Short-term Photovoltaic Output Forecasting Based on Correlation of Meteorological Data

被引：0
|
作者：
Zhang, Wencheng [1 ]
Zheng, Xiaoxing [2 ]
Sun, Xiaoguang [3 ]
Geng, Jianyu [3 ]
Niu, Qiang [4 ]
Li, Jiefu [4 ]
Bao, Chengjia [5 ]
机构：
[1] China Agr Univ, Beijing, Peoples R China
[2] North China Elect Power Univ, Beijing, Peoples R China
[3] Changchun Elect Power Bur SGCC, Changchun, Jilin, Peoples R China
[4] Jilin Elect Power Bur SGCC, Jilin, Jilin, Peoples R China
[5] Maintenance Co Gansu SGCC, Lanzhou, Gansu, Peoples R China
来源：
2017 IEEE CONFERENCE ON ENERGY INTERNET AND ENERGY SYSTEM INTEGRATION (EI2) | 2017年
关键词：
distributed generation; PV output; parameter selection; support vector regression method; SYSTEMS; MODEL;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
a short-term load forecasting method of photovoltaic (PV) output based on weak correlation between meteorological date and PV output is proposed. The Pearson cor-relation coefficient method is used to make out the main affecting factor of PV output. Fuzzy clustering analysis method is used to attain similar days and then support vector regression (SVR) forecasting model with excellent learning ability for small sample is established. And then a two-stage parameter determining method is carried out. Finally, the effectiveness of the proposed method is verified.
引用
收藏
页码：442 / 446
页数：5
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