摘要
基于2010—2011年北京地区逐时辐射及气象资料,提出有效的天气类型识别方法,研究适用于北京地区的水平面直散分离模型并对其进行本地化修正,同时验证目前主流的斜面辐射模型的性能,并建立和评估由各种天气类型对应的最优直散分离与斜面辐射模型级联而成的综合模型。结果表明:水平面直散分离模型中,修正Erbs、修正Liu&Jordan模型的预测误差较小;斜面辐射模型预测精度均与天气类型密切相关;将筛选出的组合直散分离模型的输出作为天气细分后斜面辐射模型的输入进行两级级联,对无直、散辐射观测地区的斜面辐射推算及光伏出力预测等具有指导意义。
An effective identification method of weather type is proposed based on the hourly radiation and meteorological data in Beijing area from 2010 to 2011,the horizontal diffuse radiation fraction model sui-table for Beijing area is researched and carried out for localization correction,meanwhile the performances of current main inclined plane radiation models are verified,and the comprehensive model cascaded by the optimal diffuse fraction and inclined plane radiation models corresponding to each weather type is estab⁃lished and evaluated.Results show that the prediction error of the modified Erbs and Liu&Jordan models is small in horizontal plane diffuse fraction model,the prediction accuracy of inclined plane radiation model is closely related to weather type,and two stage cascade with the output of selected composed diffuse radia⁃tion fraction model as the input of inclined plane radiation model after the classification of weather types can guide the estimation of inclined plane radiation and photovoltaic output prediction in the area without observation of diffuse radiation.
作者
李芬
林逸伦
王仁奎
李春阳
王育飞
成驰
童力
LI Fen;LIN Yilun;WANG Renkui;LI Chunyang;WANG Yufei;CHENG Chi;TONG Li(School of Electric Power Engineering,Shanghai University of Electric Power,Shanghai 200090,China;Foshan Power Supply Bureau of Guangdong Power Grid Company,Foshan 528000,China;Hubei Provincial Meteorological Service Center,Wuhan 430205,China;State Grid Zhejiang Electric Power Research Institute,Hangzhou 310014,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2021年第8期76-81,共6页
Electric Power Automation Equipment
基金
国家自然科学基金面上项目(51777120)
上海绿色能源并网工程技术研究中心项目(13DZ2251900)
上海市高校教师培养资助计划项目(CXYsdl18012)。
关键词
散射比
斜面辐射
修正清晰度指数
总云量
天气类型
diffuse radiation fraction
inclined plane radiation
modified clearness index
total cloud cover
weather type