...
首页> 外文期刊>Energy Conversion & Management >An accuracy assessment of an empirical sine model, a novel sine model and an artificial neural network model for forecasting illuminance/irradiance or horizontal plane of all sky types at Mahasarakham, Thailand
【24h】

An accuracy assessment of an empirical sine model, a novel sine model and an artificial neural network model for forecasting illuminance/irradiance or horizontal plane of all sky types at Mahasarakham, Thailand

机译:预测泰国Mahasarakham所有天空类型的照度/辐照度或水平面的经验正弦模型,新型正弦模型和人工神经网络模型的准确性评估

获取原文
获取原文并翻译 | 示例

摘要

The results of a study on all sky modeling and forecasting daylight availability for the tropical climate found in the central region of the northeastern part of Thailand (16°14' N, 103°15' E) is presented. The required components of sky quantities, namely, global and diffuse horizontal irradiance and global horizontal illuminance for saving energy used in buildings are estimated. The empirical sinusoidal models are validated. A and B values of the empirical sinusoidal model for all sky conditions are determined and developed to become a form of the sky conditions. In addition, a novel sinusoidal model, which consists of polynomial or exponential functions, is validated. A and B values of the empirical sinusoidal model for all sky conditions are determined and developed to become a new function in the polynomial or exponential form of the sky conditions. Novelettes, an artificial intelligent agent, namely, artificial neural network (ANN) model is also identified. Back propagation learning algorithms were used in the networks. Moreover, a one year data set and a next half year data set were used in order to train and test the neural network, respectively. Observation results from one year's round data indicate that luminosity and energy from the sky on horizontal in the area around Mahasarakham are frequently brighter than those of Bangkok. The accuracy of the validated model is determined in terms of the mean bias deviation (MBD), the root-mean-square-deviation (RMSD) and the coefficient of correlation (R~2) values. A comparison of the estimated solar irradiation values and the observed values revealed a small error slide in the empirical sinusoidal model as well. In addition, some results of the sky quantity forecast by the ANN model indicate that the ANN model is more accurate than the empirical models and the novel sinusoidal models. This study confirms the ability of the ANN to predict highly accurate solar radiance/illuminance values. We believe that the ANN model is suitable as an alternative model for forecasting the sky quantities.
机译:介绍了在泰国东北部中部地区(16°14'N,103°15'E)发现的热带气候全天空模型和预测日光可用性的研究结果。为了节省建筑物中使用的能源,估算了天空数量所需的分量,即,全局和漫射水平辐照度以及全局水平照度。经验正弦模型得到验证。确定所有天空条件下的经验正弦模型的A和B值,并将其发展为天空条件的一种形式。此外,还验证了由多项式或指数函数组成的新型正弦模型。确定和发展了所有天空条件下的经验正弦模型的A和B值,并成为天空条件的多项式或指数形式的新函数。还确定了Novelettes,这是一种人工智能代理,即人工神经网络(ANN)模型。在网络中使用了反向传播学习算法。此外,分别使用了一年数据集和下半年数据集来训练和测试神经网络。一年轮数据的观察结果表明,在Mahasarakham周围地区,水平天空的亮度和能量通常比曼谷的亮度和能量明亮。验证模型的准确性取决于平均偏差偏差(MBD),均方根偏差(RMSD)和相关系数(R〜2)值。估算的太阳辐射值与观测值的比较显示,经验正弦模型中的误差也较小。此外,通过人工神经网络模型预测的天空数量的一些结果表明,人工神经网络模型比经验模型和新颖的正弦模型更准确。这项研究证实了人工神经网络能够预测高度准确的太阳辐射/照度值的能力。我们认为,人工神经网络模型适合作为预测天空量的替代模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号