Knowledge Management System Of Guangzhou Institute of Energy Conversion, CAS
| Research on Short-Term Prediction Method and Application of Energy Consumption in Guangzhou and its Districts | |
| Zhang,Y T1,2,3; Cai,G T1,2,3; Ke,S J1,2,3,4; Gao,L P1,2,3 | |
| 2020-08-01 | |
| Source Publication | IOP Conference Series: Earth and Environmental Science
 |
| ISSN | 1755-1307 |
| Volume | 555Issue:1 |
| Abstract | Abstract Guangzhou’s energy consumption accounts for 24.9% of the energy consumption of Guangdong-Hong Kong-Macao Greater Bay Area (GBA). The improvement of Guangzhou’s energy management system has a significant impact and exemplary role on the energy management of GBA. Therefore, Guangzhou needs annual, quarterly and monthly energy consumption prediction for the requirements of energy consumption control and establishment of refined energy management system. Meanwhile, due to the lack of historical data, it also needs a short-term prediction method of energy consumption with short cycle and small sample. The paper provided variety of city level prediction methods and all districts energy consumption prediction method to predict the energy consumption of Guangzhou in 2018.Then this paper verify the prediction methods, and apply them to the prediction of energy consumption in 2019 and 2020. The results show that in the case of short-term prediction and small data samples, we can use a variety of factors to predict the energy consumption by refining the data collection area. And the result of all districts energy consumption prediction method is closer to the actual value than that of other methods. However, there are some difficulties in data collection of districts. Thus, in order to establish an accurate short-term prediction method, it is also necessary to strengthen the combination of city and district level energy monitoring and management systems, and expands the channels for collection and summary of district level energy data. Finally, in the future, the prediction method can be applied to GBA after the establishment of unified energy information statistics system of each city in GBA. |
| DOI | 10.1088/1755-1315/555/1/012087 |
| Language | 英语 |
| WOS ID | IOP:EES_555_1_012087 |
| Publisher | IOP Publishing |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.giec.ac.cn/handle/344007/29919 |
| Collection | 中国科学院广州能源研究所 |
| Affiliation | 1.Guangzhou Institute of Energy Conversion, CAS, Guangzhou, China 2.The Key Laboratory of Renewable Energy, CAS, Guangzhou, China 3.University of Chinese Academy of Sciences, Beijing, China 4.Nano Science and Technology Institute, University of Science and Technology of China, Suzhou, China |
| Recommended Citation GB/T 7714 | Zhang,Y T,Cai,G T,Ke,S J,et al. Research on Short-Term Prediction Method and Application of Energy Consumption in Guangzhou and its Districts[J]. IOP Conference Series: Earth and Environmental Science,2020,555(1). |
| APA | Zhang,Y T,Cai,G T,Ke,S J,&Gao,L P.(2020).Research on Short-Term Prediction Method and Application of Energy Consumption in Guangzhou and its Districts.IOP Conference Series: Earth and Environmental Science,555(1). |
| MLA | Zhang,Y T,et al."Research on Short-Term Prediction Method and Application of Energy Consumption in Guangzhou and its Districts".IOP Conference Series: Earth and Environmental Science 555.1(2020). |
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