Improvement of the Energy Efficiency of Subway Traction Systems Through the Use of Genetic Algorithm in Traffic Control
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This paper proposes a subway energy regeneration model, based on control stops and train departures throughout his trip, with the use of energy from the regenerative braking in the drive system. The goal is to optimize the power consumption and improve efficiency, in view of sustainable management. Applying genetic algorithm to get the better of the trains’ traffic configuration, the research develops and tests the Traction Control Algorithm for Subway Energy Regeneration (ACTREM), using the Scilab program. To analyze the performance of ACTREM control algorithm in enhancing energy efficiency, there were fifteen simulations of applying ACTREM on line 4—Yellow subway in São Paulo. These simulations showed the ACTREM efficiency to generate automatically diagram schedules optimized for energy savings in metro systems, considering the system’s operational constraints such as maximum each train capacity, total wait time, total travel time and interval between trains. The results show that the proposed algorithm can save 9.5% of the energy and does not cause significant impacts on the transportation system capacity passengers and also suggest possible continuity studies.
KeywordsSubway Power (energy) efficiency Numerical optimization Rectifier substation Power regeneration
- APTA. (2015). Public transportation saves energy and helps our environment. http://www.apta.com/gap/policyresearch/Documents/facts_environment_09.pdf. Accessed 15 October 2017.
- Bozorg-Haddad, O., Solgi, M., & Loáiciga, H. A. (2017). Genetic algorithms in search, optimization, and machine learning (1st ed.). Hoboken: Wiley.Google Scholar
- EPE. (2013). Resenha mensal do mercado de energia elétrica, s.l.: s.n.Google Scholar
- Metrô-SP. (2011). Companhia do Metropolitano de São Paulo—Metrô. http://www.metro.sp.gov.br/relatoriodesustentabilidade-2011/cap-06/contribuicao-metro.aspx#energia-eletrica. Accessed 20 July 2015.
- Nasri, A., Fekri Moghadam, M., & Mokhtari, H. (2010). Timetable optimization for maximum usage of regenerative energy of braking in electrical railway systems. In International symposium on power electronics, electrical drives, automation and motion—SPEEDAM 2010, Pisa, Italy.Google Scholar
- Peña-Alcaraz, M., Fernandez, A., Cucala, A. P., & Ramos, A. (2011). Optimal underground timetable design based on power flow for maximizing the use of regenerative-braking energy. In Proceedings of the institution of mechanical engineers, Part F: Journal of Rail and Rapid Transit, pp. 397–408.Google Scholar
- Rojas, G., Gregorio-Hetem, J., & Hetem Jr., A. (2008). Towards the main sequence: detailed analysis of weak line and post-T Tauri stars. Monthly Notices of the Royal Astronomical Society, pp. 1335–1343.Google Scholar
- Rosberg, I., Goldbarg, E., & Goldbarg, M. (2011). Solving the light up with ant colony optimization. In 2011 IEEE congress of evolutionary computation (CEC), 8 June, pp. 566–573.Google Scholar
- Sousa, C. A. D., & Pereira, S. L. (2015). Comparative study of existing methods for improving the energy efficiency of the system traction of subway. In 2015 IEEE 13th Brazilian power electronics conference and 1st southern power electronics conference (COBEP/SPEC), 2 December, pp. 1–5.Google Scholar
- Ticket to Kyoto. (2014). T2K WP2B energy recovery. http://www.tickettokyoto.eu/sites/default/files/downloads/T2K_WP2B_Energy%20Recovery_Final%20Report_2.pdf. Accessed 15 October 2015.
- UNITED NATIONS. (2015). World urbanization prospects—The 2014 Revision, New York: s.n.Google Scholar