Modelling of Wind Power Uncertainty Considering Heteroskedasticity Effect and Its Application in Power System Dispatching

Lixing LI; Shihong MIAO; Qingyu TU; Yaowang LI; Chao LI; Simo DUAN

doi:10.7500/AEPS20190430016

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Modelling of Wind Power Uncertainty Considering Heteroskedasticity Effect and Its Application in Power System Dispatching

Basic Research | 更新时间：2025-06-16

- Modelling of Wind Power Uncertainty Considering Heteroskedasticity Effect and Its Application in Power System Dispatching
- Automation of Electric Power Systems Vol. 44, Issue 8, Pages: 36-47(2020)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China;National Natural Science Foundation of China;State Grid Corporation of China
- DOI：10.7500/AEPS20190430016
  CLC：
- Received：30 April 2019，
  
  Revised：2019-10-18，
  
  Published Online：05 March 2020，
  
  Published：25 April 2020
- 稿件说明：
移动端阅览
李力行,苗世洪,涂青宇等.考虑异方差效应的风电不确定性建模及其在调度中的应用[J].电力系统自动化,2020,44(8):36-47.

LI Lixing,MIAO Shihong,TU Qingyu,et al.Modelling of Wind Power Uncertainty Considering Heteroskedasticity Effect and Its Application in Power System Dispatching[J].Automation of Electric Power Systems,2020,44(8):36-47.
李力行,苗世洪,涂青宇等.考虑异方差效应的风电不确定性建模及其在调度中的应用[J].电力系统自动化,2020,44(8):36-47. DOI： 10.7500/AEPS20190430016.

LI Lixing,MIAO Shihong,TU Qingyu,et al.Modelling of Wind Power Uncertainty Considering Heteroskedasticity Effect and Its Application in Power System Dispatching[J].Automation of Electric Power Systems,2020,44(8):36-47. DOI： 10.7500/AEPS20190430016.

摘要

随着风电在电力系统中渗透率的不断提升，其不确定性为电网的安全经济运行带来了重大挑战。为获得精准的风电不确定性模型，帮助运行人员实现系统的安全经济运行，文中提出了考虑异方差效应的风电预测误差条件概率分布建模方法。首先，分析了风电预测误差与各类因素的相依性水平，并基于分析结果与动态Copula理论，建立了风电波动性与风电预测误差的动态相依性模型；之后，针对边缘分布所显示出的时域特征，结合差分整合移动平均自回归（ARIMA）模型与广义自回归条件异方差（GARCH）模型，考虑异方差效应，建立了时变边缘分布模型；最后，将两模型相结合，给出了不同波动水平下的风电条件预测误差分布情况，并在不确定性机组组合模型中进行验证，证明了模型的有效性。

Abstract

As the penetration rate of wind power in the power system continues to increase

its uncertainty poses a great challenge to the safe and economic operation of the power system. In order to obtain accurate wind power uncertainty model and help operators to achieve safe and economic operation of the system

this paper proposes a conditional probability distribution modelling method of wind power forecasting error considering the heteroskedasticity effect. Firstly

the dependence of wind power forecasting error and various factors is analyzed. Based on the results and the dynamic Copula theory

a dynamic dependence model of wind power forecast error is established. Then

based on the time-domain features displayed by the edge distribution

combined with the autoregressive integrated moving average (ARIMA) model and the generalized autoregressive conditional heteroskedasticity (GARCH) model

this paper develops a time-varying edge distribution model with the consideration of heteroskedasticity effect. Finally

the two models are combined to give the forecasting error distribution of wind power conditions at different fluctuation levels

and the verification is performed in the uncertain unit combination model

which proves the validity of the model.

关键词

Keywords

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