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Tytuł artykułu

Optimal configuration of energy storage system capacity in traction power supply system considering photovoltaic consumption

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In order to achieve energy savings and promote on-site integration of photovoltaic energy in electrified railways, a topology structure is proposed for the integration of photovoltaic (PV) and the energy storage system (ESS) into the traction power supply system (TPSS) based on a railway power conditioner (RPC). This paper analyzes the composition and operation principles of this structure. To assess the economic benefits brought by the integration of photovoltaic and energy storage systems, a bilevel optimization model is established, with the objectives of optimizing energy storage capacity configuration and photovoltaic energy integration. The KKT (Karush–Kuhn–Tucker) method is employed to transform the model into a single-layer mixed-integer linear programming model, which is then solved using the CPLEX solver in MATLAB. The research findings indicate that, with the configuration of the ESS, the optimal PV consumption rate achieved is 96.8749%. Compared to a 100% PV consumption rate, the ESS capacity configuration is reduced by 13.14%, and the overall operational cost of the TPSS is at its lowest. The study suggests that the proposed bilevel optimization algorithm can more effectively consider PV consumption, leading to enhanced economic performance of the TPSS operation.
Rocznik
Strony
219--233
Opis fizyczny
Bibliogr. 22 poz., rys., tab., wykr., wz.
Twórcy
autor
  • School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou,730070 China
  • School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou,730070 China
autor
  • School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou,730070 China
Bibliografia
  • [1] https://www.mot.gov.cn/fenxigongbao/hangyegongbao/202305/P020230530535262349964.pdf, accessed August 2023.
  • [2] Haghighatseresht A., MansouriBidekani R., Razavi S. et al., Investigating the impact of building local photovoltaic power plants on the national grid, an artificial intelligence approach, Ain Shams Engineering Journal, vol. 14, no. 11, 102518 (2023), DOI: 10.1016/j.asej.2023.102518.
  • [3] Mirjalili M.A., Aslani A., Zahedi R. et al., A comparative study of machine learning and deep learning methods for energy balance prediction in a hybrid building-renewable energy system, Sustainable Energy Research, vol. 10, no. 8 (2023), DOI: 10.1186/s40807-023-00078-9.
  • [4] Pourrahmani H., Zahedi R., Daneshgar S. et al., Lab-scale investigation of the integrated backup/storage system for wind turbines using alkaline electrolyzer, Energies, vol. 16, no. 9, 3761 (2023), DOI: 10.3390/en16093761.
  • [5] Khah M.V., Zahedi R., Eskandarpanah R. et al., Optimal sizing of residential photovoltaic and battery system connected to the power grid based on the cost of energy and peak load, Heliyon, vol. 9, no. 3, e14414 (2023), DOI: 10.1016/j.heliyon.2023.e14414.
  • [6] Deng W., Dai C., Chen W., Application of PV Generation in AC/DC Traction Power Supply System and the Key Problem Analysis under the Background of Rail Transit Energy Internet, Proceedings of the Chinese Society of Electrical Engineering, vol. 39, no. 19, pp. 5692–5702(2019), DOI: 10.13334/j.0258- 8013.pcsee.181848.
  • [7] Chen W., Wang X., Li Q., Han Y., Wang W., Review on the Development Status of PV Power Station Accessing to Traction Power Supply System for Rail Transit, Power System Technology, vol. 43, no. 10, pp. 3663–3670 (2019), DOI: 10.13335/j.1000-3673.pst.2018.2498.
  • [8] Méndez-Hernández Y., Müggenburg E., Lynass M. et al., Design aspects for high voltage MW PV systems for railway power supply, Proceedings of the 29th European Photovoltaic Solar Energy Conference and Exhibition, Amsterdam (2014), https://www.researchgate.net/profile/YaruHernandez/publication/270876054_Design_Aspects_for_High_Voltage_MW_PV_Systems_for_Rail way_Power_Supply/links/56b2102908aed7ba3fedb391/Design-Aspects-for-High-Voltage-MW-PVSystems-for-Railway-Power-Supply.pdf.
  • [9] Hayashiya H. et al., Potentials, peculiarities and prospects of solar power generation on the railway premises, 2012 International Conference on Renewable Energy Research and Applications (ICRERA), Nagasaki, Japan, pp. 1–6 (2012), DOI: 10.1109/ICRERA.2012.6477458.
  • [10] D’Arco S., Piegari L., Tricoli P., Comparative Analysis of Topologies to Integrate Photovoltaic Sources in the Feeder Stations of AC Railways, IEEE Transactions on Transportation Electrification, vol. 4, no. 4, pp. 951–960 (2018), DOI: 10.1109/TTE.2018.2867279.
  • [11] Wu C.-P., Luo A., Xu X.-Y., Ma F.-J., Sun J., Integrative compensation method of negative phase sequence and harmonic for high-speed railway traction supply system with V/v transformer, Proceedings of the Chinese Society of Electrical Engineering, vol. 30, no. 16, pp. 111–117 (2010), DOI: 10.13334/j.0258- 8013.pcsee.2010.16.014.
  • [12] Roudsari H.M., Jalilian A., Jamali S., Flexible Fractional Compensating Mode for Railway Static Power Conditioner in a V/v Traction Power Supply System, IEEE Transactions on Industrial Electronics, vol. 65, no. 10, pp. 7963–7974 (2018), DOI: 10.1109/TIE.2018.2801779.
  • [13] Zhao X., Xie Z., Wang Y., Chen X., Xin Y., Mu X., Low-frequency Stability Analysis of Photovoltaic Connected Traction Power Supply System Based on Extended Forbidden Region-based Criterion, High Voltage Engineering, vol. 49, no. 5, pp. 1997–2007 (2023), DOI: 10.13336/j.1003-6520.hve.20220690.
  • [14] Wang Y., He Y., Chen X., Zhao M., Xie J., A layered compensation optimization strategy of energy storage type railway power conditioner, Archives of Electrical Engineering, vol. 71, no. 1, pp. 5–20 (2022), DOI: 10.24425/aee.2022.140194.
  • [15] Wang Ying, Yang H., Chen X. et al., Train based on virtual synchronous generator technology uninterrupted phase-separation passing study, Archives of Electrical Engineering, vol. 72, no. 3, pp. 755–768 (2023), DOI: 10.24425/aee.2023.146048.
  • [16] Deng W., Dai C., Chen W., Zhang H., Research Progress of Railway Power Conditioner, Proceedings of the Chinese Society of Electrical Engineering, vol. 40, no. 14, pp. 4640–4655 (2020), DOI: 10.13334/j.0258-8013.pcsee.191470.
  • [17] Chengpeng X., Ying H., Qi L. et al., Research on coordinated control method of PV and battery access traction power supply system based on RPC, 2020 IEEE Sustainable Power and Energy Conference (iSPEC), pp. 173–179 (2020), DOI: 10.1109/iSPEC50848.2020.9350956.
  • [18] Yuan J., Qu K., Zheng X., Min Y., Optimizing Research on Hybrid Energy Storage System of High Speed Railway, Transactions of China Electrotechnical Society, vol. 36, no. 19, pp. 4161–4169+4182 (2021), DOI: 10.19595/j.cnki.1000-6753.tces.201060.
  • [19] Zhang Y., Hu H., Geng A., Chen J., Ge Y., Wang K., Capacity optimization configuration of hybrid energy storage system for electrified railway considering peak load shifting, Electric Power Automation Equipment, vol. 43, no. 2, pp. 44–50 (2023), DOI: 10.16081/j.epae.202207012.
  • [20] Li X., Lu J., Xiao L., Jin Z., Capacity Optimization Configuration of Hybrid Energy Storage System for Long Steep Slope of High-Speed Railway, Transactions of China Electrotechnical Society, pp. 1–16 (2023), DOI: 10.19595/j.cnki.1000-6753.tces.221199.
  • [21] Chen M., Liang Z., Cheng Z., Zhao J., Tian Z., Optimal Scheduling of FTPSS with PV and HESS Considering the Online Degradation of Battery Capacity, IEEE Transactions on Transportation Electrification, vol. 8, no. 1, pp. 936–947 (2022), DOI: 10.1109/TTE.2021.3093321.
  • [22] Sinha A., Soun T., Deb K., Using Karush–Kuhn–Tucker proximity measure for solving bilevel optimization problems, Swarm and Evolutionary Computation, vol. 44, pp. 496–510 (2019), DOI: 10.1016/j.swevo.2018.06.004.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0e47c786-2148-4a1a-bd88-debdde252624
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