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Energy management strategy considering energy storage system degradation for hydrogen fuel cell ship

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A hybrid energy system (HES) including hydrogen fuel cell systems (FCS) and a lithium-ion (Li-ion) battery energy storage system (ESS) is established for hydrogen fuel cell ships to follow fast load transients. An energy management strategy (EMS) with hierarchical control is presented to achieve proper distribution of load power and enhance system stability. In the high-control loop, a power distribution mechanism based on a particle swarm optimization algorithm (PSO) with an equivalent consumption minimization strategy (ECMS) is proposed. In the low-level control loop, an adaptive fuzzy PID controller is developed, which can quickly restore the system to a stable state by adjusting the PID parameters in real time. Compared with the rule-based EMS, hydrogen consumption is reduced by 5.319%, and the stability of the power system is significantly improved. In addition, the ESS degradation model is developed to assess its state of health (SOH). The ESS capacity loss is reduced by 2% and the daily operating cost of the ship is reduced by 1.7% compared with the PSO-ECMS without considering the ESS degradation.
Rocznik
Tom
Strony
95--104
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Shanghai Maritime University, Logistics Engineering College, China
autor
  • Shanghai Maritime University, Logistics Engineering College, China
autor
  • Shanghai Maritime University, Logistics Engineering College, China
  • Gdynia Maritime University, Poland
Bibliografia
  • 1. Z. Korczewski, “Test method for determining the chemical emissions of a marine diesel engine exhaust in operation,” Polish Maritime Research, 2021. doi:10.2478/ pomr-2021-0035.
  • 2. M. Barakat, B. Tala-Ighil, H. Chaoui, H. Gualous, D. Hissel, “Energy Management of a Hybrid Tidal Turbine-Hydrogen Micro-Grid: Losses Minimization Strategy,” Fuel Cells, 2020. doi:10.1002/fuce.201900082.
  • 3. P. Geng, X. Y. Xu, T. Tarasiuk, “State of charge estimation method for lithium-ion batteries in all-electric ships based on LSTM neural network,” Polish Maritime Research, 2020. doi:10.2478/pomr-2020-0051.
  • 4. R. Zhao et al., “A numerical and experimental study of marine hydrogen-natural gas-diesel trifuel engines,” Polish Maritime Research, 2020. doi:10.2478/pomr-2020-0068.
  • 5. M. Rafiei, J. Boudjadar, M. H. Khooban, “Energy Management of a Zero-Emission Ferry Boat With a Fuel-Cell-Based Hybrid Energy System: Feasibility Assessment,” IEEE Trans. Ind. Electron., 2021. doi:10.1109/ tie.2020.2992005.
  • 6. S. Faddel, A. A. Saad, M. E. Hariri, O. A. Mohammed, “Coordination of Hybrid Energy Storage for Ship Power Systems With Pulsed Loads,” IEEE Trans. Ind. Appl., 2020. doi:10.1109/tia.2019.2958293.
  • 7. S. Hasanvand, M. Rafiei, M. Gheisarnejad, M. H. Khooban, “Reliable Power Scheduling of an Emission-Free Ship: Multiobjective Deep Reinforcement Learning,” IEEE Trans. Transport. Electrif., 2020. doi:10.1109/tte.2020.2983247.
  • 8. P. Wu, J. Partridge, R. Bucknall, “Cost-effective reinforcement learning energy management for plug-in hybrid fuel cell and battery ships,” Applied Energy, 2020. doi:10.1016/j.apenergy.2020.115258.
  • 9. M. Banaei, J. Boudjadar, M. H. Khooban, “Stochastic Model Predictive Energy Management in Hybrid Emission-Free Modern Maritime Vessels,” IEEE Trans. Ind. Inform., 2021. doi:10.1109/tii.2020.3027808.
  • 10. J. Hou, Z. Y. Song, H. Hofmann, J. Sun, “Adaptive model predictive control for hybrid energy storage energy management in all-electric ship microgrids,” Energy Conversion and Management, 2019. doi:10.1016/j. enconman.2019.111929.
  • 11. M. Banaei, M. Rafiei, J. Boudjadar, M. H. Khooban, “A Comparative Analysis of Optimal Operation Scenarios in Hybrid Emission-Free Ferry Ships,” IEEE Trans. Transport. Electrif., 2020. doi:10.1109/tte.2020.2970674.
  • 12. J. Nunez Forestieri, M. Farasat, “Energy flow control and sizing of a hybrid battery/supercapacitor storage in MVDC shipboard power systems,” IET Electrical Systems in Transportation, 2020. doi:10.1049/iet-est.2019.0161.
  • 13. M. H. Khooban, M. Gheisarnejad, H. Farsizadeh, A. Masoudian, J. Boudjadar, “A New Intelligent Hybrid Control Approach for DC-DC Converters in ZeroEmission Ferry Ships,” IEEE Trans. Power. Electron., 2020. doi:10.1109/tpel.2019.2951183.
  • 14. T. H. Wang et al., “A Power Allocation Method for Multistack PEMFC System Considering Fuel Cell Performance Consistency,” IEEE Trans. Ind. Appl., 2020. doi:10.1109/tia.2020.3001254.
  • 15. J. Chen, C. Xu, C. Wu, W. Xu, “Adaptive Fuzzy Logic Control of Fuel-Cell-Battery Hybrid Systems for Electric Vehicles,” IEEE Trans. Ind. Inform., 2018. doi:10.1109/ tii.2016.2618886.
  • 16. F. Balsamo, P. De Falco, F. Mottola, M. Pagano, “Power Flow Approach for Modeling Shipboard Power System in Presence of Energy Storage and Energy Management Systems,” IEEE Trans. Energy Convers., 2020. doi:10.1109/ tec.2020.2997307.
  • 17. H. Ahmadi, M. Rafiei, M. A. Igder, M. Gheisarnejad, M. H. Khooban, “An Energy Efficient Solution for Fuel Cell Heat Recovery in Zero-Emission Ferry Boats: Deep Deterministic Policy Gradient,” IEEE Trans. Veh. Technol., 2021. doi:10.1109/tvt.2021.3094899.
  • 18. [18] A. Boveri, F. Silvestro, M. Molinas, E. Skjong. Optimal Sizing of Energy Storage Systems for Shipboard Applications. IEEE Trans. Energy Convers. 2019. doi:10.1109/ TEC.2018.2882147.
  • 19. Y. Z. Zhang et al., “Real-Time Energy Management Strategy for Fuel Cell Range Extender Vehicles Based on Nonlinear Control,” IEEE Trans. Transport. Electrif., 2019. doi:10.1109/ tte.2019.2958038.
  • 20. C. Lin, H. Mu, R. Xiong, W. X. Shen, “A novel multi-model probability battery state of charge estimation approach for electric vehicles using H-infinity algorithm,” Applied Energy, 2016. doi:10.1016/j.apenergy.2016.01.010.
  • 21. X. Y. Lu, H. Y. Wang, “Optimal Sizing and Energy Management for Cost-Effective PEV Hybrid Energy Storage Systems,” IEEE Trans. Ind. Inform., 2020. doi:10.1109/ tii.2019.2957297.
  • 22. J. Park et al., “Semi-empirical long-term cycle life model coupled with an electrolyte depletion function for largeformat graphite/LiFePO4 lithium-ion batteries,” Journal of Power Sources, 2017. doi:10.1016/j.jpowsour.2017.08.094.
  • 23. J. Wang et al., “Cycle-life model for graphite-LiFePO4 cells,” Journal of Power Sources, 2011. doi:10.1016/j. jpowsour.2010.11.134.
  • 24. M. Kalikatzarakis, R. D. Geertsma, E. J. Boonen, K. Visser, R. R. Negenborn, “Ship energy management for hybrid propulsion and power supply with shore charging,” Control Engineering Practice, 2018. doi:10.1016/j. conengprac.2018.04.009.
  • 25. H. Chen, Z. H. Zhang, C. Guan, H. B. Gao, “Optimization of sizing and frequency control in battery/supercapacitor hybrid energy storage system for fuel cell ship,” Energy, 2020. doi:10.1016/j.energy.2020.117285.
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-b3a0b749-c81c-4152-88ff-4d34abeb46c9
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