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Day ahead hourly forecast of solar irradiance for Abu Dhabi, UAE

机译:阿联酋阿布扎比太阳辐射的前一天每小时预报

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摘要

Forecasting is an inseparable part of modern renewable energy generation systems including wind, solar and wave. In order to effectively manage integration of grid-connected energy resources and energy storage systems, the energy generation potential of these resources needs to be estimated ahead in time. To this aim, this paper applies a simple and linear statistical forecasting technique, the Autoregressive Integrated Moving Average (ARIMA) on hourly global horizontal irradiance (GHI W/m2) data. The objective is to test the capabilities of ARIMA forecasting on high resolution solar time series for the state of Abu Dhabi, the United Arab Emirates and lay down the foundations for further in-depth analysis. The performance of the model is assessed using commonly used statistical metrics, coefficient of determination (R2) and root mean square error (RMSE). The model is trained and tested on hourly GHI from March, 2016. The R2 and RMSE values for the best fit model are found to be 88.63% and 72.88 W/m2, respectively.
机译:预测是现代可再生能源发电系统不可分割的一部分,包括风能,太阳能和波浪能。为了有效地管理并网的能源和储能系统的集成,需要提前估算这些资源的发电潜力。为此,本文对小时全球水平辐照度(GHI W / m2)数据应用了一种简单且线性的统计预测技术,即自回归综合移动平均值(ARIMA)。目的是测试ARIMA在阿拉伯联合酋长国阿布扎比州的高分辨率太阳时间序列上的预报能力,并为进一步的深入分析奠定基础。使用常用的统计指标,确定系数(R2)和均方根误差(RMSE)评估模型的性能。该模型从2016年3月开始按小时GHI进行训练和测试。最佳拟合模型的R2和RMSE值分别为88.63%和72.88 W / m2。

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