Open Access
Issue
E3S Web Conf.
Volume 143, 2020
2nd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2019)
Article Number 02013
Number of page(s) 7
Section Environmental Science and Energy Engineering
DOI https://doi.org/10.1051/e3sconf/202014302013
Published online 24 January 2020
  1. SHU Yinbiao. Accelerate the construction of a strong smart grid and Promote the energy production and consumption revolution[J]. Science and Technology Industry of China, 2018, No.347(5):12. [Google Scholar]
  2. ZHANG N, KANG C, XIA Q, et al. Modeling Conditional Forecast Error for Wind Power in Generation Scheduling[J]. IEEE Transactions on Power Systems, 2014, 29(3):1316-1324. [CrossRef] [Google Scholar]
  3. JIANG Y, CHEN X, KUN Y U, et al. Short-term wind power forecasting using hybrid method based on enhanced boosting algorithm[J]. Journal of Modern Power Systems and Clean Energy, 2017, 5(1):126-133. [CrossRef] [Google Scholar]
  4. Energy Observer. Can thermal power flexibility be able to break the contradiction between wind and fire [EB/OL] http://www.chinanengyuan.com/news/109222.html.2017-05-31/2019-07-26. [Google Scholar]
  5. CUI Yang, CHEN Zhi, YAN Gangui, et al. Coordinated Wind Power Accommodating Dispatch Model Based on Electric Boiler and CHP With Thermal Energy Storage[J]. Proceedings of the CSEE, 2016, 36(15):4072-4080. [Google Scholar]
  6. Ling C, Ge Q, Lu J, et al. Research on control strategy of electric heat storage boiler based on multi-agent[C]// Power & Renewable Energy. IEEE, 2017. [Google Scholar]
  7. DENG Tuoyu, TIAN Liang, LIU Jizhen. Spatial and Temporal Multiscale Analysis on Energy Storage in Heat Supply Units’ Boiler and Heat Supply Nets[J]. Proceedings of the CSEE, 2017, 37(2):599-605. [Google Scholar]
  8. HUANG X, XU Z, SUN Y, et al. Heat and power load dispatching considering energy storage of district heating system and electric boilers[J]. Journal of Modern Power Systems and Clean Energy, 2018. [Google Scholar]
  9. LYU Quan, JIANG Hao, CHEN Tianyou, et al. Wind Power Accommodation by Combined Heat and Power Plant with Electric Boiler and Its National Economic Evaluation[J]. Automation of Electric Power Systems, 2014, 38(1):6-12. DOI: 10.7500/AEPS201206124. [Google Scholar]
  10. LI Jiajia, HU Linxian. Research on Accommodation Scheme of Curtailed Wind Power Based on Peak-Shaving Electric Boiler in Secondary Heat Supply Network[J]. Power System Technology, 2015, 39(11):3286-3291. [Google Scholar]
  11. GUO Fenghui, HU Linxian, ZHOU Shengyu. Dispatching Model of Wind Power Accom-modation Based on Heat Storage Electric Boiler for Peak-load Regulation in Secondary Heat Supply Network[J]. Automation of Electric Power Systems, 2018, 42(19):50-56. DOI: 10.7500/AEPS20180130009. [Google Scholar]
  12. FANG Jinyu, SONG Ziqiu, HAN Xiaojuan, et al. Study on Wind Power Consumption Method Using Energy Storage Technology to Coordinate Heat Storage Electric Boilers[J]. Electrical and Energy Management Technology, 2017(13):16-21. [Google Scholar]
  13. LI Junhui, XING Zhitong, XING Jin, et al. Design of Optimized Planning Platform of Electric Boiler with Heat Storage to Enhance Wind Power Consumption.[J] Acta Energiae Solaris Sinica, 2017(13):16-21. [Google Scholar]
  14. WANG Zhibin, GU Bowen, ZU Guangxin, et al. Research on the operation mode of regenerative electric boiler system based on multi-wind bidding[J]. Heilongjiang Electric Power, 2018, 40(04):70-74. [Google Scholar]
  15. LIU Jiantao, ZHU Bingquan, MA Jingwei, et al. Study on Evaluation Indexes of Spinning Reserve Capacity Considering Reliability in Day-ahead Schedule[J]. Power System Technology, 2019, 43-(06):2147-2154. [Google Scholar]
  16. CHEN X, KANG C, O’MALLEY M, et al. Increasing the Flexibility of Combined Heat and Power for Wind Power Integration in China Modeling and Implications[J]. IEEE Transactions on Power Systems, 2015, 30(4):1848-1857. [CrossRef] [Google Scholar]
  17. WU Juai, XUE Yusheng, XIE Dongliang, et al. Evaluation and Simulation Analysis of Reserve Capability for Electric Vehicles[J]. Automation of Electric Power Systems, 2018, 42(13):101-107. DOI: 10.7500/AEPS20180130012. [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.