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Enhancing the maximum power point tracking techniques for photovoltaic systems

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  • Abu Eldahab, Yasser E.
  • Saad, Naggar H.
  • Zekry, Abdalhalim

Abstract

The development of maximum power point tracking (MPPT) is continuing in order to increase the energy transfer efficiency of the solar photovoltaic system. This paper provides a review of the conventional maximum power point tracking techniques that is enhanced by the presentation of a new technique. The new method is based on a genetic neural algorithm in order to predict the closest point to the maximum power point (MPP), which will be the kickoff point of the search process. Not only does the new technique start the search process from the nearest point to the MPP, but also the developed search algorithm is very fast. Consequently, the time taken to reach the MPP is reduced. In order to determine the new MPPT performance, a complete photovoltaic generator system is modeled and simulated using the MATLAB/SIMULINK package. Simulation results show that the new technique reaches the MPP in less than 100 sample times compared to tens of thousands of samples for conventional methods. Furthermore, the new technique reaches directly the target MPP with small deviation from the intended values. Consequently, the new technique has a significant improvement in energy extraction efficiency from the photovoltaic array to the load, in addition to higher tracking speed and system stability compared to the conventional ones.

Suggested Citation

  • Abu Eldahab, Yasser E. & Saad, Naggar H. & Zekry, Abdalhalim, 2014. "Enhancing the maximum power point tracking techniques for photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 505-514.
    • Handle: RePEc:eee:rensus:v:40:y:2014:i:c:p:505-514
    DOI: 10.1016/j.rser.2014.07.202
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    References listed on IDEAS

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    1. Tafticht, T. & Agbossou, K. & Doumbia, M.L. & Chériti, A., 2008. "An improved maximum power point tracking method for photovoltaic systems," Renewable Energy, Elsevier, vol. 33(7), pages 1508-1516.
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    1. Nabipour, M. & Razaz, M. & Seifossadat, S.GH & Mortazavi, S.S., 2017. "A new MPPT scheme based on a novel fuzzy approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1147-1169.
    2. Harrag, Abdelghani & Messalti, Sabir, 2015. "Variable step size modified P&O MPPT algorithm using GA-based hybrid offline/online PID controller," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1247-1260.
    3. Mahela, Om Prakash & Shaik, Abdul Gafoor, 2017. "Comprehensive overview of grid interfaced solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 316-332.
    4. Jiang, Joe-Air & Su, Yu-Li & Kuo, Kun-Chang & Wang, Chien-Hao & Liao, Min-Sheng & Wang, Jen-Cheng & Huang, Chen-Kang & Chou, Cheng-Ying & Lee, Chien-Hsing & Shieh, Jyh-Cherng, 2017. "On a hybrid MPPT control scheme to improve energy harvesting performance of traditional two-stage inverters used in photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1113-1128.
    5. Abu Eldahab, Yasser E. & Saad, Naggar H. & Zekry, Abdalhalim, 2016. "Enhancing the design of battery charging controllers for photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 646-655.
    6. 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.
    7. Nižetić, S. & Grubišić- Čabo, F. & Marinić-Kragić, I. & Papadopoulos, A.M., 2016. "Experimental and numerical investigation of a backside convective cooling mechanism on photovoltaic panels," Energy, Elsevier, vol. 111(C), pages 211-225.
    8. Abu Eldahab, Yasser E. & Saad, Naggar H. & Zekry, Abdalhalim, 2017. "Enhancing the tracking techniques for the global maximum power point under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1173-1183.

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