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计及预测误差动态相关性的多风电场联合出力不确定性模型
作者:
作者单位:

1. 华中科技大学电气与电子工程学院, 湖北省武汉市 430074;2. 强电磁工程与新技术国家重点实验室, 华中科技大学, 湖北省武汉市 430074;3. 电力安全与高效湖北省重点实验室, 华中科技大学, 湖北省武汉市 430074

摘要:

为实现对多风电场联合出力不确定性的精细化建模,提出了计及预测误差动态相关性的多风电场联合出力不确定性建模方法。首先,分析了同区域风电场的出力及出力预测误差动态相关性特征。进一步,针对此特征,引入高维动态藤Copula理论,建立了多风电场预测出力及预测误差的联合分布模型。最终,将以上模型与基于Copula函数的离散卷积法相结合,建立了计及预测误差动态相关性的多风电场联合出力不确定性模型,并以置信区间对多风电场联合出力不确定性进行了离散化表征。仿真结果表明,对比其他模型,所提模型拟合精度更高,拟合过程与预测方法解耦,灵活性更强。

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基金项目:

国家重点研发计划资助项目(2017YFB0902600);国家电网公司科技项目(SGJS0000DKJS1700840)。

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作者简介:


Uncertainty Model of Combined Output for Multiple Wind Farms Considering Dynamic Correlation of Prediction Errors
Author:
Affiliation:

1. School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; 2. State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China; 3. Key Laboratory of Electric Power Security and High Efficiency of Hubei Province, Huazhong University of Science and Technology, Wuhan 430074, China

Abstract:

In order to realize the refinement modeling of the combined output for multiple wind farms, this paper proposes an uncertainty model of combined output for multiple wind farms considering dynamic correlation of prediction errors. Firstly, the dynamic correlation characteristics of the wind power output and output prediction errors of the wind farms in the same region are analyzed. Furthermore, the high-dimensional dynamic vine Copula theory is introduced to establish a joint distribution model of prediction output and prediction error for multiple wind farms. Combining the above model with the discrete convolution method based on Copula function, the uncertainty model of combined output for multiple wind farms considering the dynamic correlation of prediction error is established. And the uncertainty of combined output for multiple wind farms is discretely represented by confidence intervals. The simulation results show that, compared with other models, the proposed model has higher fitting precision, and the fitting process is decoupled from the prediction method, which is more flexible. This work is supported by National Key R&D Program of China(No. 2017YFB0902600)and State Grid Corporation of China(No. SGJS0000DKJS1700840).

Keywords:

Foundation:
引用本文
[1]段偲默,苗世洪,李力行,等.计及预测误差动态相关性的多风电场联合出力不确定性模型[J].电力系统自动化,2019,43(22):31-37. DOI:10.7500/AEPS20190401011.
DUAN Simo, MIAO Shihong, LI Lixing, et al. Uncertainty Model of Combined Output for Multiple Wind Farms Considering Dynamic Correlation of Prediction Errors[J]. Automation of Electric Power Systems, 2019, 43(22):31-37. DOI:10.7500/AEPS20190401011.
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  • 收稿日期:2019-04-01
  • 最后修改日期:2019-10-16
  • 录用日期:2019-09-17
  • 在线发布日期: 2019-10-10
  • 出版日期: 2019-11-25
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