考虑风光出力动态相关性的场景生成方法

高帆; 包道日娜; 狄彦强; 张少华

doi:10.19912/j.0254-0096.tynxb.2023-1873

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (8) : 256-264. DOI: 10.19912/j.0254-0096.tynxb.2023-1873

考虑风光出力动态相关性的场景生成方法

高帆¹, 包道日娜¹, 狄彦强², 张少华³

作者信息 +

SCENE GENERATION METHOD CONSIDERING DYNAMIC CORRELATION OF WIND AND PHOTOVOLTAIC OUTPUTS

Gao Fan¹, Bao Daorina¹, Di Yanqiang², Zhang Shaohua³

Author information +

文章历史 +

摘要

针对风光出力的不确定性问题提出一种利用混合Copula函数结合多元正态分布的风光出力场景生成方法。基于风电功率和光伏功率的历史数据建立风光出力的联合分布模型,进一步通过多元正态分布和协方差矩阵生成具有动态相关的风光出力联合分布序列;采用马尔科夫链蒙特卡洛抽样法生成风光出力场景的随机分布数,通过逆变换法得到相应的风光出力场景;对不同方法生成出力场景进行对比,分析动态相关下风光出力场景的拟合效果和耦合效应。结果验证所提方法的有效性,生成的出力场景能够较好地刻画风光单独出力和耦合出力时的不确定性。

Abstract

A hybrid Copula function combined with multivariate normal distribution is proposed to generate scenarios of wind and photovoltaic powers in response to the uncertainty. Based on the historical data of wind power and photovoltaic power, the joint distribution model of wind and PV is established, and the joint distribution sequence of wind and PV outputs with dynamic correlation is further generated by the multivariate normal distribution and covariance matrix. The random distribution number of wind and photovoltaic power scenarios are generated by the Markov Chain Monte Carlo Sampling method, and the corresponding wind and PV outputs scenarios are obtained by the inverse transformation method; the output scenarios generated by the different methods are compared, and the fitting effect and coupling effect of the wind power and photovoltaic power scenarios under dynamic correlation are analyzed. The results verify the validity of the proposed method, and the output scenarios can better portray the uncertainty of single output and coupled output of wind and PV power system.

导出引用

高帆, 包道日娜, 狄彦强, 张少华. 考虑风光出力动态相关性的场景生成方法[J]. 太阳能学报. 2024, 45(8): 256-264 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1873

Gao Fan, Bao Daorina, Di Yanqiang, Zhang Shaohua. SCENE GENERATION METHOD CONSIDERING DYNAMIC CORRELATION OF WIND AND PHOTOVOLTAIC OUTPUTS[J]. Acta Energiae Solaris Sinica. 2024, 45(8): 256-264 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1873

中图分类号： TM7

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