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Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review

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  • Ahmad, Riaz
  • Murtaza, Ali F.
  • Sher, Hadeed Ahmed

Abstract

This paper presents a comprehensive overview on various maximum power point tracking (MPPT) techniques, which have been recently designed, simulated and/or experimentally validated in the PV literature. The primary goal of each MPPT technique is to optimize the output of shaded/unshaded photovoltaic (PV) array under static and dynamic weather conditions. Though each MPPT technique has its own pros and cons, an optimized MPPT technique is characterized in many aspects like hardware and software simplicity, implementation, cost effectiveness, sensors required, popularity, accuracy and convergence speed. In this paper the rating of various MPPT methods has been done based on the benchmark P&O method. The rating criteria is separately calculated for the techniques that are capable to work in full-sun and partial shading conditions. A rule based table is set to evaluate the MPPT against the algorithm's complexity, hardware implementation, tracking speed, and steady state accuracy or detection of global maximum. Moreover, special consideration has been given to bio-inspired MPPT algorithms. The bio-inspired algorithms are compared side by side with their specific application in PV system. A tree diagram is also designed to see the emergence of partial shading algorithms over a period of time. The traits presented in this paper are novel and provide bottom-line for the researchers to select and implement an appropriate MPPT technique.

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  • Ahmad, Riaz & Murtaza, Ali F. & Sher, Hadeed Ahmed, 2019. "Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 82-102.
    • Handle: RePEc:eee:rensus:v:101:y:2019:i:c:p:82-102
    DOI: 10.1016/j.rser.2018.10.015
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    1. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    2. 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.
    3. Ahmad, R. & Murtaza, Ali F. & Ahmed Sher, Hadeed & Tabrez Shami, Umar & Olalekan, Saheed, 2017. "An analytical approach to study partial shading effects on PV array supported by literature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 721-732.
    4. Seyedmahmoudian, M. & Horan, B. & Soon, T. Kok & Rahmani, R. & Than Oo, A. Muang & Mekhilef, S. & Stojcevski, A., 2016. "State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 435-455.
    5. Belhaouas, N. & Cheikh, M.-S. Ait & Agathoklis, P. & Oularbi, M.-R. & Amrouche, B. & Sedraoui, K. & Djilali, N., 2017. "PV array power output maximization under partial shading using new shifted PV array arrangements," Applied Energy, Elsevier, vol. 187(C), pages 326-337.
    6. Jordehi, A. Rezaee, 2016. "Maximum power point tracking in photovoltaic (PV) systems: A review of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1127-1138.
    7. Reza Reisi, Ali & Hassan Moradi, Mohammad & Jamasb, Shahriar, 2013. "Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 433-443.
    8. Merino, S. & Sánchez, F.J. & Sidrach de Cardona, M. & Guzmán, F. & Guzmán, R. & Martínez, J. & Sotorrío, P.J., 2018. "Optimization of energy distribution in solar panel array configurations by graphs and Minkowski’s paths," Applied Mathematics and Computation, Elsevier, vol. 319(C), pages 48-58.
    9. Mahmoud, Marwan M., 2006. "Transient analysis of a PV power generator charging a capacitor for measurement of the I–V characteristics," Renewable Energy, Elsevier, vol. 31(13), pages 2198-2206.
    10. Messalti, Sabir & Harrag, Abdelghani & Loukriz, Abdelhamid, 2017. "A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 221-233.
    11. Guo, Lei & Meng, Zhuo & Sun, Yize & Wang, Libiao, 2018. "A modified cat swarm optimization based maximum power point tracking method for photovoltaic system under partially shaded condition," Energy, Elsevier, vol. 144(C), pages 501-514.
    12. Pandey, A.K. & Tyagi, V.V. & Selvaraj, Jeyraj A/L & Rahim, N.A. & Tyagi, S.K., 2016. "Recent advances in solar photovoltaic systems for emerging trends and advanced applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 859-884.
    13. 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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    5. Ming-Fa Tsai & Chung-Shi Tseng & Kuo-Tung Hung & Shih-Hua Lin, 2021. "A Novel DSP-Based MPPT Control Design for Photovoltaic Systems Using Neural Network Compensator," Energies, MDPI, vol. 14(11), pages 1-20, June.
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    8. Ye Liu & Yiwei Zhong & Chaowei Tang, 2023. "Optimal Sizing of Photovoltaic/Energy Storage Hybrid Power Systems: Considering Output Characteristics and Uncertainty Factors," Energies, MDPI, vol. 16(14), pages 1-23, July.
    9. Baldwin Cortés & Roberto Tapia & Juan J. Flores, 2021. "System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles," Energies, MDPI, vol. 14(16), pages 1-18, August.
    10. Mirza, Adeel Feroz & Mansoor, Majad & Zhan, Keyu & Ling, Qiang, 2021. "High-efficiency swarm intelligent maximum power point tracking control techniques for varying temperature and irradiance," Energy, Elsevier, vol. 228(C).
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