Open Access
E3S Web Conf.
Volume 53, 2018
2018 3rd International Conference on Advances in Energy and Environment Research (ICAEER 2018)
Article Number 01012
Number of page(s) 6
Section Energy Engineering, Materials and Technology
Published online 14 September 2018
  1. L.F. Cheng, T. Yu, X.S. Zhang, et al. Cyberphysical-social systems based smart energy robotic dispatcher and its knowledge automation: framework, techniques and challenges. Proceedings of the CSEE, 2018, 38(1): 25-40. [Google Scholar]
  2. L.F. Cheng, Z.Y. Zhang, H.R. Jiang, et al. Local energy management and optimization: A novel energy universal service bus system based on energy Internet technologies. Energies, 2018, 11(5), 1160. [CrossRef] [Google Scholar]
  3. Z. Wang, S. Bian, Y. Liu, et al. The load characteristics classification and synthesis of substations in large area power grid. International Journal of Electrical Power & Energy Systems, 2013, 48(1): 71-82. [CrossRef] [Google Scholar]
  4. X. Xu, J. Xi, Y. Li, et al. Research on the dynamic frequency characteristic of large-scale power grid considering the action of power system splitting and load shedding. In proceedings of the International Conference on Power System Technology, 2014, 103-108. [Google Scholar]
  5. L.I. Hu, Q. Zhou, J. Shi, et al. Impact of large-scale electric vehicles connected to power grid on the load characteristics in nanjing city and the corresponding countermeasures. Proceedings of the CSU-EPSA, 2016. [Google Scholar]
  6. Y.G. Huang, Y. Lu. Characteristic analysis and forecasting of summer daily peak load. Power DSM, 2009, 11(4): 35-37. [Google Scholar]
  7. Y.F. Yin. Analysis on impact of air temperature on local load characteristics. Guangdong Electric Power, 2011, 24(10): 79-83. [Google Scholar]
  8. L.F. Cheng, T. Yu, G.P. Wang, et al. Hot spot temperature and grey target theory-based dynamic modelling for reliability assessment of transformer oil-paper insulation systems: A practical case study. Energies, 2018, 11(1), 249. DOI:10.3390/en11010249 [CrossRef] [Google Scholar]
  9. L.F. Cheng, T. Yu. Dissolved gas analysis principlebased intelligent approaches to fault diagnosis and decision making for large oil-immersed power transformers: A survey. Energies, 2018, 11(4), 913. DOI: 10.3390/en11040913 [CrossRef] [Google Scholar]
  10. W.Y. Liu, D.Y. Men, J.F. Liang, et al. Monthly load forecasting based on grey relational degree and least squares support vector machine. Power System Technology, 2012, 36(8): 228-231. [Google Scholar]
  11. L.F. Cheng, B. Zhou, D.H. Cai, et al. Lifetime assessment and optimized maintenance system of transformers based on the HST model. Lecture Notes in Electrical Engineering, v 334, p 417-430, 2015. DOI: 10.1007/978-3-319-13707-0_46 [CrossRef] [Google Scholar]
  12. Y.J. Zhang, H. Shi. Distribution network energysaving investment compact planning based on grey connectedness weighting. Automation of Electric Power Systems, 2010, 34(22): 46-50. [Google Scholar]
  13. B. Song, Y. Ping, Y. Luo, et al. Study on the fault diagnosis of transformer based on the grey relational analysis. In Proceedings of the International Conference on Power System Technology, 2002. Proceedings. Powercon. IEEE,. 2002, 4: 2231-2234. [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.