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Tytuł artykułu

Energy management in a proton exchange membrane fuel cell based DC microgrid using feedback linearization control and GWO

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Warianty tytułu
PL
Zarządzanie energią w paliwie z membraną do wymiany protonów Mikrosieć prądu stałego oparta na komórkach wykorzystująca kontrolę linearyzacji ze sprzężeniem zwrotnym i GWOP
Języki publikacji
EN
Abstrakty
EN
This paper proposes a new energy management approch based on th integration of Grey Wolf Optimization (GWO) with Feedback Linearization Control (FLC) for a DC microgrid. The studied hybrid power system uses multiple power sources based on a Proton Exchange Membrane Fuel cell (PEMFC), and supercapacitor (SC). The proposed energy management strategy optimizes the ration use of the sources in order to minimize fuel consumption and maximize the renewable energy sources part. The strategy also takes account on the intrinsic specificities of PEMFC and SC, such as their response time and efficiency, to ensure smooth and stable operation of the system. The fuel consumption, dynamic performance, and service life of power sources can be significantly impacted by the energy management strategy used to accommodate fluctuations in power demand. The proposed strategy performances is verified through extensive simulation results.
PL
W artykule zaproponowano nowe podejście do zarządzania energią oparte na integracji optymalizacji Gray Wolfa (GWO) z kontrolą linearyzacji ze sprzężeniem zwrotnym (FLC) dla mikrosieci prądu stałego. Badany hybrydowy system zasilania wykorzystuje wiele źródeł zasilania opartych na ogniwie paliwowym z membraną do wymiany protonów (PEMFC) i superkondensatorze (SC). Zaproponowana strategia zarządzania energią optymalizuje racjonalne wykorzystanie źródeł w celu minimalizacji zużycia paliw i maksymalizacji udziału energii odnawialnej. Strategia uwzględnia także wewnętrzną specyfikę PEMFC i SC, taką jak czas reakcji i wydajność, aby zapewnić płynne i stabilne działanie systemu. Strategia zarządzania energią stosowana w celu uwzględnienia wahań zapotrzebowania na moc może znacząco wpływać na zużycie paliwa, wydajność dynamiczną i żywotność źródeł zasilania. Efektywność zaproponowanej strategii jest weryfikowana poprzez obszerne wyniki symulacji.
Rocznik
Strony
20--26
Opis fizyczny
Bibliogr. 28 poz., rys., tab.
Twórcy
  • Department of Chemistry, Faculty of science University of M'Sila, Algeria; PO Box 166 Icheblilia, 28000 M'sila, Algeria
  • Sport department,Institute of scence and Tehnology of physique and sports activities University of M'Sila, Algeria; PO Box 166 Icheblilia, 28000 M'sila, Algeria
Bibliografia
  • [1] X. Hao; I. Salhi;S. Laghrouche;Y. Ait-Amirat;A. Djerdir, “Backstepping Supertwisting Control of Four-Phase Interleaved Boost Converter for PEM Fuel Cell” IEEE Transactions on Power Electronics, vol. 37, issue 7, 2022
  • [2] D. Göhlich, T. A. Fay, D. Jefferies, E. Lauth, A. Kunith, and X. Zhang, “Adaptive Parameter Identification of a Fuel Cell System for Health-Conscious Energy Management Applications” IEEE Transactions on Intelligent Transportation Systems., vol. 23, issue 7, 2022.
  • [3] H. Mehnatkesh;A. Alasty;M. Boroushaki;M. H. Khodsiani;M. R. Hasheminasab; M. J. Kermani, Estimation of Water Coverage Ratio in Low Temperature PEM-Fuel Cell Using Deep Neural Network, IEEE Sensors Journal. Vol 20, issue 18, 2022.
  • [4] A. Djerioui et al., “Energy management strategy of Supercapacitor/Fuel Cell energy storage devices for vehicle applications,” Int. J. Hydrogen Energy, vol. 44, no. 41, pp. 23416– 23428, 2019.
  • [5] K. Bos, J. Gupta, Climate change: the risks of stranded fossil fuel assets and resources to the developing world, Third World Q. 39, pp 436–453, 2018.
  • [6] B. Bendjedia, H. Alloui, N. Rizoug, M. Boukhnifer, F. Bouchafaa, and M. E. Benbouzid, “Sizing and Energy Management Strategy for hybrid FC/Battery electric vehicle,” IECON Proc. (Industrial Electron. Conf., pp. 2111–2116, 2016.
  • [7] Z. Ma, A. Bouscayrol, W. Lhomme, and S. Cui, “Optimal sizing of the EVT for a hybrid urban delivery truck,” IFAC-Papers On Line, vol. 52, no. 5, pp. 504–509, 2019.
  • [8] L. Pérez-Lombard, J. Ortiz, C. Pout, A review on buildings energy consumption information, Energy Build. Vol. 40, pp. 394–398,2008.
  • [9] Souleman Njoya Motapon ; Louis-A. Dessaint ; Kamal Al-Haddad “A Comparative Study of Energy Management Schemes for a Fuel-Cell Hybrid Emergency Power System of More-Electric Aircraft” IEEE Transactions on Industrial Electronics, Volume: 61 , Pages 1320 – 1334, March 2014
  • [10] Y.Hames, K. Kaya, E. B. ArzuTurksoy “Analysis of the control strategies for fuel saving in the hydrogen fuel cell vehicles” International Journal of Hydrogen Energy Volume 43, Issue 23,Pages 10810-10821, 7 June 2018
  • [11] N. Chettibi ; A. Mellit ; G. Sulligoi ; A. M. Pavan “ Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid” IEEE Transactions on Smart Grid, Volume: 9 , Issue: 3 , Pages 1667 – 1679, May 2018
  • [12] P. Garcia, L. M. Fernandez, C.A. Garcia, and F. Jurado, “Recent Approach of Forensic-Based Investigation Algorithm for Optimizing Fractional Order PID-Based MPPT With Proton Exchange Membrane Fuel Cell ” IEEE Access, Volume: 9, pp. : 18974 - 18992 , DECEMBER 2010, Jan. 2021
  • [13] C. Yan; J. Chen;H. Liu;L. Kumar; and H. Lu” Health Management for PEM Fuel Cells Based on an Active Fault Tolerant Control Strategy” IEEE Transactions on Sustainable Energy Volume 12,issue 2, 2021
  • [14] A. Amamou;M. Kandidayeni;S. Kelouwani;L. Boulon” An Online Self Cold Startup Methodology for PEM Fuel Cells in Vehicular Applications” IEEE Transactions on Vehicular Technology, Vol 69,issue 12, 2020.
  • [15] S. Mirjalili, S. Mohammad, and A. Lewis, “Advances in Engineering Software Grey Wolf Optimizer,” Advances in Engineering Software, vol. 69, pp. 46–61, 2014.
  • [16] A. Djerioui, A. Houari, M. Ait-Ahmed, M.F Benkhoris, A. Chouder and M. Machmoum " Grey Wolf based control for speed ripple reduction at low speed operation of PMSM drives" ISA Trans., vol. PP, pp. 1–8, 2018.
  • [17] A Djerioui, A Houari, M. Machmoum, Malek Ghanes“Grey Wolf Optimizer-Based Predictive Torque Control for Electric Buses Applications,” Energies, vol. 13, 2020
  • [18] R.E.Precup, R.-C.David and E.M. Petriu, " Grey wolf optimizer algorithm-based tuning of fuzzy control systems with reduced parametric sensitivity. IEEE Transactions on Industrial Electronics 64, 1,. 527–534. 2017
  • [19] Seydali Ferahtia, A Djerioui, Tedjani Mesbahi and etc, “Optimal Adaptive Gain LQR-Based Energy Management Strategy for Battery-Supercapacitor Hybrid Power System,” Energies, vol. 16, 2021.
  • [20] S. Sharma, S. Bhattacharjee, and A. Bhattacharya, “Grey wolf optimisation for optimal sizing of battery energy storage device to minimise operation cost of microgrid,” IET Gener. Transm. Distrib., vol. 10, no. 3, pp. 625–637, 2016.
  • [21] M. Pradhan, P. K. Roy, and T. Pal, “Grey wolf optimization applied to economic load dispatch problems,” Int. J. Electr. Power Energy Syst., vol. 83, pp. 325–334, Dec. 2016.
  • [22] N. Jayakumar, S. Subramanian, S. Ganesan, and E. B. Elanchezhian, “Grey wolf optimization for combined heat and power dispatch with cogeneration systems,” Int. J. Electr. Power Energy Syst., vol. 74, pp. 252–264, Jan. 2016.
  • [23] K Shojaei, M. Abdolmaleki “Output feedback control of a tractor with N-trailer with a guaranteed performance”. Mech Syst Signal Process ; pp. 142: 106746, 2020.
  • [24] SJ. Yoo, BS. Park. Quantized feedback control strategy for tracking performance guarantee of nonholonomic mobile robots with uncertain nonlinear dynamics. Appl Mathematics Comput, pp. 407: 126349, 2021
  • [25] K. Shojaei and H. Taghavifar “Input-output feedback linearization control of a tractor with n-trailers mechanism considering the path curvature” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science Volume 236, Issue 17, June. 2022
  • [26] R. Pintelon, M. Schoukens, and J. Lataire, “Best Linear Approximation of Nonlinear Continuous-Time Systems Subject to Process Noise and Operating in Feedback,” IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 10, pp. 8600–8612, Oct. 2020.
  • [27] E. Tazelaar, Y. Shen, P. A. Veenhuizen, T. Hofman, and P. P. J. van den Bosch, “Sizing Stack and Battery of a Fuel Cell Hybrid Distribution Truck,” Oil Gas Sci. Technol. – Rev. d’IFP Energies Nouv., vol. 67, no. 4, pp. 563–573, 2012, doi: 10.2516/ogst/2012014.
  • [28] X. Zhang, L Liu and Y. Dai ” Fuzzy State Machine Energy Management Strategy for Hybrid Electric UAVs with PV/Fuel Cell/Battery Power System” International Journal of Aerospace Engineering 2018, July 2018, pages 1-16.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-99498990-6ea1-454a-8368-77c3e614ab72
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