Open Access
Issue |
E3S Web Conf.
Volume 256, 2021
2021 International Conference on Power System and Energy Internet (PoSEI2021)
|
|
---|---|---|
Article Number | 02006 | |
Number of page(s) | 5 | |
Section | Energy Internet R&D and Smart Energy Application | |
DOI | https://doi.org/10.1051/e3sconf/202125602006 | |
Published online | 10 May 2021 |
- Yang Ting, Zhai Feng, Zhao Yingjie, et al. Explanation and prospect of ubiquitous electric power Internet of things[J]. Automation of Electric Power Systems, 2019, 43(13): 9–20+53. [Google Scholar]
- Wang Beibei. Research on consumers’ response characteristics under ability smart grid: a literatures survey[J]. Proceedings of the CSEE, 2014, 34(22): 3654–3663. [Google Scholar]
- Bahrami S, Sheikhi A. From Demand Response in Smart Grid Toward Integrated Demand Response in Smart Energy Hub[J]. IEEE Transactions on Smart Grid, 2015: 1-1. [Google Scholar]
- Liao Nihuan, Hu Zhihong, Ma Yingying, et al. Review of the short-term load forecasting methods of electric power system[J]. Power System Protection and Control, 2011, 39(01): 147–152. [Google Scholar]
- Xia Bo, Yang Chao, Li Chong. Review of the short-term load forecasting methods of electric power system [J]. Power Systems and Big Data, 2018, 21(07): 22–28. [Google Scholar]
- Dudek G. Artificial Immune System For Short-Term Electric Load Forecasting[J]. IEEE Transactions on Evolutionary Computation, 2017, PP(99): 1-1. [Google Scholar]
- Zhang Zhisheng, Yu Daolin. RBF-NN based short term load forecasting model considering comprehensive factors affecting demand response[J]. Proceedings of the CSEE, 2018, 38(06): 1631–1638+1899. [Google Scholar]
- Su Xiaolin, Liu Xiaojie, Yan Xiaoxia, et al. Short-term load forecasting of active distribution network based on demand response[J]. Automation of Electric Power Systems, 2018, 42(10): 60–66+134. [Google Scholar]
- Chen Lina, Zhang Zhisheng, Yu Daolin. Short-term load forecasting model of power system based on generalized demand side resources aggregation[J]. Power System Protection and Control, 2018, 46(15): 45–51. [Google Scholar]
- Peng Wen, Wang Jinrui, Yin Shanqing. Short-term load forecasting model based on Attention-LSTM in electricity market[J]. Power System Technology, 2019, 43(05): 1745–1751. [Google Scholar]
- Guo Yizong, WANG Chutong, SHI Yunhui, et al. Comprehensive optimization configuration of electric and thermal cloud energy storage in regional integrated energy system[J]. Power System Technology, 2020, 44(5):1611-1621. [Google Scholar]
- Guo Yizong, Feng Bin, Yue Boxiong, et al. Ultra-short-term Load Forecasting Considering Demand Response in Load Aggregator Mode[J]. Automation of Electric Power Systems, 2021, 45(1):79-87. [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.