Unconventional Hybrid System Control for Traction Microgrids

Yogesh Shivaji PawarResearch scholar, Bhabha University, Bhopal, Madhyapradesh, IndiaDr. Ashok Kumar JhalaAssociate Professor, Dept. of Electrical Engineering, Bhabha University, Bhopal, Madhyapradesh, India

Vol 7 No (2023): Volume 7, Special Issue of ICRTET- 2023 | Pages: 1-5

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 16-07-2023

doi Logo IRJIET.ICRTET01

Abstract

The power consumption of the Indian Railways is around 2.5 percent of the country’s total electricity consumption. To reduce the consumption of electricity comes from power plants. so, we Hybridizing (it consists of P.V. and wind turbine generators and battery storage units) the railway substations with hybrid energy sources based on renewable energy sources and storage units connected to a dc bus may be a solution to contribute to the partial independence of energy producers in the sector of traffic rail. This project proposes a reversible, self adaptive, autonomous and intelligent distributed generator connected to dc bus control by multi agent system.

Keywords

Braking and tracking energy, Jade, MacsimJX, MATLAB Simulink, multiagent system (MAS), penalty costs, railway microgrid, renewable energy sources (RES)


Citation of this Article

Yogesh Shivaji Pawar, Dr. Ashok Kumar Jhala, “Unconventional Hybrid System Control for Traction Microgrids” in proceeding of International Conference of Recent Trends in Engineering & Technology (ICRTET – 2023), Organized by SCOE, Sudumbare, Pune, India, Published in IRJIET, Volume 7, Special issue of ICRTET-2023, pp 1-5, June 2023.

References
  1. R. R. Pecharroman, A. Lopez-Lopez, A. P. Cucala, and A. Fernandez Cardador, “Riding the rails to DC power efficiency: Energy efficiency in dc-electrified metropolitan railways,” IEEE Electrific. Mag., vol. 2, no. 3, pp. 32–38, Sep. 2014.
  2. S. Boudoudouh and M. Maaroufi, “Smart control in a DC railway by ˆ multi agent system (MAS),” in Proc. Int. Conf. Elect. Syst. Aircr. Railway Ship Propulsion Road Veh. Int. Transp. Electrific. Conf., 2016, pp. 1–6.
  3. Hajizadeh and M. A. Golkar, “Intelligent power management strategy of hybrid distributed generation system,” Int. J. Elect. Power Energy Syst., vol. 29, pp. 783–795, 2007.
  4. H. Ibrahim et al., “Integration of wind energy into electricity systems: Technical challenges and actual solutions,” Energy Proceedia, vol. 6, pp. 815–824, 2011.
  5. B. Robyns et al., Electricity Production from Renewables Energies. New York, NY, USA: Wiley 2012.
  6. M. Alvarez-Herault, “Architectures of the distribution future networks in the presence of decentralized production,” Ph.D. dissertation, Univ. Grenoble, Grenoble, France, 2009.
  7. R. Faranda and S. Leva, “Energetic sustainable development of railway stations,” in Proc. IEEE Power Eng. Soc. Gen. Meeting, Tampa, FL, USA, 2007 pp. 1–6.
  8. H. Hayashiya et al., “Necessity and possibility of smart grid technology application on railway power supply system,” in Proc. 14th Eur. Conf. Power Electron. Appl., Bermingham, U.K., 2011, pp. 1–10.
  9. W. Khamphanchai, M. Pipattanasomporn, and S. Rahman, “A multi-agent system for restoration of an electric power distribution network with local generation,” in Proc. IEEE Power Energy Soc. Gen. Meeting, 2012, pp. 1–8.
  10. W. Khamphanchai, M. Kuzlu, and M. Pipattanasomporn, “A smart distribution transformer management with multi agent technologies,” in Proc. IEEE PES Innov. Smart Grid Technol. Conf., 2013, pp. 1–6.
  11. D. E. Olivares, C. A. Canizares, and M. A. Kazerani, “Acentralized optimal energy management system for microgrids,” in Proc. IEEE Power Energy Soc. Gen. Meeting, Jul. 2011, pp. 1–6.
  12. H. Etemadi, E. J. Davison, and R. Iravani, “Adecentralized robust control strategy for multi-DER microgrids—Part I: Fundamental concepts,” IEEE Trans. Power Del., vol. 27, no. 4, pp. 1843–1853, Oct. 2012.
  13. L. Kulasekera et al., “A review on multi-agent systems in microgrid applications,” in Proc. IEEE PES Conf. Innov. Smart Grid Technol. India, Kerala, India, Dec. 1–3, 2011, pp. 173–177.
  14. S. Boudoudouh, M. Ouassaid, and M. Maaroufi, “Multi agent system ˆ in a distributed energy management of a multi sources system with a hybrid storage,” in Proc. 3rd Int. Renewable Sustain. Energy Conf., 2015, pp. 1–6.
  15. S. Boudoudouh and M. Maaroufi, “Real time battery state of charge estimation in smart grid application by multi agent system,” Int. J. Hydrogen Energy, vol. 42, pp. 19487–19495, 2017.
  16. S. Boudoudouh and M. Maaroufi, “Real time distributed systems modeling and control: Application to photovoltaic fuel cell electrolyser system,” J. Eng. Sci. Technol. Rev., vol. 10, no. 1, pp. 10–17, 2017.
  17. F. L. Bellifemine, G. Caire, and D. Greenwood, Developing Multi Agent Systems with JADE. New York, NY, USA: Wiley, 2007.