Open Access
| Issue |
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
|
|
|---|---|---|
| Article Number | 03089 | |
| Number of page(s) | 4 | |
| Section | Digital Signal and Image Processing | |
| DOI | https://doi.org/10.1051/matecconf/201817303089 | |
| Published online | 19 June 2018 | |
- Zhang Suxiang, Zhao Binzhen, Wang Fengyu, et al. Short-term power load forecasting based on big data[J]. Proceedings of the CSEE, 2015, 35(1): 37-42(in Chinese). [Google Scholar]
- Informatization Committee of the CSEE. White paper of electric power big data of China[M]. Beijing: China Electric Power Press, 2013: 10-15(in Chinese). [Google Scholar]
- Sun Bolin. Big data technology and its application in power industry[J] . Electric Age, 2013(8) : 18-23(in Chinese). [Google Scholar]
- Huang Yanhao, Yu Zhihong, Xie Chang. Study on the application ofelectric power big data technology in power system simulation[J] . Proceedings ofthe CSEE, 2015,35(1): 13-22(in Chinese.) [Google Scholar]
- Zhang Dongxia, Miao Xin, Liu Liping,et al. Research on development strategy for smart grid big data[J]. Proceedings of the CSEE, 2015, 35(1): 2-12(in Chinese) [Google Scholar]
- Meng Xiaofeng, Ci Xiang. Big data management: concepts, techniques and challenges[J] . Journal of Computer Research and Development, 2013, 50(1): 146-169(in Chinese). [Google Scholar]
- Li Guibing, Luo Hong . Intelligent data analysis under the background of big data[J] . Science & Technology Information, 2013(30): 11-12(in Chinese). [Google Scholar]
- Rao Wei, Ding Jianyong, Lu Qingkai . Cloud computing platform for smart grid[J] . East China Electric Power, 2011, 39(9): 1493-1496. [Google Scholar]
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