全球能源互联网（英文）2021，Vol.4Issue(6)：608-618,11.DOI:10.14171/j.2096-5117.gei.2021.06.008
基于不确定性分析理论的光伏电站储能容量配置方法
Research on energy storage capacity configuration for PV power plants using uncertainty analysis and its applications
摘要
Abstract
Compensating for photovoltaic (PV) power forecast errors is an important function of energy storage systems. As PV power outputs have strong random fluctuations and uncertainty, it is difficult to satisfy the grid-connection requirements using fixed energy storage capacity configuration methods. In this paper, a method of configuring energy storage capacity is proposed based on the uncertainty of PV power generation. A k-means clustering algorithm is used to classify weather types based on differences in solar irradiance. The power forecast errors in different weather types are analyzed, and an energy storage system is used to compensate for the errors. The kernel density estimation is used to fit the distributions of the daily maximum power and maximum capacity requirements of the energy storage system; the power and capacity of the energy storage unit are calculated at different confidence levels. The optimized energy storage configuration of a PV plant is presented according to the calculated degrees of power and capacity satisfaction. The proposed method was validated using actual operating data from a PV power station. The results indicated that the required energy storage can be significantly reduced while compensating for power forecast errors.关键词
光伏发电/天气分类/误差分析/核密度估计/储能容量配置Key words
PV power/Weather classification/Error analysis/Kernel density estimation/Energy storage capacity configuration引用本文复制引用
朱红路,侯汝印,蒋婷婷,吕清泉..基于不确定性分析理论的光伏电站储能容量配置方法[J].全球能源互联网（英文）,2021,4(6):608-618,11.基金项目
This work was supported by Nation Key R&D Program of China(2021YFE0102400). （2021YFE0102400）
