Skip to main content

Advertisement

Log in

Optimal Operation of Electrified Railways with Renewable Sources and Storage

  • Original Article
  • Published:
Journal of Electrical Engineering & Technology Aims and scope Submit manuscript

Abstract

This paper proposes an approach for the optimal operation of electrified railways by balancing energy flows among energy exchange with the traditional electrical grid, energy consumption by accelerating trains, energy production from decelerating trains, energy from renewable energy resources (RERs) such as wind and solar photovoltaic (PV) energy systems, and energy storage systems. The objective function considered in this work is the minimization of total operating cost of electrified railway system consisting of cost of power generation from the external power system, cost of power obtained from RERs such as wind and solar PV sources, cost of power from storage systems such as battery storage and supercapacitors, and the income obtained by selling excess power back to the main electrical grid. This problem is formulated as an AC optimal power flow problem subjected to various equality and inequality constraints. In this work, the probability distribution functions (PDFs) are used to the uncertainties related to wind and solar PV powers. The proposed optimization problem is solved by using CONOPT solver of generalized algebraic modeling system (GAMS) software, which is a powerful and efficient optimization tool. The simulation results obtained with GAMS/CONOPT solver are also compared with meta-heuristic based differential evolution algorithm (DEA).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Khodaparastan M, Mohamed AA, Brandauer W (2019) Recuperation of regenerative braking energy in electric rail transit systems. IEEE Trans Intell Transp Syst 20(8):2831–2847

    Article  Google Scholar 

  2. Young B, Ertugrul N, Chew HG (2016) Overview of optimal energy management for nanogrids (end-users with renewables and storage). In: Australasian Universities power engineering conference, Brisbane, pp 1–6

  3. Huang X, Liao Q, Li Q, Tang S, Sun K (2020) Power management in co-phase traction power supply system with super capacitor energy storage for electrified railways. Railw Eng Sci 28:85–96

    Article  Google Scholar 

  4. Aguado JA, Racero AJS, de la Torre S (2018) Optimal operation of electric railways with renewable energy and electric storage systems. IEEE Trans Smart Grid 9(2):993–1001

    Article  Google Scholar 

  5. Moazzami M, Moradi J, Shahinzadeh H, Gharehpetian GB, Mogoei H (2018) Optimal economic operation of microgrids integrating wind farms and advanced rail energy storage system. Int J Renew Energy Res 8(2):1155–1164

    Google Scholar 

  6. Sumpavakup C, Ratniyomchai T, Kulworawanichpong T (2017) Optimal energy saving in DC railway system with on-board energy storage system by using peak demand cutting strategy. J Mod Transport 25:223–235

    Article  Google Scholar 

  7. Kumar H, Yadav SK, Sahay K, Kumar SS (2019) Investigation on recuperation of regenerative braking energy using ESS in (Urban) rail transit system. In: International conference on electrical, electronics and computer engineering (UPCON), Aligarh, India, pp 1–6

  8. Wu X, Hu X, Yin X, Moura SJ (2018) Stochastic optimal energy management of smart home with PEV energy storage. IEEE Trans Smart Grid 9(3):2065–2075

    Article  Google Scholar 

  9. Khan N, Dilshad S, Khalid R, Kalair AR, Abas N (2019) Review of energy storage and transportation of energy. Energy Storage 1(3):e49

    Article  Google Scholar 

  10. de Matos JG, Silva FSF, Ribeiro LAS (2015) Power control in AC isolated microgrids with renewable energy sources and energy storage systems. IEEE Trans Ind Electron 62(6):3490–3498

    Google Scholar 

  11. Ratniyomchai T, Hillmansen S, Tricoli P (2014) Recent developments and applications of energy storage devices in electrified railways. IET Electr Syst Transport 4(1):9–20

    Article  Google Scholar 

  12. Almehizia AA, Al-Masri HMK, Ehsani M (2019) Integration of renewable energy sources by load shifting and utilizing value storage. IEEE Trans Smart Grid 10(5):4974–4984

    Article  Google Scholar 

  13. Cui G, Luo L, Liang C, Hu S, Li Y, Cao Y, Xie B, Xu J, Zhang Z, Liu Y, Wang T (2019) Supercapacitor integrated railway static power conditioner for regenerative braking energy recycling and power quality improvement of high-speed railway system. IEEE Trans Transport Electrif 5(3):702–714

    Article  Google Scholar 

  14. Ovalle A, Pouget J, Bacha S, Gerbaud L, Vinot E, Sonier B (2018) Energy storage sizing methodology for mass-transit direct-current wayside support: application to French railway company case study. Appl Energy 230:1673–1684

    Article  Google Scholar 

  15. Kotel’nikov AV, Shevlyugin MV, Zhumatova AA (2017) Distributed generation of electric energy in traction power-supply systems of railways based on wind-power plants. Russ Electr Eng 88:586–591

    Article  Google Scholar 

  16. Bade SK, Kulkarni VA (2018) Analysis of railway traction power system using renewable energy: a review. In: International conference on computation of power, energy, information and communication, Chennai, pp 404–408

  17. Park S, Salkuti SR (2019) Optimal energy management of railroad electrical systems with renewable energy and energy storage systems. Sustainability 11:6293

    Article  Google Scholar 

  18. Dragičević T, Pandžić H, Škrlec D, Kuzle I, Guerrero JM, Kirschen DS (2014) Capacity optimization of renewable energy sources and battery storage in an autonomous telecommunication facility. IEEE Trans Sustain Energy 5(4):1367–1378

    Article  Google Scholar 

  19. de la Torre S, Racero AJS, Aguado JA, Reyes M, Martínez O (2015) Optimal sizing of energy storage for regenerative braking in electric railway systems. IEEE Trans Power Syst 30(3):1492–1500

    Article  Google Scholar 

  20. Ata M, Erenoğlu AK, Şengör İ, Erdinç O, Taşcıkaraoğlu A, Catalão JPS (2019) Optimal operation of a multi-energy system considering renewable energy sources stochasticity and impacts of electric vehicles. Energy 186:115841

    Article  Google Scholar 

  21. Das B (2014) Uncertainty modelling of wind turbine generating system in power flow analysis of radial distribution network. Electr Power Syst Res 111:141–147

    Article  Google Scholar 

  22. Vinod RK, Singh SK (2018) Solar photovoltaic modeling and simulation: as a renewable energy solution. Energy Rep 4:701–712

    Article  Google Scholar 

  23. Technologies and potential developments for energy efficiency and CO2 reductions in rail systems. Technical Report. https://uic.org/IMG/pdf/_27_technologies_and_potential_developments_for_energy_efficiency_and_co2_reductions_in_rail_systems._uic_in_colaboration.pdf

  24. Javaid N, Hafeez G, Iqbal S, Alrajeh N, Alabed MS, Guizani M (2018) Energy efficient integration of renewable energy sources in the smart grid for demand side management. IEEE Access 6:77077–77096

    Article  Google Scholar 

  25. Ćalasan MP, Nikitović L, Mujović S (2019) CONOPT solver embedded in GAMS for optimal power flow. J Renew Sustain Energy 11(4):046301

    Article  Google Scholar 

  26. Raja SC, Banu SAW, Venkatesh P (2012) Congestion Management using GAMS/CONOPT solver. In: IEEE-international conference on advances in engineering, science and management, Nagapattinam, pp 72–78

  27. Tian H, Shuai M, Li K (2019) Optimization study of line planning for high speed railway based on an improved multi-objective differential evolution algorithm. IEEE Access 7:137731–137743

    Article  Google Scholar 

  28. Birogul S (2019) Hybrid Harris hawk optimization based on differential evolution (HHODE) algorithm for optimal power flow problem. IEEE Access 7:184468–184488

    Article  Google Scholar 

  29. Novak H, Vašak M, Gulin M, Leši´c V (2015) Railway transport system energy flow optimization with integrated microgrid. In: 12th international conference on modern electrified transport, Trogir, Croatia, pp 1–6

  30. Novak H, Vašak M, Leši´c V (2016) Hierarchical energy management of multi-train railway transport system with energy storages. In: IEEE international conference on intelligent rail transportation, Birmingham, pp 130–138

Download references

Acknowledgements

This research work has been carried out based on the support of “Woosong University's Academic Research Funding—(2019–2020)”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Surender Reddy Salkuti.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Salkuti, S.R. Optimal Operation of Electrified Railways with Renewable Sources and Storage. J. Electr. Eng. Technol. 16, 239–248 (2021). https://doi.org/10.1007/s42835-020-00608-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42835-020-00608-1

Keywords

Navigation