Open Access
| Issue |
E3S Web Conf.
Volume 375, 2023
8th International Conference on Energy Science and Applied Technology (ESAT 2023)
|
|
|---|---|---|
| Article Number | 03026 | |
| Number of page(s) | 5 | |
| Section | Energy Sustainability & Energy-Related Environmental Science | |
| DOI | https://doi.org/10.1051/e3sconf/202337503026 | |
| Published online | 27 March 2023 | |
- Zhou Hu, Jiang Yuechun, Chen Xu, et al. Short term load forecasting combining fuzzy clustering analysis and algebraic algorithm [J]. Journal of Power System and Automation, 2011, 23 (3): 101–105. [Google Scholar]
- He Miao, Ye Peng, He Ningning, et al. Overview of research on saturated load forecasting of power system [J]. Journal of Shenyang Institute of Engineering, 2017, 13 (4): 340–345 [Google Scholar]
- Yang Shuangji, Dong Qingfeng. Application of output unit consumption method in load forecasting [J]. Journal of North China University of Water Resources and Hydropower, 2009, 30 (6): 73–76 [Google Scholar]
- Qian Wen. Load Prediction by Electric Power Elastic Coefficient Method [J]. Yunnan Electric Power Technology, 2001, 29 (1): 41–44 [Google Scholar]
- Ding Qia, Lu Jiangang, Qian Yumei, et al. A practical extrapolation method for ultra short term load forecasting curve [J]. Power System Automation, 2004, 28 (16): 83–85 [Google Scholar]
- He Jing, Wei Gang, Xiong Lingling, et al. Fuzzy improvement of linear regression analysis method for load forecasting [J]. East China Power, 2003 (11): 21–23 [Google Scholar]
- Li Long, Wei Jing, Li Canbing, et al. Load Model Based on Artificial Neural Network [J]. Journal of Electrotechnics, 2015, 30(8): 225-230. [Google Scholar]
- Wang Qiumei. The principle and application of time series load forecasting [J]. East China Electric Power, 1993 (4): 37–39 [Google Scholar]
- Xiong Gang. Long term power demand forecasting based on grey system theory [J]. Journal of Shanghai Jiaotong University, 1993, 27 (5): 15–18 [Google Scholar]
- Wang Ben, Leng Beixue, Zhang Xihai, et al. Overview of the application of support vector machine in short-term load forecasting [J]. Journal of Power System and Automation, 2011, 23 (4): 115–121. [Google Scholar]
- Tai Nengling, Hou Zhijian, Li Tao, et al. Short term load forecasting method of power system based on wavelet analysis [J]. Chinese Journal of Electrical Engineering, 2003, 23 (1): 45–50 [Google Scholar]
- Cheng Xu, Kang Chongqing, Xia Qing, et al. Comprehensive model of short-term load forecasting [J]. Power System Automation, 2000 (9): 42–44 [Google Scholar]
- Chang Xianrong, Sun Jingwen. Load preprocessing based on improved fuzzy C-means clustering [J]. Journal of North China Electric Power University, 2014, 41 (1): 27–32. [14] Kang Chongqing, Xia Qing, Liu Mei. Power system load forecasting [M]. Beijing: China Power Press, 2017 [Google Scholar]
- Shao, Z; Gao, F; Zhang, Q; Yang, SL. Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting in China[J]. Applied Energy, 2015, 156: 502–518. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.