐照度和天空图像建立神经网络预报系统。采用一种改进的类电磁算法对神经网络预测系统进行优化。最后给出了一些比较结果,验证了本文方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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