PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Optimization of railway microgrid operation under conditions of minimizing energy outflow to the grid

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The railway energy microgrid, in terms of both photovoltaic installation and energy storage, should be dimensioned so that there is no or minimal energy outflow. Only under this assumption - that there is no energy flow outside the microgrid - can the consumer freely define the microgrid without the risk of disagreement from the grid operator. The article presents an optimization analysis of microgrid operation to minimize the energy exported to the grid. The microgrid operation was analysed regarding the load generated by one of Poland's railway traction substations. The Particle Swarm Optimization method was used to optimize microgrid operation. Different photovoltaic panel orientations, values for the maximum energy export, and depth of discharge of energy storage were considered. The results show that it is possible to significantly reduce the value of energy export to the grid and use excess energy to charge the designed optimal battery energy storage. An analysis of the green energy used to power the traction substation was also carried out. The results indicate that it can represent a significant percentage of the energy used to power a traction substation.
Twórcy
Bibliografia
  • [1] E -LOBSTER Electric losses balancing through integrated storage and power electronics towards increased synergy between railways and electricity distribution networks, H2020-LCE-2016-2017, European Commission, Innovation and Networks Executive Agency, Grant agreement no. 731249, Deliverable D1.8, Smart Management of Railway Networks, 2020
  • [2] E. Pilo de la Fuente, S. K. Mazumder and I. G. Franco, “Railway Electrical Smart Grids: An introduction to next-generation railway power systems and their operation,” IEEE Electrification Magazine, vol. 2, no. 3, pp. 49-55, 2014. https://doi.org/10.1109/MELE.2014.2338411
  • [3] Z. Kljaic, D. Pavkovic, M. Cipek, M. Trstenjak, T. J. Mlinaric, M. Niksic, “An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency,” Safety, and Sustainability of Railway Transport, Future Internet, vol. 15, no. 11, pp. 347-391, 2023. https://doi.org/10.3390/fi15110347
  • [4] M. Brenna, F. Foiadelli and H. J. Kaleybar, “The Evolution of Railway Power Supply Systems Toward Smart Microgrids: The concept of the energy hub and integration of distributed energy resources,” IEEE Electrification Magazine, vol. 8, no. 1, pp. 12-23, 2020. https://doi.org/10.1109/MELE.2019.2962886
  • [5] H. Hayashiya, Y. Watanabe, Y. Fukasawa, T. Miyagawa, A. Egami, “Cost impacts of high efficiency power supply technologies in railway power supply - Traction and Station -,”, 2012 15th International Power Electronics and Motion Control Conference (EPE/PEMC), Novi Sad, Serbia, pp. LS3e.4-1-LS3e.4-6, 2012. https://doi.org/10.1109/EPEPEMC.2012.6397441
  • [6] H. Hayashiya, H. Yoshizumi, T. Suzuki, T. Furukawa, T. Kondoh, “Necessity and possibility of smart grid technology application on railway power supply system," Proceedings of the 2011 14th European Conference on Power Electronics and Applications, Birmingham, UK, pp. 1-10, 2011.
  • [7] F. Ma, X. Wang, L. Deng, Z. Zhu, Q. Xu and N. Xie, “Multiport Railway Power Conditioner and Its Management Control Strategy With Renewable Energy Access,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 8, no. 2, pp. 1405-1418, 2020. https://doi.org/10.1109/JESTPE.2019.2899138
  • [8] R. Nematirad, A. Pahwa, B. Natarajan, H. Wu, “Optimal sizing of photovoltaic-battery system for peak demand reduction using statistical models,” Frontiers in Energy Research, paper number 11:1297356, 2023. https://doi.org/10.3389/fenrg.2023.1297356
  • [9] C. O. Okoye, O. Solyali, “Optimal sizing of stand-alone photovoltaic systems in residential buildings,” Energy, vol. 126, pp. 573-584, 2017. https://doi.org/10.1016/j.energy.2017.03.032
  • [10] R. Belfkira, L. Zhang, G. Barakat, “Optimal sizing study of hybrid wind/PV/diesel power generation unit,” Solar Energy, vol. 85, no. 1, pp. 100-110, 2011. https://doi.org/10.1016/j.solener.2010.10.018
  • [11] S. Mandelli, C. Brivio, E. Colombo, M. Merlo, “A sizing methodology based on Levelized Cost of Supplied and Lost Energy for off-grid rural electrification systems,” Renewable Energy, vol. 89, pp. 475-488, 2016. https://doi.org/10.1016/j.renene.2015.12.032
  • [12] C. B. Salah, K. Lamamra, A. Fatnassi, “New optimally technical sizing procedure of domestic photovoltaic panel/battery system,” Journal of Renewable and Sustainable Energy, vol. 7, paper number 013134, 2015. https://doi.org/10.1063/1.4907923
  • [13] A. Mellit, “ANN-based GA for generating the sizing curve of stand-alone photovoltaic systems,” Advances in Engineering Software, vol. 41, no, 5, pp. 687-693, 2010. https://doi.org/10.1016/j.advengsoft.2009.12.008
  • [14] L. Zhou, Y. Zhang, X. Lin, C. Li, Z. Cai, and P. Yang, “Optimal sizing of PV and BESS for a smart household considering different price mechanisms,” IEEE Access, vol. 6, pp. 41 050-41 059, 2018.
  • [15] R. Khalilpour, A. Vassallo, “Planning and operation scheduling of pv-battery systems: A novel methodology,” Renewable and Sustainable Energy Reviews, vol. 53, pp. 194-208, 2016. https://doi.org/10.1016/j.rser.2015.08.015
  • [16] O. Erdinc, N. G. Paterakis, I. N. Pappi, A. G. Bakirtzis, and J. P.Catalao, “A new perspective for sizing of distributed generation and energy storage for smart households under demand response,” Applied Energy, vol. 143, pp. 26-37, 2015. https://doi.org/10.1016/j.apenergy.2015.01.025
  • [17] M. Alramlawi, P. Li, “Design Optimization of a Residential PV-Battery Microgrid With a Detailed Battery Lifetime Estimation Model,” IEEE Transactions on Industry Applications, vol. 56, no. 2, pp. 2020-2030, 2020. https://doi.org/10.1109/TIA.2020.2965894
  • [18] J. Li, “Optimal sizing of grid-connected photovoltaic battery systems for residential houses in Australia,” Renewable Energy, vol. 136, pp. 1245-1254, 2019. https://doi.org/10.1016/j.renene.2018.09.099
  • [19] R. Khezri, A. Mahmoudi and H. Aki, “Multi-Objective Optimization of Solar PV and Battery Storage System for A Grid-Connected Household,” 2020 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), pp. 1-6, Jaipur, India, 2020. https://doi.org/10.1109/PEDES49360.2020.9379481
  • [20] A. Gonçalves, G. O. Cavalcanti, M. A. F. Feitosa, R. F. D. Filho, A. C. Pereira, E. B. Jatoba, J. B. de Melo Filho, M. H. N. Marinho, A. Converti, L. A. Gómez-Malagon, “Optimal Sizing of a Photovoltaic/Battery Energy Storage System to Supply Electric Substation Auxiliary Systems under Contingency," Energies, vol. 16, no. 13, paper number 5165, 2023. https://doi.org/10.3390/en16135165
  • [21] M. Bortolini, M. Gamberi, A. Graziani, “Technical and economic design of photovoltaic and battery energy storage system,” Energy Conversion and Management, vol. 86, pp. 81-92, 2014. https://doi.org/10.1016/j.enconman.2014.04.089
  • [22] M. Aghamohamadi, A. Mahmoudi, M. H. Haque, “Two-Stage Robust Sizing and Operation Co-Optimization for Residential PV-Battery Systems Considering the Uncertainty of PV Generation and Load,” IEEE Transactions on Industrial Informatics, vol. 17, no. 2, pp. 1005-1017, 2021. https://doi.org/10.1109/TII.2020.2990682
  • [23] G. M. Masters, K. F. Hsu, “Renewable and Efficient Electric Power Systems,” 3rd Edition, John Wiley & Sons, Inc. - IEEE Press, USA, pp. 331-388, 2023
  • [24] R. Khezri, A. Mahmoudi, M. H. Haque, “Optimal Capacity of Solar PV and Battery Storage for Australian Grid-Connected Households,” IEEE Transactions on Industry Applications, vol. 56, no. 5, pp. 5319-5329, 2020. https://doi.org/10.1109/TIA.2020.2998668
  • [25] Y. del Valle, G. K. Venayagamoorthy, S. Mohagheghi, J. C. Hernandez and R. G. Harley, “Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems,” IEEE Transactions on Evolutionary Computation, vol. 12, no. 2, pp. 171-195, 2008. https://doi.org/10.1109/TEVC.2007.896686
  • [26] M. Combe, A. Mahmoudi, M.H. Haque, R. Khezri, “Optimal sizing of an AC-coupled hybrid power system considering incentive-based demand response,” IET Generation, Transmission & Distribution, vol. 13, no. 15, pp. 3354-3361, 2019. https://doi.org/10.1049/iet-gtd.2018.7055
  • [27] J. Kennedy, R. Eberhart, “Particle swarm optimization,” Proceedings of ICNN'95 - International Conference on Neural Networks, Perth, WA, Australia, Vol. 4, pp. 1942-1948, 1995. https://doi.org/10.1109/ICNN.1995.488968
  • [28] Y. Shi, R. Eberhart, “A modified particle swarm optimizer,” 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360), Anchorage, AK, USA, pp. 69-73, 1998. https://doi.org/10.1109/ICEC.1998.699146
  • [29] H. Hajian-Hoseinabadi, S. H. Hosseini, M. Hajian, “Optimal power flow solution by a modified particle swarm optimization algorithm,” 2008 43rd International Universities Power Engineering Conference, Padova, Italy, pp. 1-4, 2008. https://doi.org/10.1109/UPEC.2008.4651443
  • [30] PVGIS.COM Photovoltaic Geographical Information System, https://pvgis.com
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-866abd95-bf7b-4791-96c6-0030b71d6206
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.