基于Bayes判别准则的风电场等值误差阈值最小风险量化方法

朱乾龙; 金小强; 王绪利; 苏凡亚; 邓天白; 陶骏

doi:10.11930/j.issn.1004-9649.202406035

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基于Bayes判别准则的风电场等值误差阈值最小风险量化方法

风电机组暂态运行控制与试验验证关键技术 | 更新时间：2025-10-29

- 基于Bayes判别准则的风电场等值误差阈值最小风险量化方法
- Minimum Risk Quantification Method for Equivalent Error Threshold of Wind Farm Based on Bayes Criterion
- 中国电力 2025年58卷第4期页码：98-106
- 作者机构：
  
  1.安徽大学电气工程与自动化学院，安徽合肥　230601
  2.国网安徽省电力有限公司经济技术研究院，安徽合肥　230022
- 作者简介：
  
  [ "", "朱乾龙（1988），男，通信作者，博士，讲师，从事新能源场站建模与有效性验证研究，E-mail：zhuqianl19@163.com" ]
  [ "金小强（1998），男，硕士研究生，从事风电场等值模型有效性研究，E-mail：z22301181@stu.ahu.edu.cn" ]
- 基金信息：
  
  安徽省高等学校科学研究项目（2023AH050075，2022AH050105）。
- DOI：10.11930/j.issn.1004-9649.202406035
  中图分类号：
- 收稿：2024-06-12，
  
  修回：2025-03-17，
  
  纸质出版：2025-05-28
- 稿件说明：
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朱乾龙, 金小强, 王绪利, 等. 基于Bayes判别准则的风电场等值误差阈值最小风险量化方法[J]. 中国电力, 2025,58(4):98-106.

Qianlong ZHU, Xiaoqiang JIN, Xuli WANG, et al. Minimum Risk Quantification Method for Equivalent Error Threshold of Wind Farm Based on Bayes Criterion[J]. Electric power, 2025, 58(4): 98-106.
朱乾龙, 金小强, 王绪利, 等. 基于Bayes判别准则的风电场等值误差阈值最小风险量化方法[J]. 中国电力, 2025,58(4):98-106. DOI： 10.11930/j.issn.1004-9649.202406035.

Qianlong ZHU, Xiaoqiang JIN, Xuli WANG, et al. Minimum Risk Quantification Method for Equivalent Error Threshold of Wind Farm Based on Bayes Criterion[J]. Electric power, 2025, 58(4): 98-106. DOI： 10.11930/j.issn.1004-9649.202406035.

摘要

等值误差阈值是平衡风电场模型数学复杂度与仿真速度的基石，可推动风电场等值模型的标准化进程。世界主要风电大国在量化风电模型误差阈值方面的出发点和侧重点不同，误差阈值的形式及指标尚未统一。为此，从理论层面提出一种基于Bayes判别准则的风电场等值误差阈值最小风险量化方法。首先，以等值误差的时间分布特性为切入点，量化不同时段内风电场等值模型的欧几里得误差，进而通过核密度估计拟合上述误差的概率密度分布。然后，使用实时加权先验概率算法获取风电场模型有效的先验概率，并计及模型有效性漏判和误判给电力系统带来的不同损失，基于Bayes判别准则建立面向最小风险的风电场等值误差阈值量化模型。最后，以某实际风电场算例进行分析，验证了所提方法的可行性，与国内外误差阈值相比，所提方法可更加快速、准确地判定风电场等值模型的有效性。

Abstract

The equivalent error threshold is the cornerstone to balance the mathematical complexity and simulation speed of wind farm (WF) model

and can promote the standardization process of WF equivalent model. Major wind power countries in the world have different starting points and emphases in quantifying the error threshold of wind power models

and the form and indicators of the error threshold have not been unified. Therefore

this paper puts forward a method based on Bayes criterion to quantify the minimum risk of equivalent error threshold of WFs. Firstly

taking the time distribution characteristics of equivalent errors as the starting point

the Euclidean errors of equivalent models of WFs in different periods are quantified

and then the probability density distributions of the above errors are fitted by kernel density estimation. Secondly

the real-time weighted prior probability algorithm is used to obtain the effective prior probability of the WF model

and based on the Bayes criterion

the equivalent error threshold quantization model of the WF is established for the minimum risk

with consideration of the different losses caused by the misjudgment of the model validity to the power system. Finally

the feasibility of the proposed method is verified by an actual WF example

and compared with the error threshold at home and abroad

the effectiveness of the WF equivalent model can be determined more quickly and accurately.

关键词

Keywords

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