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Journal of Applied Mathematics
Volume 2014 (2014), Article ID 808549, 10 pages
Research Article

Hierarchical Agent-Based Integrated Modelling Approach for Microgrids with Adoption of EVs and HRES

School of Information Science and Engineering, Northeastern University, Shenyang 066004, China

Received 16 October 2013; Accepted 12 January 2014; Published 9 April 2014

Academic Editor: M. Montaz Ali

Copyright © 2014 Peng Han et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Navigant Consulting, Microgrids Research Assessment-Phase 2, 2006.
  2. EPRI/NRDC, Environmental Assessment of Plug-In Hybrid Electric Vehicles, 2007.
  3. P. Han, J. Wang, Y. Han, and Y. Li, “Resident plug-in electric vehicle charging modeling and scheduling mechanism in the smart grid,” Mathematical Problems in Engineering, pp. 1–8, 2014. View at Google Scholar
  4. P. Han, J. Wang, and Y. Han, “Dynamic-priority-based real-time charging management for plug-in electric vehicles in smart grid,” Journal of University of Science and Technology of China, vol. 42, no. 6, pp. 100–105, 2012. View at Google Scholar
  5. J. T. Salihi, “Energy requirements for electric cars and their impact on electric power generation and distribution systems,” IEEE Transactions on Industry Applications, vol. 9, no. 5, pp. 516–532, 1973. View at Google Scholar · View at Scopus
  6. A. Y. Saber and G. K. Venayagamoorthy, “Plug-in vehicles and renewable energy sources for cost and emission reductions,” IEEE Transactions on Industrial Electronics, vol. 58, no. 4, pp. 1229–1238, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. M. K. Deshmukh and S. S. Deshmukh, “Modeling of hybrid renewable energy systems,” Renewable and Sustainable Energy Reviews, vol. 12, no. 1, pp. 235–249, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. P. Bazan and R. German, “Hybrid simulation of renewable energy generation and storage grids,” in Proceedings of the Winter Simulation Conference, 2012.
  9. C. Petermann, S. Ben Amor, and A. Bui, “A complex system approach for a reliable smart grid modeling,” Advances in Knowledge-Based and Intelligent Information and Engineering Systems, pp. 149–158, 2012. View at Google Scholar
  10. W. Weniun, H. Wei, S. Yunling, and W. Guannan, “Study on control model of microgrid based on multi—agent method,” Modern Electric Power, vol. 29, no. 5, pp. 6–11, 2012. View at Google Scholar
  11. S. J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, Upper Saddle River, NJ, USA, 2nd edition, 2003.
  12. Z. Zhou, W. K. Chan, and J. H. Chow, “Agent-based simulation of electricity markets: a survey of tools,” Artificial Intelligence Review, vol. 28, no. 4, pp. 305–342, 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Sterman and J. D. Sterman, Business Dynamics: Systems Thinking and Modeling for a Complex World with CD-ROM, McGraw-Hill, Irwin, Pa, USA, 2000.
  14. S. A. Akhwanzada and R. M. Tahar, “Strategic forecasting of electricity demand using system dynamics approach,” International Journal of Environmental Science and Development, vol. 3, no. 4, pp. 328–333, 2012. View at Google Scholar
  15. AnyLogic-Multimethod Simulation Software and Solutions,
  16. FERC Annual Electric Balancing Authority and Planning Area Report,
  17. A. Rachakonda, Potentially Available Natural Gas Combined Cycle Capacity: Opportunities for Substantial CO2 Emissions Reductions, Massachusetts Institute of Technology, Cambridge, Mass, USA, 2010.
  18. P. Han, J. Wang, Y. Han et al., “Assessment of smart grid pev charging management in grid safety and environmental impact,” Advances in Information Sciences and Service Sciences, vol. 4, no. 13, pp. 144–152, 2012. View at Google Scholar