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风电功率物理预测模型引入误差量化分析方法
作者:
作者单位:

华北电力大学经济与管理学院,北京市 102206

作者简介:

牛东晓(1962—),男,博士,教授,博士生导师,主要研究方向:电力技术经济及电力项目管理。E-mail:niudx@ncepu.edu.cn
纪会争(1974—),男,通信作者,硕士,高级工程师,主要研究方向:电力技术经济。E-mail:jbgswlb@126.com

通讯作者:

纪会争(1974—),男,通信作者,硕士,高级工程师,主要研究方向:电力技术经济。E-mail:jbgswlb@126.com

基金项目:

国家自然科学基金资助项目(71804045)。


Quantitative Analysis Method for Errors Introduced by Physical Prediction Model of Wind Power
Author:
Affiliation:

School of Economics and Management, North China Electric Power University, Beijing 102206, China

Fund Project:

This work is supported by National Natural Science Foundation of China (No. 71804045).

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    摘要:

    风电功率短期预测是风电调度运行的基础之一,物理预测方法是风电短期功率预测的基本方法之一,在欧美等国家仍作为主要预测方法,分析风电功率物理预测方法的误差源对提升预测精度具有重要作用。针对风电功率物理预测方法的误差来源问题,在分解物理预测关键环节的基础上,分别从物理模型、地转拖曳定律、数值天气预报(NWP)风速、风速-功率转化等方面,采用单一变量原则研究了各环节误差探明方案,通过物理过程推导,提出了一种面向风电功率物理预测模型的误差源分析方法,获得了物理预测方法各环节引入预测误差的量化结果。采用实际算例进行测试的结果显示,所提出的误差源分析方法能够获得误差源量化分析结果,且分析结果与实际相符,验证了方法的准确性。

    Abstract:

    Short-term wind power prediction is one of the basic supports for dispatching operation of wind power, and the physical prediction method is one of the basic methods for short-term wind power prediction, which is still the main prediction method in Europe and America. It is important to analyze the error sources of the physical prediction method to improve the prediction accuracy of wind power. In view of the error source problem of the physical prediction method for wind power, and on the basis of decomposing the key links of physical prediction model, a detection scheme of errors in each link is designed by using the principle of single variable, which considers the physical model, the geostrophic drag law, the numerical weather prediction (NWP) wind speed and wind speed and power transformation. Through a derivation to the physical process, an error source analysis method for wind power physical prediction model is proposed. Furthermore, the quantitative results of prediction errors in each part of the physical prediction method are obtained. Finally, an actual test case is used and the results show that the proposed error source analysis method can obtain quantitative analysis results of error sources, and the analysis results are consistent with the actual results, which verifies the accuracy of the method.

    图1 粗糙度变化下的风廓线示意图Fig.1 Schematic diagram of wind profile with roughness change
    图2 物理模型环节的计算风速与实测风速对比Fig.2 Comparison between calculated and measured wind speeds in the part of physical model
    图3 地转拖曳定律环节的计算风速与实测风速对比Fig.3 Comparison between calculated and measured wind speeds in the part of geostrophic drag law
    图4 不同分辨率NWP的计算风速与实测风速对比Fig.4 Comparison between calculated and measured wind speed of NWP with different resolutions
    图5 风电机组实际功率与计算功率对比Fig.5 Comparison between actual and calculated power of wind turbines
    图 风电机组轮毂高度风速、风向预测技术路线Fig. The technical route of wind speed and direction prediction on the height of wind turbine hub
    图 物理模型引入误差分析方案Fig. The introduction error analysis scheme of physical model
    图 地转拖曳定律引入误差分析方案Fig. The introduction error analysis scheme of the law of ground-to-drag
    图 参考测风塔与计算测风塔地理位置示意图Fig. Locations of reference wind tower and calculation wind tower
    图 风电机组地理位置示意图Fig. Locations of Wind Turbine Generator
    图 风电机组风轮前后风速对比Fig. Comparison of wind speed between back and front of wind wheel
    图 某风电机组风速-功率转化曲线Fig. the curve of one WTG to convert wind to power
    表 1 引入误差量化结果Table 1 Quantification results of introduction error
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引用本文

牛东晓,纪会争.风电功率物理预测模型引入误差量化分析方法[J].电力系统自动化,2020,44(8):57-65. DOI:10.7500/AEPS20191224003.
NIU Dongxiao,JI Huizheng.Quantitative Analysis Method for Errors Introduced by Physical Prediction Model of Wind Power[J].Automation of Electric Power Systems,2020,44(8):57-65. DOI:10.7500/AEPS20191224003.

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  • 收稿日期:2019-12-24
  • 最后修改日期:2020-03-09
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  • 在线发布日期: 2020-04-23
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