Minimum Risk Quantification Method for Equivalent Error Threshold of Wind Farm Based on Bayes Criterion

Qianlong ZHU; Xiaoqiang JIN; Xuli WANG; Fanya SU; Tianbai DENG; Jun TAO

doi:10.11930/j.issn.1004-9649.202406035

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

Minimum Risk Quantification Method for Equivalent Error Threshold of Wind Farm Based on Bayes Criterion

Key Technologies for Transient Operation Control and Test Verification of Wind Turbines | 更新时间：2025-10-29

- Minimum Risk Quantification Method for Equivalent Error Threshold of Wind Farm Based on Bayes Criterion
- Electric Power Vol. 58, Issue 4, Pages: 98-106(2025)
- 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：
- 基金信息：
- DOI：10.11930/j.issn.1004-9649.202406035
  CLC：
- Received：12 June 2024，
  
  Revised：2025-03-17，
  
  Published：28 May 2025
- 稿件说明：
移动端阅览
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：

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

references

陈国平, 李明节, 董昱, 等. 构建新型电力系统仿真体系研究[J]. 中国电机工程学报, 2023, 43(17): 6535–6551.

CHEN Guoping, LI Mingjie, DONG Yu, et al . Research on the simulation technology architecture for the new-type power system[J ] . Proceedings of the CSEE, 2023, 43(17): 6535–6551.

李丹, 秦世耀, 李少林, 等. 基于混沌粒子群的双馈风电机组LVRT实测建模及暂态参数辨识[J]. 中国电力, 2024, 57(8): 75–84.

LI Dan, QIN Shiyao, LI Shaolin, et al . LVRT measurement model and transient parameter identification of wind turbine based on chaotic particle swarm[J ] . Electric Power, 2024, 57(8): 75–84.

蒋昊, 许立雄, 崔晓丹, 等. 基于保护电路运行状态增强识别的双馈风电场等值建模[J]. 电力系统保护与控制, 2024, 52(22): 129–142.

JIANG Hao, XU Lixiong, CUI Xiaodan, et al . Equivalent modeling of a DFIG farm based on enhanced recognition of protection circuit operating state[J ] . Power System Protection and Control, 2024, 52(22): 129–142.

杨舒婷, 陈新, 黄通, 等. 考虑MMC环流控制的海上风电经柔直送出系统阻抗塑造方法[J]. 中国电力, 2023, 56(4): 38–45.

YANG Shuting, CHEN Xin, HUANG Tong, et al . Impedance modeling method of offshore wind farm integration through MMC-HVDC with MMC circulation control[J ] . Electric Power, 2023, 56(4): 38–45.

王晗玥, 付乐融, 刘星, 等. 风电场站等值模型综合评价体系[J]. 电力自动化设备, 2024, 44(7): 271–277.

WANG Hanyue, Fu Lerong, Liu Xing, et al . The synthetic evaluation system of wind power station equivalent model[J ] . Electric power automation equipment, 2024, 44(7): 271–277.

朱乾龙, 齐盟. 风电场等值模型准确度评价研究综述[J]. 电力电容器与无功补偿, 2020, 41(6): 180–184, 190.

ZHU Qianlong, QI Meng. Review on accuracy evaluation of equivalent model of wind farm[J]. Power Capacitor&Reactive Power Compensation, 2020, 41(6): 180–184, 190.

MEUSER M, BRENNECKE M. Analysis and comparison of national and international validation methods to assess the quality of DG simulation models[C]//International ETG Congress 2015, Die Energiewende - Blueprints for the New Energy Age·VDE, 2016.

FGW-TR4: Technical guidelines for power generating units and systems part 4, demands on modelling and validating simulation models of the electrical characteristics of power generating units and systems[S]. 2016.

Procedimientos de verificación, validación y certificación de los requisitos del PO 12.3 y P. O. 12.2. sobre la respuestade las instalaciones eólicas y fotovoltaicas ante huecos de tensión, 11th ed: PO 12.3[S]. Asociación Empresarial Eólica. 2017.

JIMÉNEZ-BUENDÍA F, VILLENA-RUIZ R, HONRUBIA-ESCRIBANO A, et al . Submission of a WECC DFIG wind turbine model to Spanish operation procedure 12.3[J ] . Energies, 2019, 12(19): 3749.

National Electricity Market Management Company Limited. Wind farm model guidelines and checklist-memmco[S]. Australia, 2006.

LI W X, CHAO P P, LIANG X D, et al . An improved single-machine equivalent method of wind power plants by calibrating power recovery behaviors[J ] . IEEE Transactions on Power Systems, 2018, 33(4): 4371–4381.

WECC Renewable Energy Modeling Task Force. WECC wind power plant dynamic modeling guidelines[R]. USA: EPRI, 2014.

Wind energy generation systems—Part 27-2: electrical simulation models—model validation: IEC 61400-27-2[S]. Switzerland, 2020.

风能发电系统通用电气仿真模型: GB/T 36237—2023[S]. 北京: 中国标准出版社.

风电机组电气仿真模型验证规程: NB/T 31053—2021[S]. 北京: 中国电力出版社.

CHEN P, CHEN C C, PENG Y H, et al . A time-domain SAR smart temperature sensor with curvature compensation and a 3σ inaccuracy of −0.4 ℃~0.6 ℃ over a 0 ℃ to 90 ℃ range[J ] . IEEE Journal of Solid-State Circuits, 2010, 45(3): 600–609.

狄亚南, 江刚武, 张一, 等. 联合变化强度和相关系数最小错分概率变化检测阈值优化[J]. 测绘科学技术学报, 2016, 33(2): 180–184.

DI Yanan, JIANG Gangwu, ZHANG Yi, et al . Change detection threshold optimization of combining change intensity with correlation coefficient based on the minimum error probability[J ] . Journal of Geomatics Science and Technology, 2016, 33(2): 180–184.

孙华东, 李佳豪, 李文锋, 等. 大规模电力系统仿真用新能源场站模型结构及建模方法研究(二): 机电暂态模型[J]. 中国电机工程学报, 2023, 43(6): 2190–2202.

SUN Huadong, LI Jiahao, LI Wenfeng, et al . Research on model structures and modeling methods of renewable energy station for large-scale power system simulation(Ⅱ): electromechanical transient model[J ] . Proceedings of the CSEE, 2023, 43(6): 2190–2202.

陈继明, 王辉, 仉志华. 双馈风电场等值准确度研究[J]. 电网技术, 2014, 38(7): 1867–1872.

CHEN Jiming, WANG Hui, ZHANG Zhihua. Research on equivalent accuracy of wind farm composed of DFIGs[J]. Power System Technology, 2014, 38(7): 1867–1872.

ZHU Q L. Quantitative evaluation method for error of wind farm equivalent model based on multiscale entropy-greedy Gaussian segmentation[J]. Electric Power Systems Research, 2023, 220: 109270.

贾巍, 雷才嘉, 方兵华, 等. 供电分区场景下基于数据驱动的负荷密度综合评估及预测方法[J]. 中国电力, 2023, 56(6): 71–81.

JIA Wei, LEI Caijia, FANG Binghua, et al . A comprehensive evaluation and prediction method for load density based on big data under power supply partition scenarios[J ] . Electric Power, 2023, 56(6): 71–81.

HATZIARGYRIOU N, MILANOVIC J, RAHMANN C, et al . Definition and classification of power system stability–revisited & extended[J ] . IEEE Transactions on Power Systems, 2021, 36(4): 3271–3281.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

No data

Related Author

No data

Related Institution

No data

AI问答

⁰