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Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions

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  • Sivakumar, P.
  • Abdul Kader, Abdullah
  • Kaliavaradhan, Yogeshraj
  • Arutchelvi, M.

Abstract

This paper presents experimental evaluations for variation in the efficiency of energy extracted from a photovoltaic (PV) module (under non-linear loading) incorporated with an incremental conductance(IC) maximum power point tracking (MPPT) algorithm. The focus is on the evaluation of the PV panel under non-linear loading conditions using the experimental installation of a 100Wp photovoltaic array connected to a DC–DC converter and a KVA inverter feeding a non-linear load. Under the conditions of non-linear loading, both the simulation and experiment show that the MPPT technique fails to attain maximum power point due to the presence of ripples in the current leading eventually to a reduction in efficiency. In this paper, panel current is taken as a function of load impedance in the MPPT algorithm to eradicate power variation, as load impedance varies with supply voltage under non-linear conditions. The system is simulated for different non-linear loads using MATLAB-Simulink. A TMDSSOLAREXPKIT was used for MPPT control. In case 2, the inverter is connected to a single phase grid. When a voltage swell occurs in the grid, PV power drops. This power loss is reduced using the proposed MPPT method. The results of simulations and experimental measurements and cost efficiency calculations are presented.

Suggested Citation

  • Sivakumar, P. & Abdul Kader, Abdullah & Kaliavaradhan, Yogeshraj & Arutchelvi, M., 2015. "Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions," Renewable Energy, Elsevier, vol. 81(C), pages 543-550.
    • Handle: RePEc:eee:renene:v:81:y:2015:i:c:p:543-550
    DOI: 10.1016/j.renene.2015.03.062
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    Cited by:

    1. Yi Jin & Wenhui Hou & Guiqiang Li & Xiao Chen, 2017. "A Glowworm Swarm Optimization-Based Maximum Power Point Tracking for Photovoltaic/Thermal Systems under Non-Uniform Solar Irradiation and Temperature Distribution," Energies, MDPI, vol. 10(4), pages 1-13, April.
    2. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    3. Haidar Islam & Saad Mekhilef & Noraisyah Binti Mohamed Shah & Tey Kok Soon & Mehdi Seyedmahmousian & Ben Horan & Alex Stojcevski, 2018. "Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems," Energies, MDPI, vol. 11(2), pages 1-24, February.
    4. Joshi, Puneet & Arora, Sudha, 2017. "Maximum power point tracking methodologies for solar PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1154-1177.
    5. Yinxiao Zhu & Moon Keun Kim & Huiqing Wen, 2018. "Simulation and Analysis of Perturbation and Observation-Based Self-Adaptable Step Size Maximum Power Point Tracking Strategy with Low Power Loss for Photovoltaics," Energies, MDPI, vol. 12(1), pages 1-20, December.
    6. Jong-Chan Kim & Jun-Ho Huh & Jae-Sub Ko, 2020. "Optimization Design and Test Bed of Fuzzy Control Rule Base for PV System MPPT in Micro Grid," Sustainability, MDPI, vol. 12(9), pages 1-25, May.
    7. Mostafaeipour, Ali & Qolipour, Mojtaba & Mohammadi, Kasra, 2016. "Evaluation of installing photovoltaic plants using a hybrid approach for Khuzestan province, Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 60-74.
    8. Hong, Ying-Yi & Beltran, Angelo A. & Paglinawan, Arnold C., 2018. "A robust design of maximum power point tracking using Taguchi method for stand-alone PV system," Applied Energy, Elsevier, vol. 211(C), pages 50-63.
    9. Ram, J.Prasanth & Rajasekar, N. & Miyatake, Masafumi, 2017. "Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1138-1159.
    10. Alexandro Ortiz & Efrain Mendez & Israel Macias & Arturo Molina, 2022. "Earthquake Algorithm-Based Voltage Referenced MPPT Implementation through a Standardized Validation Frame," Energies, MDPI, vol. 15(23), pages 1-24, November.
    11. Venkateswari, R. & Sreejith, S., 2019. "Factors influencing the efficiency of photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 376-394.
    12. Chin, Vun Jack & Salam, Zainal & Ishaque, Kashif, 2015. "Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review," Applied Energy, Elsevier, vol. 154(C), pages 500-519.
    13. Ram, J. Prasanth & Babu, T. Sudhakar & Rajasekar, N., 2017. "A comprehensive review on solar PV maximum power point tracking techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 826-847.
    14. Sidra Mumtaz & Saghir Ahmad & Laiq Khan & Saima Ali & Tariq Kamal & Syed Zulqadar Hassan, 2018. "Adaptive Feedback Linearization Based NeuroFuzzy Maximum Power Point Tracking for a Photovoltaic System," Energies, MDPI, vol. 11(3), pages 1-15, March.
    15. G, Dileep. & Singh, S.N., 2017. "Selection of non-isolated DC-DC converters for solar photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1230-1247.
    16. Li, Shaowu, 2016. "Linear equivalent models at the maximum power point based on variable weather parameters for photovoltaic cell," Applied Energy, Elsevier, vol. 182(C), pages 94-104.
    17. Chendi Li & Yuanrui Chen & Dongbao Zhou & Junfeng Liu & Jun Zeng, 2016. "A High-Performance Adaptive Incremental Conductance MPPT Algorithm for Photovoltaic Systems," Energies, MDPI, vol. 9(4), pages 1-17, April.
    18. Moacyr A. G. de Brito & Victor A. Prado & Edson A. Batista & Marcos G. Alves & Carlos A. Canesin, 2021. "Design Procedure to Convert a Maximum Power Point Tracking Algorithm into a Loop Control System," Energies, MDPI, vol. 14(15), pages 1-17, July.
    19. Md Tahmid Hussain & Adil Sarwar & Mohd Tariq & Shabana Urooj & Amal BaQais & Md. Alamgir Hossain, 2023. "An Evaluation of ANN Algorithm Performance for MPPT Energy Harvesting in Solar PV Systems," Sustainability, MDPI, vol. 15(14), pages 1-36, July.

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