Day-Ahead Hourly Forecasting of Solar Generation Based on Cluster Analysis and Ensemble Model
文献类型：期刊论文
| 作者 | Pan, Cheng1,2 ; Tan, Jie1
|
| 刊名 | IEEE ACCESS
 |
| 出版日期 | 2019 |
| 卷号 | 7页码:112921-112930 |
| 关键词 | Cluster analysis ensemble model ridge regression solar generation forecasting |
| ISSN号 | 2169-3536 |
| DOI | 10.1109/ACCESS.2019.2935273 |
| 通讯作者 | Tan, Jie(tan.jie@tom.com) |
| 英文摘要 | Accurate solar generation prediction is of great significance for grid dispatching and operation of photovoltaic power plants. In this paper, we propose a novel solar generation forecasting method based on cluster analysis and ensemble model. Two common ways to improve prediction accuracy are adopted. We first conduct cluster analysis based on solar generation to obtain a weather regime, which improves the computational efficiency and avoids the difficulty in selecting weather variables to participate in the clustering process. Then random forests with different parameters is established for different weather regimes, which is used as component models in the followed ensemble model. Finally, we weighted the predictions from different weather regimes to get the final results. To avoid manual design weights, ridge regression is used to calculate weights for each weather regime automatically. A large number of experiments have been carried out on freely available data sets to verify the performance of the proposed method. The experimental results show that our method predicts solar generation more accurately, which has broad prospects in practical application. |
| WOS关键词 | NEURAL-NETWORK ; POWER ; TERM ; PREDICTION |
| 资助项目 | National Natural Science Foundation of China[U1801263] |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000484307300004 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27253]  |
| 专题 | 综合信息系统研究中心_工业智能技术与系统 |
| 通讯作者 | Tan, Jie |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pan, Cheng,Tan, Jie. Day-Ahead Hourly Forecasting of Solar Generation Based on Cluster Analysis and Ensemble Model[J]. IEEE ACCESS,2019,7:112921-112930. |
| APA | Pan, Cheng,&Tan, Jie.(2019).Day-Ahead Hourly Forecasting of Solar Generation Based on Cluster Analysis and Ensemble Model.IEEE ACCESS,7,112921-112930. |
| MLA | Pan, Cheng,et al."Day-Ahead Hourly Forecasting of Solar Generation Based on Cluster Analysis and Ensemble Model".IEEE ACCESS 7(2019):112921-112930. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。