Open Access
Issue
E3S Web Conf.
Volume 729, 2026
1st Sustainable Power, Energy, Transportation, and Materials Conference (SPETM 2026)
Article Number 06004
Number of page(s) 8
Section Smart Grid and Smart City Technologies
DOI https://doi.org/10.1051/e3sconf/202672906004
Published online 31 July 2026
  1. M. Eremia, L. Toma and M. Sanduleac, The Smart City Concept in The 21st Century, Procedia Engineering, 181, 12–19, (2017). [Google Scholar]
  2. M. Farmanbar, K. Parham, O. Arild and C. Rong, A Widespread Review of Smart Grids towards Smart Cities, Energies, 12(23), 4484, (2019). [Google Scholar]
  3. O.S. Neffati, S. Sengan, K.D. Thangavelu, S.D. Kumar, R. Setiawan, M. Elangovan and P. Velayutham, Migrating From Traditional Grid to Smart Grid in Smart Cities Promoted in Developing Country, Sustainable Energy Technologies and Assessments, 45, 101–125, (2021). [Google Scholar]
  4. Santoshkumar Hampannavar, Suresh Chavhan, Swapna Mansani, Udaykumar R. Yaragatti, Electrical vehicle traffic pattern analysis and prediction in aggregation regions/parking lot zones to support V2G operation in smart grid: A cyberphysical system entity, International Journal of Emerging Electric Power Systems. February (2020). [Google Scholar]
  5. A. von Meier, D. Culler, A. McEachern, and R. Arghandeh, Micro-synchrophasors for distribution systems, in Proc. IEEE Innov. Smart Grid Technol. Conf. (ISGT), Washington, DC, USA, Feb. (2014), pp. 1–5. [Google Scholar]
  6. Mohammadi, Pooria, Shahab Mehraeen, and Hamidreza Nazaripouya. Sensitivity analysis-based optimal PMU placement for fault observability. IET Generation, Transmission & Distribution 15.4 (2021): 737–750. [Google Scholar]
  7. Lin, Chenhui, Wenchuan Wu, and Ye Guo. Decentralized robust state estimation of active distribution grids incorporating microgrids based on PMU measurements. IEEE Transactions on Smart Grid 11.1 (2019): 810–820. [Google Scholar]
  8. Rangu, Seshu Kumar, et al. Recent trends in power management strategies for optimal operation of distributed energy resources in microgrids: A comprehensive review. International Journal of Energy Research 44.13 (2020): 9889–9911. [Google Scholar]
  9. H. Gharavi and B. Hu, Scalable synchrophasors communication network design and implementation for real-time distributed generation grid, IEEE Trans. Smart Grid, vol. 6, no. 5, pp. 2539–2550, Sep. (2015). [Google Scholar]
  10. Sultana, U., et al. A review of optimum DG placement based on minimization of power losses and voltage stability enhancement of distribution system. Renewable and Sustainable Energy Reviews 63 (2016): 363–378. [Google Scholar]
  11. Gou, Bei, and Rajesh G. Kavasseri. Unified PMU placement for observability and bad data detection in state estimation. IEEE Transactions on Power Systems 29.6 (2014): 2573–2580. [Google Scholar]
  12. Y.-F. Huang, S. Werner, J. Huang, N. Kashyap, and V. Gupta, State estimation in electric power grids: Meeting new challenges presented by the requirements of the future grid, IEEE Signal Process. Mag., vol. 29, no. 5, pp. 33–43, Sep. 2012. [Google Scholar]
  13. Vejdan, Sadegh, Majid Sanaye-Pasand, and Om P. Malik. Accurate dynamic phasor estimation based on the signal model under off-nominal frequency and oscillations. IEEE Transactions on Smart Grid 8.2 (2015): 708–719. [Google Scholar]
  14. S. Hampannavar, C. B. Teja, M. Swapna and U. Kumar, Performance Improvement of M-Class Phasor Measurement Unit (PMU) using Hamming and Blackman Windows, 2020 IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy (PESGRE2020), Cochin, India, 2020, pp. 1–5, doi: 10.1109/PESGRE45664.2020.9070382. [Google Scholar]
  15. Giotopoulos, Vasilis, and Georgios Korres. Implementation of phasor measurement unit based on phase-locked loop techniques: A comprehensive review. Energies 16.14 (2023): 5465. [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.