Abstract
Moving towards clean and sustainable transportation system, electrification of railway systems along with the use of electric vehicles (EVs) are of great interest. For economic operation of such systems, the peer-to-peer (P2P) energy trading policy became more applicable. Therefore, this paper proposes a double-layer individual-based optimization algorithm for P2P based optimal energy management (EM) of a smart distribution network incorporating flexible smart railway substation taking into consideration multiple energy sources of the traction system and the wayside distribution network with the integration of both EVs and energy hubs (EHs). For efficient operation of the railway substation, captured regenerative braking energy (RBE) are considered. In addition, photovoltaic (PV) units are used on station’s and platforms’ roof-tops for clean energy generation along with a multistory parking garage of electric vehicles (EVs). The wayside distribution network of district distribution area with flexible loads also contains several energy sources including distributed generation and multiple EHs. Optimal energy management is carried out including optimal demand side management of flexible loads and EHs. The optimization study takes into consideration several operational uncertainties arising from several components of the system. The simulation results show the feasibility of applying the proposed EM algorithm with an improvement of the energy economics of the system. The results show a reduction of 6.5 % in energy cost of the distribution network loads, 48 % in net energy cost of EHs, 70.8 % in net energy cost of EVs, and 59.1 % in the cost of energy bought by the traction substation.
-
Research ethics: Not applicable.
-
Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: The author states no conflict of interest.
-
Research funding: None declared.
-
Data availability:The raw data can be obtained on request from the corresponding author.
References
[1] E-LOBSTER – D1.8 Smart Management of Railway Networks. Electric losses balancing through integrated storage and power electronics towards increased synergy between railways and electricity distribution networks; 2020. https://www.e-lobster.eu/wp/wp-content/uploads/2021/03/E-LOBSTER-Smart-Management-of-Railway-Networks.pdf [Accessed 16 November 2022].Search in Google Scholar
[2] Csuzi, I, Csuzi, B. The urban electric bus, a sustainable solution to increase energy efficiency of public transport and reduce atmospheric pollution in the cities. In: Proc., Electric Vehicles International Conference (EV). Bucharest, Romania: IEEE; 2017:1–6 pp.10.1109/EV.2017.8242101Search in Google Scholar
[3] Cwil, M, Bartnik, W, Jarze bowski, S. Railway vehicle energy efficiency as a key factor in creating sustainable transportation systems. Energies 2021;14:5211. https://doi.org/10.3390/en14165211.Search in Google Scholar
[4] Alam, M, St-Hilaire, M, Kunz, T. An optimal P2P energy trading model for smart homes in the smart grid. Energy Effic 2017;5:1–19. https://doi.org/10.1007/s12053-017-9532-5.Search in Google Scholar
[5] Kang, J, Yu, R, Huang, X, Maharjan, S, Zhang, Y, Hossain, E. Enabling localized peer-to-peer electricity trading among plug-in hybrid electric vehicles using consortium blockchains. IEEE Trans Ind Inf 2017;13:3154–64. https://doi.org/10.1109/TII.2017.2709784.Search in Google Scholar
[6] Wang, N, Xu, W, Xu, Z, Shao, W. Peer-to-Peer energy trading among microgrids with multidimensional willingness. Energies 2018;11:3312. https://doi.org/10.3390/en11123312.Search in Google Scholar
[7] Zhang, C, Wu, J, Zhou, Y, Cheng, M, Long, C. Peer-to-Peer energy trading in a Microgrid. Appl Energy 2018;220:1–12. https://doi.org/10.1016/j.apenergy.2018.03.010.Search in Google Scholar
[8] Smart park: transforming travel. https://www.smart-park.co/ [Accessed 4 August 2023].Search in Google Scholar
[9] Çiçek, A, Şengör, İ, Güner, S, Karakuş, F, Erenoğlu, AK, Erdinç, O, et al.. Integrated rail system and EV parking lot operation with regenerative braking energy, energy storage system and PV availability. IEEE Trans Smart Grid 2022;13:3049–58. https://doi.org/10.1109/TSG.2022.3163343.Search in Google Scholar
[10] Fachrizal, R, Shepero, M, van der Meer, D, Munkhammar, J, Widén, J. Smart charging of electric vehicles considering photovoltaic power production and electricity consumption: a review. eTransportation 2020;4:1–17. https://doi.org/10.1016/j.etran.2020.100056.Search in Google Scholar
[11] Hussain, MT, Sulaiman, DNB, Hussain, MS, Jabir, M. Optimal management strategies to solve issues of grid having electric vehicles (EV): a review. J Energy Storage 2021;33:1–14. https://doi.org/10.1016/j.est.2020.102114.Search in Google Scholar
[12] Akbari, S, Fazel, SS, Jadid, S. Optimal coordinated operation of integrated energy hubs, considering regenerative braking utilization. IET Electr Syst Transp 2021;11:362–76. https://doi.org/10.1049/els2.12032.Search in Google Scholar
[13] Zakzouk, NE, Dyasty, AE, Ahmed, A, El Safty, SM. Power flow control of a standalone photovoltaic-fuel cell-battery hybrid system. In: Proc. Int. Conf. Renewable Energy Research and App. (ICRERA). Paris, France: IEEE; 2018:431–6 pp.10.1109/ICRERA.2018.8566869Search in Google Scholar
[14] Kumagai, K, Fujita, T, Nakahira, M, Mizuguchi, Y, Sonoda, H. Comparative evaluations of regenerative and electro-dynamic braking and power substations along graded section of a Japanese suburban rail line. In: Proc. IEEE Electric. Power Energy Conference (EPEC). Ottawa, ON, Canada: IEEE; 2016:2590–5 pp.10.1109/EPEC.2016.7771701Search in Google Scholar
[15] Liu, H, Zhou, MC, Guo, X, Zhang, Z, Ning, B, Tang, T. Timetable optimization for regenerative energy utilization in subway systems. IEEE Trans Intell Transport Syst 2019;20:3247–57. https://doi.org/10.1109/TITS.2018.2873145.Search in Google Scholar
[16] Yang, H, Shen, W, Yu, Q, Liu, J, Jiang, Y, Ackom, E, et al.. Coordinated demand response of rail transit load and energy storage system considering driving comfort. CSEE J Power Energy Syst 2020;6:749–59. https://doi.org/10.17775/CSEEJPES.2020.02590.Search in Google Scholar
[17] Novak, H, Vasak, M, Lesic, V. Hierarchical energy management of multi-Train railway transport system with energy storages. In: IEEE Int. Conf. Intell. Rail Transp. (ICIRT). Birmingham, UK: IEEE; 2016:130–8 pp.10.1109/ICIRT.2016.7588722Search in Google Scholar
[18] Réchard, G, Gouttefangeas, R. Recovering energy from train braking for traction and grid use. Energy Proc 2017;143:61–6. https://doi.org/10.1016/j.egypro.2017.12.648.Search in Google Scholar
[19] D’Achiardi, D, Annaswamy, AM, Mazumder, SK, Pilo, E. Transactive control of electric railways using dynamic market mechanisms. IEEE Trans Control Syst Technol 2022;30:1–13. https://doi.org/10.1109/TCST.2022.3202171.Search in Google Scholar
[20] Ying, Y, Liu, Q, Wu, M, Zhai, Y. The flexible smart traction power supply system and its hierarchical energy management strategy. IEEE Access 2021;9:64127–41. https://doi.org/10.1109/ACCESS.2021.3075768.Search in Google Scholar
[21] Pankovits, P, Pouget, J, Robyns, B, Delhaye, F, Brisset, S. Towards railway-smart grid: energy management optimization for hybrid railway power substations. In: IEEE PES Innov. Smart Grid Tech., Europe. Istanbul, Turkey: IEEE; 2014:1–6 pp.10.1109/ISGTEurope.2014.7028816Search in Google Scholar
[22] Liu, Y, Chen, M, Chen, Y, Chen, L. Energy management of connected Co-phase traction power system considering HESS and PV. In: 14th IEEE Conf. Ind. Electronics and App. (ICIEA). Xi’an, China; 2019:1408–12 pp.10.1109/ICIEA.2019.8834002Search in Google Scholar
[23] Aguado, JA, Racero, AJS, De La Torre, S. Optimal operation of electric railways with renewable energy and electric storage systems. IEEE Trans Smart Grid 2018;9:993–1001. https://doi.org/10.1109/TSG.2016.2574200.Search in Google Scholar
[24] Şengör, İ, Kılıçkıran, HC, Akdemir, H, Kekezo, B, Erdinç, O, Catalão, JPS. Energy management of a smart railway station considering regenerative braking and stochastic behaviour of ESS and PV generation. IEEE Trans Sustain Energy 2018;9:1041–50. https://doi.org/10.1109/TSTE.2017.2759105.Search in Google Scholar
[25] Calvillo, CF, Sánchez-Miralles, A, Villar, J, Martín, F. Impact of EV penetration in the interconnected urban environment of a smart city. Energy 2017;141:2218–33. https://doi.org/10.1016/j.energy.2017.12.006.Search in Google Scholar
[26] Maroufi, A, Mobtahej, M, Karimi, M, Baziar, A. A novel energy management model among interdependent sections in the smart grids. IET Gener Transm Distrib 2022:1–13. https://doi.org/10.1049/gtd2.12702.Search in Google Scholar
[27] Mobtahej, M, Esapour, K, Tajalli, SZ, Mohammadi, M. Effective demand response and GANs for optimal constraint unit commitment in solar‐tidal based microgrids. IET Renew Power Gener 2022;16:3485–95.10.1049/rpg2.12331Search in Google Scholar
[28] Javadi, MS, Gough, M, Nezhad, AE, Santos, SF, Shafie-khah, M, Catalão, JP. Pool trading model within a local energy community considering flexible loads, photovoltaic generation and energy storage systems. Sustain Cities Soc 2022;79:103747. https://doi.org/10.1016/j.scs.2022.103747.Search in Google Scholar
[29] El-Zonkoly, AM. Optimal energy management in smart grids including different types of aggregated flexible loads. J Energy Eng 2019;145:04019015. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000613.Search in Google Scholar
[30] Solar radiation in Alexandria. https://en.tutiempo.net/solar-radiation/alexandria.html [Accessed 21 July 2022].Search in Google Scholar
[31] El-Zonkoly, AM. Application of smart grid specifications to overcome excessive load shedding in Alexandria, Egypt. Elec Power Syst Res 2015;124:18–32. https://doi.org/10.1016/j.epsr.2015.02.019.Search in Google Scholar
[32] El-Zonkoly, AM. Feasibility of blockchain-based energy trading within islanded microgrids in Alexandria, Egypt. J Energy Eng 2021;147:04021009. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000754.Search in Google Scholar
© 2023 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Review
- California’s electric grid nexus with the environment
- Research Articles
- Adaptive centralized energy management algorithm for islanded bipolar DC microgrid
- Distributed new energy information acquisition model of distribution network based on Beidou communication
- A single phase modified Y-source inverter with high voltage gains and reduced switch stresses
- Technical assessment of power interface to utilize untapped power of decentralized solar pumps for positive impact in livelihoods
- An improved method for monitoring the junction temperature of 1200V / 50A IGBT modules used in power conversion systems
- Stochastic uncertainty management in electricity markets with high renewable energy penetration
- Power quality disturbances classification using autoencoder and radial basis function neural network
- Use of waste activated carbon and wood ash mixture as an electrical grounding enhancement material
- Double-layer optimal energy management of smart grid incorporating P2P energy trading with smart traction system
- Performance analysis of SRFT based D-STATCOM for power quality improvement in distribution system under different loading conditions
- Power quality improvement of utility-distribution system using reduced-switch DSTATCOM in grid-tied solar-PV system based on modified SRF strategy
Articles in the same Issue
- Frontmatter
- Review
- California’s electric grid nexus with the environment
- Research Articles
- Adaptive centralized energy management algorithm for islanded bipolar DC microgrid
- Distributed new energy information acquisition model of distribution network based on Beidou communication
- A single phase modified Y-source inverter with high voltage gains and reduced switch stresses
- Technical assessment of power interface to utilize untapped power of decentralized solar pumps for positive impact in livelihoods
- An improved method for monitoring the junction temperature of 1200V / 50A IGBT modules used in power conversion systems
- Stochastic uncertainty management in electricity markets with high renewable energy penetration
- Power quality disturbances classification using autoencoder and radial basis function neural network
- Use of waste activated carbon and wood ash mixture as an electrical grounding enhancement material
- Double-layer optimal energy management of smart grid incorporating P2P energy trading with smart traction system
- Performance analysis of SRFT based D-STATCOM for power quality improvement in distribution system under different loading conditions
- Power quality improvement of utility-distribution system using reduced-switch DSTATCOM in grid-tied solar-PV system based on modified SRF strategy