【论文推荐】华北电力大学刘永前等：基于卷积神经网络的数值天气预报统计降尺度研究

摘要

数值天气预报（NWP）是短期风电功率预测的必要输入。现有的数值天气预报模式均基于纯粹的物理模型。需要大型计算机进行大规模数值计算，且同化过程技术门槛高，时效性和精度都有待进一步提高。为了解决上述问题，本文提出了基于人工智能的数值天气预报方法，该方法基于卷积神经网络算法，建立了全球背景场到给定风电机组轮毂高度位置的降尺度模型。计算结果表明：所提方法与传统纯物理模型的预报精度相当，部分月份优于纯物理模型，且大幅提升计算效率；验证了所提方法的有效性和优势，在一定程度上实现了传统数值天气预报模式的替代。

Statistical downscaling of numerical weather prediction based on convolutional neural networks

基于卷积神经网络的数值天气预报统计降尺度研究

Hongwei Yang^1,2, Jie Yan^1,2, Yongqian Liu^1,2, Zongpeng Song^3,4

(1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, P.R.China 2.School of Renewable Energy, North China Electric Power University, Beijing 102206, P.R.China 3.Renewable Energy Center, China Electric Power Research Institute, Beijing 100192, P.R.China 4.State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems, Beijing 100192, P.R.China)

收听作者1分钟语音介绍

Statistical Downscaling of Numerical Weather Prediction

Abstract

Numerical Weather Prediction (NWP) is a necessary input for short-term wind power forecasting.Existing NWP models are all based on purely physical models.This requires mainframe computers to perform large-scale numerical calculations and the technical threshold of the assimilation process is high.There is a need to further improve the timeliness and accuracy of the assimilation process.In order to solve the above problems, NWP method based on artificial intelligence is proposed in this paper.It uses a convolutional neural network algorithm and a downscaling model from the global background field to establish a given wind turbine hub height position.We considered the actual data of a wind farm in north China as an example to analyze the calculation example.The results show that the prediction accuracy of the proposed method is equivalent to that of the traditional purely physical model.The prediction accuracy in some months is better than that of the purely physical model, and the calculation efficiency is considerably improved.The validity and advantages of the proposed method are verified from the results, and the traditional NWP method is replaced to a certain extent.

Keywords

Convolutional Neural Network, Deep learning, Numerical Weather Prediction.

Fig.1 Schematic diagram of image convolution operation

Fig.2 Schematic diagram of the maximum pooling function operation

Fig.3 Schematic diagram of upsampling operation

Fig.4 CNN downscaling model construction flowchart

Fig.5 CNN downscaling model structure diagram

Fig.6 Comparison of NWP wind speed before and after correction with the actual wind speed of wind turbines

本文引文信息

Yang HW, Yan J, Liu YQ, Song ZP (2022) Statistical downscaling of numerical weather prediction based on convolutional neural networks. Global Energy Interconnection, 5(2): 217-225

杨宏伟，阎洁，刘永前，宋宗朋 (2022) 基于卷积神经网络的数值天气预报统计降尺度研究. 全球能源互联网（英文），5(2): 217-225

Biographies

Hongwei Yang

Hongwei Yang is currently studying at North China Electric Power University (NCEPU),studying for a master’s degree, and his research direction is numerical weather prediction based on artificial intelligence.

Jie Yan

Jie Yan is the corresponding author, who received her joint educated Ph.D.degree in renewable & clean energy from North China Electric Power University (NCEPU), Beijing,China and University of Bath, Bath, U.K.in 2016.She is currently an associate professor with the school of renewable energy in NCEPU.Her major research interest includes wind/solar power forecasting, wind farm control and multi-energy operation.

Yongqian Liu

Yongqian Liu received the Ph.D.degree in production automation from Nancy 1 University and the Ph.D.degree in hydropower engineering from the Huazhong University of Science and Technology in 2002.He has 30 years of professional experience on wind power and hydro power engineering.He is currently a Professor with the School of Renewable Energy, North China Electric Power University, Beijing,China.His main research interests focus on wind farm technologies,including wind resources assessment and wind farm design, wake modelling, wind power prediction, operation and maintenance of a wind farm.

Zongpeng Song

Zongpeng Song received his Ph.D.degree at Institute of Atmospheric Physics, Chinese Academy of Science, Beijing, 2014.He is working in Renewable Energy Center, China Electric Power Research Institute, Beijing,China.

编辑：王彦博

审核：王伟

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Statistical downscaling of numerical weather prediction based on convolutional neural networks

【论文推荐】华北电力大学 刘永前等：基于卷积神经网络的数值天气预报统计降尺度研究

郑重声明

【论文推荐】华北电力大学刘永前等：基于卷积神经网络的数值天气预报统计降尺度研究