电力系统自动化2017，Vol.41Issue(6)：30-36,7.DOI:10.7500/AEPS20160604002
光伏发电功率持续时间特性的概率分布定量分析
Quantitative Analysis of Probability Distribution for Duration Time Characteristic of Photovoltaic Power
摘要
Abstract
With the rapid increase of the photovoltaic(PV)power penetration,it is essential to precisely consider the impacts of PV power on power system planning and operation.However,due to the uncertainty and volatility of PV generation,statistical approaches are required to describe its features.This paper quantitatively depicts the distribution of the time for PV power to continuously maintain a certain output status.Firstly,the output status of PV power is defined by the operation point and deviation range of PV power,then the duration time characteristic is proposed.It is indicated by numerical results based on field measured data of China and Germany that:there is an obvious'double peaks property' in PV power duration time distributions and it can be properly fitted by the mixture of inverse Gaussian and generalized extreme value probability density function.The'double peaks property' further reveals that under frequent disturbances of clouds,PV power will maintain the current output status for only a few minutes.Otherwise,PV generation can smoothly follow the regular changes of solar radiation and keep the current output status unchanged for hours.Research results of this paper can provide important references for the optimal choice of the measurement and control time interval in the PV generation dispatch,validation of the maximum output variability,and for design and selection of power equipment in transmission systems.关键词
光伏发电/持续时间特性/逆高斯分布/广义极值分布Key words
photovoltaic generation/characteristic of duration time/inverse Gaussian distribution/generalized extreme value distribution引用本文复制引用
黎嘉明,艾小猛,文劲宇,方家琨,谢海莲..光伏发电功率持续时间特性的概率分布定量分析[J].电力系统自动化,2017,41(6):30-36,7.基金项目
国家自然科学基金资助项目(51577075) （51577075）
国家重点研发计划资助项目(2016YFB0900400,2016YFB0900403) （2016YFB0900400,2016YFB0900403）
中国博士后科学基金资助项目(2016M590694).This work is supported by National Natural Science Foundation of China (No.51577075),National Key Research and Development Program of China (No.2016YFB0900400,No.2016YFB0900403) and Post-doctoral Science Foundation of China(No.2016M590694). （2016M590694）
