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Novel highly accurate universal maximum power point tracker for maximum power extraction from hybrid fuel cell/photovoltaic/wind power generation systems

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  • Fathabadi, Hassan

Abstract

All the maximum power point tracking (MPPT) units that are currently used in hybrid systems include several distinct MPPT controllers, so that, each MPPT controller is dedicated to a subsystem. Using a distinct MPPT algorithm and controller for each subsystem of a hybrid system explicitly complicates the system implementation, increases cost, and decreases the accuracy of the MPPT process. This paper addresses this problem by presenting a novel fast and highly accurate universal maximum power point (MPP) tracker for hybrid fuel cell/photovoltaic/wind power generation systems. The tracker is called “universal tracker” because it uses a unified algorithm and controller to concurrently track the MPPs of the photovoltaic (PV), fuel cell (FC) and wind energy conversion (WEC) subsystems of a hybrid FC/PV/wind power system. The proposed universal MPP tracker only uses the output voltages and currents of the PV module, FC stack, and WEC subsystem used in a hybrid power system, i.e., it does not need any expensive sensors such as anemometers and tachometers. Moreover, the technique tracks the MPP of the WEC subsystem, not the MPP of its wind turbine, so it extracts the highest output electrical power from the WEC subsystem. A hybrid FC/PV/wind power generation system has been built to validate theoretical results and evaluate the tracker performances. It is experimentally verified that the universal MPP tracker performs a very fast and highly accurate MPPT process, so that, the MPPT efficiencies are about 99.60%, 99.41%, and 99.28% respectively in the PV, FC and WEC subsystems with the very short tracking convergence times of 12 ms, 33 s, and 25 s, respectively. A comparison between the tracker and the state-of-the-art MPP trackers has been also performed that explicitly demonstrates the better performances of the proposed universal MPP tracker, while it concurrently tracks three MPPs but others track only one MPP.

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  • Fathabadi, Hassan, 2016. "Novel highly accurate universal maximum power point tracker for maximum power extraction from hybrid fuel cell/photovoltaic/wind power generation systems," Energy, Elsevier, vol. 116(P1), pages 402-416.
  • Handle: RePEc:eee:energy:v:116:y:2016:i:p1:p:402-416
    DOI: 10.1016/j.energy.2016.09.095
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    References listed on IDEAS

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    1. Han, Wanlong & Yan, Peigang & Han, Wanjin & He, Yurong, 2015. "Design of wind turbines with shroud and lobed ejectors for efficient utilization of low-grade wind energy," Energy, Elsevier, vol. 89(C), pages 687-701.
    2. Parlak, Koray Sener, 2014. "FPGA based new MPPT (maximum power point tracking) method for PV (photovoltaic) array system operating partially shaded conditions," Energy, Elsevier, vol. 68(C), pages 399-410.
    3. Fathabadi, Hassan, 2015. "Lambert W function-based technique for tracking the maximum power point of PV modules connected in various configurations," Renewable Energy, Elsevier, vol. 74(C), pages 214-226.
    4. Daraban, Stefan & Petreus, Dorin & Morel, Cristina, 2014. "A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading," Energy, Elsevier, vol. 74(C), pages 374-388.
    5. Belmokhtar, K. & Doumbia, M.L. & Agbossou, K., 2014. "Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator)," Energy, Elsevier, vol. 76(C), pages 679-693.
    6. Kumar, Dipesh & Chatterjee, Kalyan, 2016. "A review of conventional and advanced MPPT algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 957-970.
    7. Fathabadi, Hassan, 2016. "Maximum mechanical power extraction from wind turbines using novel proposed high accuracy single-sensor-based maximum power point tracking technique," Energy, Elsevier, vol. 113(C), pages 1219-1230.
    8. Jiang, Joe-Air & Su, Yu-Li & Shieh, Jyh-Cherng & Kuo, Kun-Chang & Lin, Tzu-Shiang & Lin, Ta-Te & Fang, Wei & Chou, Jui-Jen & Wang, Jen-Cheng, 2014. "On application of a new hybrid maximum power point tracking (MPPT) based photovoltaic system to the closed plant factory," Applied Energy, Elsevier, vol. 124(C), pages 309-324.
    9. Dai, Juchuan & Liu, Deshun & Wen, Li & Long, Xin, 2016. "Research on power coefficient of wind turbines based on SCADA data," Renewable Energy, Elsevier, vol. 86(C), pages 206-215.
    10. Bouilouta, A. & Mellit, A. & Kalogirou, S.A., 2013. "New MPPT method for stand-alone photovoltaic systems operating under partially shaded conditions," Energy, Elsevier, vol. 55(C), pages 1172-1185.
    11. Carton, J.G. & Olabi, A.G., 2010. "Wind/hydrogen hybrid systems: Opportunity for Ireland’s wind resource to provide consistent sustainable energy supply," Energy, Elsevier, vol. 35(12), pages 4536-4544.
    12. Fathabadi, Hassan, 2015. "Utilization of electric vehicles and renewable energy sources used as distributed generators for improving characteristics of electric power distribution systems," Energy, Elsevier, vol. 90(P1), pages 1100-1110.
    13. Rizzo, Santi Agatino & Scelba, Giacomo, 2015. "ANN based MPPT method for rapidly variable shading conditions," Applied Energy, Elsevier, vol. 145(C), pages 124-132.
    14. Elnaggar, M. & Abdel Fattah, H.A. & Elshafei, A.L., 2014. "Maximum power tracking in WECS (Wind energy conversion systems) via numerical and stochastic approaches," Energy, Elsevier, vol. 74(C), pages 651-661.
    15. Fathabadi, Hassan, 2016. "Novel fast dynamic MPPT (maximum power point tracking) technique with the capability of very high accurate power tracking," Energy, Elsevier, vol. 94(C), pages 466-475.
    16. Xie, Wei & Zeng, Pan & Lei, Liping, 2015. "Wind tunnel experiments for innovative pitch regulated blade of horizontal axis wind turbine," Energy, Elsevier, vol. 91(C), pages 1070-1080.
    17. Ahmed, Jubaer & Salam, Zainal, 2014. "A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability," Applied Energy, Elsevier, vol. 119(C), pages 118-130.
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    2. Rezk, Hegazy & Fathy, Ahmed & Abdelaziz, Almoataz Y., 2017. "A comparison of different global MPPT techniques based on meta-heuristic algorithms for photovoltaic system subjected to partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 377-386.
    3. Aktaş, Ahmet & Kırçiçek, Yağmur, 2020. "A novel optimal energy management strategy for offshore wind/marine current/battery/ultracapacitor hybrid renewable energy system," Energy, Elsevier, vol. 199(C).
    4. Kebir, Anouer & Woodward, Lyne & Akhrif, Ouassima, 2019. "Real-time optimization of renewable energy sources power using neural network-based anticipative extremum-seeking control," Renewable Energy, Elsevier, vol. 134(C), pages 914-926.
    5. Mao, Mingxuan & Zhang, Li & Duan, Pan & Duan, Qichang & Yang, Ming, 2018. "Grid-connected modular PV-Converter system with shuffled frog leaping algorithm based DMPPT controller," Energy, Elsevier, vol. 143(C), pages 181-190.
    6. Mohammad Junaid Khan & Divesh Kumar & Yogendra Narayan & Hasmat Malik & Fausto Pedro García Márquez & Carlos Quiterio Gómez Muñoz, 2022. "A Novel Artificial Intelligence Maximum Power Point Tracking Technique for Integrated PV-WT-FC Frameworks," Energies, MDPI, vol. 15(9), pages 1-35, May.

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