一种新的太阳能光伏发电量预测数据缺口填充方法

IF 1.9 4区 工程技术 Q4 ENERGY & FUELS
I. Benitez, Jessa A. Ibañez, Cenon D. Lumabad, Jayson M. Cañete, F. N. De los Reyes, J. Principe
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引用次数: 1

摘要

本研究提出了一种改进的缺口填充方法,扩展了列均值法,并使用随机生成的缺失值分别占原始输出数据的5%、10%、15%和20%进行评估。XGBoost算法是利用原始数据集和处理后的数据集,以及两个太阳辐射数据源,即来自Advanced Himawari Imager 8 (AHI-8)的短波辐射(SWR)和来自ERA5全球再分析数据的地表太阳向下辐射(SSRD),作为预测模型实现的。使用均方根误差(RMSE)和平均绝对误差(MAE)对两组预测输出功率的准确性进行评估。结果表明:采用间隙填充方法和利用SWR预测光伏发电量,RMSE和MAE的改善幅度分别为12.52% ~ 24.30%和21.10% ~ 31.31%;同时,采用SSRD方法,RMSE和MAE的改善幅度分别为14.01% ~ 28.54%和22.39% ~ 35.53%。为了进一步评估所提出的空白填充方法的准确性,可以使用不同的数据集和其他预测方法验证所提出的方法。未来的研究还可以考虑将上述方法应用于数据差距大于20%的数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel data gaps filling method for solar PV output forecasting
This study proposes a modified gaps filling method, expanding the column mean imputation method and evaluated using randomly generated missing values comprising 5%, 10%, 15%, and 20% of the original data on power output. The XGBoost algorithm was implemented as a forecasting model using the original and processed datasets and two sources of solar radiation data, namely, Shortwave Radiation (SWR) from Advanced Himawari Imager 8 (AHI-8) and Surface Solar Radiation Downward (SSRD) from ERA5 global reanalysis data. The accuracy of the two sets of forecasted power output was evaluated using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Results show that by applying the proposed gap filling method and using SWR in forecasting solar photovoltaic (PV) output, the improvement in the RMSE and MAE values range from 12.52% to 24.30% and from 21.10% to 31.31%, respectively. Meanwhile, using SSRD, the improvement in the RMSE values range from 14.01% to 28.54% and MAE values from 22.39% to 35.53%. To further evaluate the accuracy of the proposed gap-filling method, the proposed method could be validated using different datasets and other forecasting methods. Future studies could also consider applying the said method to datasets with data gaps higher than 20%.
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来源期刊
Journal of Renewable and Sustainable Energy
Journal of Renewable and Sustainable Energy ENERGY & FUELS-ENERGY & FUELS
CiteScore
4.30
自引率
12.00%
发文量
122
审稿时长
4.2 months
期刊介绍: The Journal of Renewable and Sustainable Energy (JRSE) is an interdisciplinary, peer-reviewed journal covering all areas of renewable and sustainable energy relevant to the physical science and engineering communities. The interdisciplinary approach of the publication ensures that the editors draw from researchers worldwide in a diverse range of fields. Topics covered include: Renewable energy economics and policy Renewable energy resource assessment Solar energy: photovoltaics, solar thermal energy, solar energy for fuels Wind energy: wind farms, rotors and blades, on- and offshore wind conditions, aerodynamics, fluid dynamics Bioenergy: biofuels, biomass conversion, artificial photosynthesis Distributed energy generation: rooftop PV, distributed fuel cells, distributed wind, micro-hydrogen power generation Power distribution & systems modeling: power electronics and controls, smart grid Energy efficient buildings: smart windows, PV, wind, power management Energy conversion: flexoelectric, piezoelectric, thermoelectric, other technologies Energy storage: batteries, supercapacitors, hydrogen storage, other fuels Fuel cells: proton exchange membrane cells, solid oxide cells, hybrid fuel cells, other Marine and hydroelectric energy: dams, tides, waves, other Transportation: alternative vehicle technologies, plug-in technologies, other Geothermal energy
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