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

Yuming Shen, Hao Yang, Jiayin Xu, Kun Li, Jiaqing Wang and Qianlong Zhu ()
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Yuming Shen: Economic & Technical Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230022, China
Hao Yang: Economic & Technical Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230022, China
Jiayin Xu: Economic & Technical Research Institute, State Grid Anhui Electric Power Co., Ltd., Hefei 230022, China
Kun Li: State Grid Anhui Electric Power Co., Ltd., Hefei 230009, China
Jiaqing Wang: State Grid Anhui Electric Power Co., Ltd., Hefei 230009, China
Qianlong Zhu: School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China

Energies, 2024, vol. 17, issue 19, 1-14

Abstract: The error threshold is the cornerstone to balance the mathematical complexity and simulation speed of wind farm (WF) equivalent models, and can promote the standardization process of equivalent methodology. Due to differences in power system conditions and model evaluation standards in different countries, the form and indexes of error thresholds of WF equivalent models have not been unified yet. This paper proposes a theoretical method for quantifying the minimum risk of error threshold of WF equivalent models based on the Bayes discriminant criterion. Firstly, the Euclidean errors of WF equivalent models in different periods are quantified, and the probability density distributions of the errors are fitted by kernel density estimation. Secondly, the real-time weighted prior probability algorithm is used to obtain the prior probability of a valid WF equivalent model, and the different losses caused by the missed judgment and misjudgment of the model validity to power systems are taken into account. Thirdly, the minimum risk quantification model of error threshold is established based on the Bayes discriminant criterion, and the feasibility of the proposed method is verified by an actual WF with numerical examples. Compared with the existing error thresholds, the proposed error threshold can more quickly and accurately determine the validity of WF equivalent models.

Keywords: error of WF equivalent model; threshold quantization; Bayes discriminant criterion; prior probability; discriminant loss ratio (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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