A comprehensive review for wind, solar, and electrical load forecasting methods
2022-03-14
【论文推荐】清华大学 王函等：风光发电功率与用电负荷预测方法综述
文章导读
风光发电功率与用电负荷预测是保障电力系统安全稳定运行的重要工作。随着新能源渗透率与需求响应负荷的不断增加，电力系统源荷两端的不确定性均日益增强，不仅为预测工作带来了新的挑战，也对预测精度提出了更高的要求。当前关于风、光、荷预测的综述论文主要集中在单一对象，少数同时涉及上述两到三个对象，但仅在文章中对不同对象的预测方法分别进行综述。为应对源荷两端不断增加的不确定性对电力系统的冲击，一些学者同时对上述两到三个对象进行预测，然而目前尚无相关综述文章。论文提供了针对当前风光发电功率与用电负荷预测方法的全面综述。首先从相关文献发表数量、年份、国家、机构等多方面入手对现有预测文章进行概述，而后全面回顾了当前风光荷预测方法，总结分析了各方法的优缺点，并首次整理了同时包含风光荷至少两种对象的预测文章。此外，作者对直接影响短期风光发电功率预测精度的数值天气预报风速/辐照度的修正方法进行了综述。最后探讨了预测工作当前所面临的挑战和未来的研究方向。研究成果可为风光发电功率和用电负荷预测研究提供参考。
A comprehensive review for wind, solar, and electrical load forecasting methods
风光发电功率与用电负荷预测方法综述
Han Wang1,3,4, Ning Zhang1, Ershun Du2, Jie Yan3,4, Shuang Han3,4, Yongqian Liu3,4
(1.Department of Electrical Engineering, Tsinghua University, Beijing 100084, P. R. China
2.Low Carbon Energy Laboratory, Tsinghua University, Beijing 100084, P. R. China
3.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, P. R. China
4.School of New Energy, North China Electric Power University, Beijing 102206, P. R. China)
收听作者1分钟语音介绍
Abstract
Keywords
Wind power, Solar power, Electrical load, Forecasting, Numerical Weather Prediction, Correlation.
Fig.1 Correlation of wind power, solar power, and electrical load
Fig.2 Number of SCI publications about wind, solar, and load forecasting in 2011-2020
Fig.3 A classification of SCI-Q1 publications about wind, solar, and load forecasting in 2011-2020 (from perspective of country)
Fig.4 Classification of wind power/solar power forecasting methods
Fig.5 Uncertain forecasting results of wind power
Fig.6 Uncertain forecasting results of solar power
Fig.7 Classification of electrical load forecasting methods
Fig.8 Probabilistic forecasting results of electrical load
Fig.9 Ways to improve NWP correction accuracy
Fig.10 Ways to consider correlation among wind, solar, and load
本文引文信息
Wang H, Zhang N, Du E S, Yan J, Han S, Liu Y Q. (2022) A comprehensive review for wind, solar, and electrical load forecasting methods, 5(1): 9-30
王函，张宁，杜尔顺，阎洁，韩爽，刘永前 (2022) 风光发电功率与用电负荷预测方法综述. 全球能源互联网（英文），5(1): 9-30
Biographies
Han Wang
received her joint educated Ph.D. degree from North China Electric Power University, Beijing, China and the University of Bath, Bath, U.K., in 2021, bachelor degree from North China Electric Power University, Beijing, China, in 2015. She is currently a research associate with Department of Electrical Engineering, Tsinghua University.
Her major research interest includes the characteristics analysis of new energy and load, and their forecasting methods.
Ning Zhang
received his Ph.D. degree from Tsinghua University, Beijing, China, in 2012, bachelor degree from Tsinghua University, Beijing, China, in 2007. He is now an associate professor with Department of Electrical Engineering, Tsinghua University, Beijing, China. His research interests focus on multi- energy system, planning and operation of power system.
Ershun Du
received his Ph.D. degree from Tsinghua University, Beijing, China, in 2018. He is now a research associate in Tsinghua University, Beijing, China. His research interests focus on multi-energy system, planning and operation of power system.
Jie Yan
received her joint educated Ph.D. degree in renewable and clean energy from North China Electric Power University, Beijing, China and the University of Bath, Bath, U.K., in 2016, and master and bachelor degrees from North China Electric Power University, Beijing, China in 2010 and 2012, respectively. She is currently an associate
professor with School of New Energy, North China Electric Power University, Beijing, China. Her major research interest includes uncertainty analysis of wind power generation, wind power forecasting, and power system economic dispatch.
Shuang Han
received her Ph.D. degree from North China Electric Power University, Beijing, China, in 2008. She is now a professor with School of New Energy, North China Electric Power University, Beijing, China. Her major research interest includes the wind energy resource assessment, wind power forecasting, wind farm design and post- evaluation.
Yongqian Liu
received his Ph.D. degree from Henri Poincare University (Nancy 1), Nancy, France and Huazhong University of Science and Technology, Wuhan, China, both in 2002, master and bachelor degrees from North China University of Water Resources and Electric Power, Zhengzhou, China, in 1992 and 1986, respectively. He is now a professor with School
of New Energy, North China Electric Power University, Beijing, China. His main research interests focus on wind farm technologies, including wind energy resource assessment and wind farm design, wake modelling, wind power prediction, operation and maintenance of a wind farm.
编辑：王彦博
审核：王 伟
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