基于非对称Copula函数的风电场黑启动储能优化配置

刘威鹏; 刘玉田

doi:10.7500/AEPS20191219007

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基于非对称Copula函数的风电场黑启动储能优化配置

学术研究 | 更新时间：2025-06-16

- 基于非对称Copula函数的风电场黑启动储能优化配置
- Optimal Configuration of Energy Storage for Wind Farm Black-start Based on Asymmetric Copula Function
- 电力系统自动化-方正平台 2020年44卷第19期页码：47-54
- 作者机构：
  
  电网智能化调度与控制教育部重点实验室(山东大学)，山东省济南市 250061
- 作者简介：
  
  刘威鹏(1992—)，男，博士研究生，主要研究方向：电力系统运行与控制。E-mail：wpliu@mail.sdu.edu.cn
  刘玉田(1964—)，男，通信作者，博士，教授，博士生导师，主要研究方向:电力系统运行与控制。E-mail：liuyt@sdu.edu.cn
- 基金信息：
  
  国家重点研发计划资助项目(2017YFB0902600)
- DOI：10.7500/AEPS20191219007
  中图分类号：
- 收稿日期：2019-12-19，
  
  修回日期：2020-06-28，
  
  网络出版日期：2020-08-13，
  
  纸质出版日期：2020-10-10
- 稿件说明：
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刘威鹏,刘玉田.基于非对称Copula函数的风电场黑启动储能优化配置[J].电力系统自动化,2020,44(19):47-54.

LIU Weipeng,LIU Yutian.Optimal Configuration of Energy Storage for Wind Farm Black-start Based on Asymmetric Copula Function[J].Automation of Electric Power Systems,2020,44(19):47-54.
刘威鹏,刘玉田.基于非对称Copula函数的风电场黑启动储能优化配置[J].电力系统自动化,2020,44(19):47-54. DOI： 10.7500/AEPS20191219007.

LIU Weipeng,LIU Yutian.Optimal Configuration of Energy Storage for Wind Farm Black-start Based on Asymmetric Copula Function[J].Automation of Electric Power Systems,2020,44(19):47-54. DOI： 10.7500/AEPS20191219007.

摘要

在高比例风电接入的区域电网中，为加快停电后的恢复速度，可以采用风电场配置储能系统作为黑启动电源。针对启动发电机组过程中风电出力平滑问题，提出一种基于非对称Copula函数的储能优化配置方法，以投资成本最小为目标，使风电场具备黑启动电源的能力。将储能的功率配置和容量配置看作2个随机变量，根据样本数据分析两者之间的相关特性，基于非对称Copula函数建立二元联合概率分布进行准确描述。利用核密度估计得到2个边缘概率分布，通过极大似然估计和拟合度测试确定最佳Copula函数。仿真结果表明

所提非对称Copula函数拟合准确度更高，得到的储能配置成本更低。

Abstract

In the regional power grid integrated with high proportional wind power

wind farms can be configured with energy storage system (ESS) as black-start power sources to accelerate the restoration after power outage. Aiming at smoothing wind power output in the process of starting generation units

an optimal configuration method of energy storage based on the asymmetric Copula function is proposed to equip the wind farms as black-start power sources with the minimum investment cost as the goal. The power configuration and capacity configuration of ESS are considered as two random variables

and the correlation characteristics between them are analyzed based on sample data

which are described accurately by the established binary joint probability distribution based on the asymmetric Copula function. The two marginal distributions are obtained by using kernel density estimation

and the optimal Copula function is determined based on maximum likelihood estimation and goodness of fitting test. Simulation results demonstrate that the proposed asymmetric Copula function has higher fitting accuracy and lower ESS configuration cost.

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references

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