新能源发电预测方法分类及研究进展
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安徽理工大学电气与信息工程学院

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TM61

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国网安徽省电力有限公司2023年科技项目(52120023001Q);安徽省高校自然科学研究项目2023AH051214


Classification and Research Progress of New Energy Power Generation Forecasting Methods
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School of Electrical and Information Engineering,Anhui University of Science and Technology

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    摘要:

    在国家的现代能源体系结构建设下,全国风力、光伏的发电机组容量快速增长。风、光等可再生能源的发电方式具有随机性、波动性等特点,大量接入电网时,对电力系统的稳定运行以及并网功率平滑带来巨大挑战。准确预测新能源发电电量,不仅能够提高电网的消纳能力减轻电网的调度负担,还能在一定程度上减少经济成本。因此,新能源发电预测技术的研究显得尤为重要。鉴于此,现将回顾近年来已建立的几种预测方法的分类以及新提出的新能源发电预测的方法,就模型应用原理的不同以及在实际应用上的局限性进行分析,总结出不同方法的优缺点及可改进的地方。最后,分析目前新能源发电预测面临的挑战,并提出未来可能解决的方向,给予新能源发电预测技术的相关研究人员一定的参考及指导。

    Abstract:

    Under the construction of the country's modern energy system structure, the generating capacity of wind and photovoltaic is growing rapidly across the country. Wind, light, and other renewable energy generation methods are characterized by randomness and volatility, and when a large number of them are connected to the power grid, it poses a huge challenge to the stable operation of the power system as well as grid power smoothing. Accurate prediction of new energy power generation can not only improve the grid"s ability to reduce the grid"s scheduling burden, but also reduce the economic costs to a certain extent. Therefore, the research of new energy generation forecasting technology is particularly important. Given this, we will review the classification of several prediction methods that have been established in recent years as well as the newly proposed methods for new energy generation prediction, analyze the differences in the application principles of the models as well as the limitations of their practical applications, and summarize the advantages and disadvantages of the different methods, as well as the areas that can be improved. Finally, the challenges faced by new energy power generation forecasting are analyzed, and possible future directions are proposed to give certain reference and guidance to researchers related to new energy power generation forecasting technology.

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郑晓亮,杨晓亮,来文豪. 新能源发电预测方法分类及研究进展[J]. 科学技术与工程, , ():

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  • 收稿日期:2023-12-06
  • 最后修改日期:2024-07-04
  • 录用日期:2024-07-09
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