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新能源功率预测特性分析及精度提升措施 被引量:10

Renewable Energy Power Prediction Characteristics Analyses and Accuracy Improvement Measures
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摘要 为了实现“碳达峰,碳中和”的战略目标,大力发展新能源成为构建新一代低碳化、清洁化电力系统的趋势。目前,在新型电力系统的全面建设中,新能源的功率预测误差分析与预测精度提升至关重要。以我国南方数省2021年新能源日前功率预测及实际运行数据为例,系统性梳理分析了新能源功率预测特性并提出了相应的预测误差应对思路。首先,对现有预测技术以及国内外预测技术应用现状进行了总结;然后,梳理了现行新能源功率预测误差的共性特性;最后,提出了新能源功率预测误差应对思路,包括新能源功率预测指标体系构建、组合算法研究思路、新能源功率预测价值生态培育探索等。 To achieve the goals of carbon peaking and carbon neutrality,the development of renewable energies becomes the trend in building a power system with low-carbon emissions and clean energy sources.Analyses of power forecasting errors and improve⁃ments in the prediction accuracy of renewable energies are crucial for building new power systems.In this paper,by taking day-ahead prediction of renewable energy power of several southern provinces of China in 2021 as examples,the power prediction characteristics of renewable energies is systematically analyzed and corresponding strategies are proposed to cope with forecasting er⁃rors.Firstly,first,existing forecast technologies and the current status of their applications at home and abroad are summarized.Secondly,the common characteristics of the current day-ahead renewable energy power forecasting errors are sorted out.Finally,ideas for coping with renewable energy power forecasting errors are proposed,including the investigation of evaluation metrics for renewable energy power forecasting,research on the ensemble of forecast models,exploration of value ecology cultivation for renew⁃able energy power predictions,etc.
作者 邓韦斯 孟子超 王皓怀 郭烨 刘显茁 田伟达 谢平平 戴仲覆 DENG Weisi;MENG Zichao;WANG Haohuai;GUO Ye;LIU Xianzhuo;TIAN Weida;XIE Pingping;DAI Zhongfu(Power Dispatch Control Center,CSG,Guangzhou 510663,China;State Key Laboratory of HVDC,Electric Power Research Institute,CSG,Guangzhou 510663,China)
出处 《南方电网技术》 CSCD 北大核心 2023年第2期11-23,共13页 Southern Power System Technology
基金 国家重点研发计划资助项目(2018YFB0904200) 广东省海上风电联合基金项目(206292459140) 中国南方电网有限责任公司科技项目(ZDKJXM20210047)。
关键词 碳达峰 碳中和 新能源 预测特性分析 误差应对措施 carbon peaking carbon neutrality renewable energies prediction characteristics analyses measures to cope with forecasting errors
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