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基于数据驱动的风电功率预测误差解耦评价方法
作者:
作者单位:

1.国家电网华北电力调控分中心,北京市 100053;2.华北电力科学研究院有限责任公司,北京市 100045

摘要:

针对风电功率预测中多环节交互影响的复杂性,文中提出一种风电功率预测误差的精细化评价方法,旨在利用数值天气预报、气象观测数据、风电运行数据等多源异构信息,定量分析功率预测各关键环节对预测总误差的影响程度。首先,解析了风电功率预测运行机理,将预测过程分解为数值天气预报、风能-功率转换建模、预测结果校正3个关键环节。然后,设计了基于核密度估计的风电异常数据分区间辨识方法,建立了风资源-电力特性的简化模型。最后,基于气象、电力等多源运行数据驱动,提出功率预测各环节等效误差的量度方法。算例结果表明,所提方法可定量评估各环节预测对功率预测误差的影响。

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基金项目:

已申请国家发明专利(申请号:201910916121.3,201910916360.9)。

通信作者:

作者简介:

江长明(1971—),男,硕士,教授级高级工程师,主要研究方向:电力系统调控运行、新能源运行消纳分析、源-网-荷-储多元协调控制等。E-mail:jiang.changming@nc.sgcc.com.cn
杨健(1972—),男,硕士,高级工程师,主要研究方向:新能源电力系统调控运行、新能源功率预测等。E-mail:yj72072@sina.com
柳玉(1985—),男,通信作者,博士,高级工程师,主要研究方向:新能源发电运行控制、新能源功率预测等。E-mail:ncepuly@126.com


Data-driven Decoupling Evaluation Method of Wind Power Prediction Error
Author:
Affiliation:

1.North China Power Dispatching and Control Branch Center of State Grid, Beijing 100053, China;2.North China Electric Power Research Institute Co., Ltd., Beijing 100045, China

Abstract:

For the complexity of multi-link interaction in wind power prediction, this paper proposes a refined evaluation method for wind power prediction error. It aims to quantitatively analyze the effect of each key link of power prediction on the total prediction error by using numerical weather prediction, meteorological observation data, wind power operation data and other multi-source heterogeneous information. Firstly, the operation mechanism of wind power prediction is analyzed, the prediction process is divided into three key links, i.e., numerical weather prediction, wind energy-power conversion modeling and prediction result correction. Secondly, based on the kernel density estimation, the segmented identification method is designed for wind power anomaly data, and a simplified model of wind resource-power characteristics is established. Finally, based on the multi-source operation data-driven in meteorology and electric power, a method for measuring equivalent error in each link of power prediction is proposed. The case results show that the proposed method can quantitatively evaluate the effects of each link on the power prediction error.

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Foundation:
引用本文
[1]江长明,杨健,柳玉,等.基于数据驱动的风电功率预测误差解耦评价方法[J].电力系统自动化,2021,45(1):105-113. DOI:10.7500/AEPS20200318005.
JIANG Changming, YANG Jian, LIU Yu, et al. Data-driven Decoupling Evaluation Method of Wind Power Prediction Error[J]. Automation of Electric Power Systems, 2021, 45(1):105-113. DOI:10.7500/AEPS20200318005.
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  • 收稿日期:2020-03-18
  • 最后修改日期:2020-06-05
  • 录用日期:
  • 在线发布日期: 2021-01-05
  • 出版日期:
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