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A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics

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  • Jiang, Lian Lian
  • Nayanasiri, D.R.
  • Maskell, Douglas L.
  • Vilathgamuwa, D.M.

Abstract

Partial shading and rapidly changing irradiance conditions significantly impact on the performance of photovoltaic (PV) systems. These impacts are particularly severe in tropical regions where the climatic conditions result in very large and rapid changes in irradiance. In this paper, a hybrid maximum power point (MPP) tracking (MPPT) technique for PV systems operating under partially shaded conditions witapid irradiance change is proposed. It combines a conventional MPPT and an artificial neural network (ANN)-based MPPT. A low cost method is proposed to predict the global MPP region when expensive irradiance sensors are not available or are not justifiable for cost reasons. It samples the operating point on the stairs of I–V curve and uses a combination of the measured current value at each stair to predict the global MPP region. The conventional MPPT is then used to search within the classified region to get the global MPP. The effectiveness of the proposed MPPT is demonstrated using both simulations and an experimental setup. Experimental comparisons with four existing MPPTs are performed. The results show that the proposed MPPT produces more energy than the other techniques and can effectively track the global MPP with a fast tracking speed under various shading patterns.

Suggested Citation

  • Jiang, Lian Lian & Nayanasiri, D.R. & Maskell, Douglas L. & Vilathgamuwa, D.M., 2015. "A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics," Renewable Energy, Elsevier, vol. 76(C), pages 53-65.
    • Handle: RePEc:eee:renene:v:76:y:2015:i:c:p:53-65
    DOI: 10.1016/j.renene.2014.11.005
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    References listed on IDEAS

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    5. Başoğlu, Mustafa Engin & Çakır, Bekir, 2016. "Comparisons of MPPT performances of isolated and non-isolated DC–DC converters by using a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1100-1113.
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    7. Belhachat, Faiza & Larbes, Cherif, 2017. "Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 875-889.
    8. Başoğlu, Mustafa Engin & Çakır, Bekir, 2016. "A novel voltage-current characteristic based global maximum power point tracking algorithm in photovoltaic systems," Energy, Elsevier, vol. 112(C), pages 153-163.
    9. Khaled Bataineh & Naser Eid, 2018. "A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather Conditions," Resources, MDPI, vol. 7(4), pages 1-16, November.
    10. Saud Alotaibi & Ahmed Darwish, 2021. "Modular Multilevel Converters for Large-Scale Grid-Connected Photovoltaic Systems: A Review," Energies, MDPI, vol. 14(19), pages 1-30, September.
    11. Ali Bughneda & Mohamed Salem & Anna Richelli & Dahaman Ishak & Salah Alatai, 2021. "Review of Multilevel Inverters for PV Energy System Applications," Energies, MDPI, vol. 14(6), pages 1-23, March.
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    13. Kermadi, Mostefa & Berkouk, El Madjid, 2017. "Artificial intelligence-based maximum power point tracking controllers for Photovoltaic systems: Comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 369-386.

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