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A novel tangent error maximum power point tracking algorithm for photovoltaic system under fast multi-changing solar irradiances

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  • Peng, Lele
  • Zheng, Shubin
  • Chai, Xiaodong
  • Li, Liming

Abstract

In this paper, a novel tangent error maximum power point tracking algorithm based on perturb and observe method is presented to achieve the high efficiency for photovoltaic system under fast multi-changing solar irradiances. In order to get a proper initial value, the mathematical model of optimal voltage is established. By using tangent error method, a dynamic perturbation step is calculated. Meanwhile, the characteristics for tracking direction is analyzed in detail to distinguish oscillating power from changes in irradiances and perturbation step. Moreover, the tracking performance of the proposed algorithm is investigated by modeling, simulation and experiment of PV system. Furthermore, errors and statistical analyses are carried out to illustrate the accuracy of the tangent error algorithm. Compared with previous methods in other works, the results demonstrate that the proposed method not only has the fast tracking speed but also the high efficiency. In addition, it is found that the overall energy conversion efficiency of the photovoltaic module has increased by approximately 3% during the whole time. Besides, due to its ease implementation, high efficiency and reliability under fast varying irradiances, the proposed method can be applied to provide energy for moving carriers, such as UAVs, cars and trains.

Suggested Citation

  • Peng, Lele & Zheng, Shubin & Chai, Xiaodong & Li, Liming, 2018. "A novel tangent error maximum power point tracking algorithm for photovoltaic system under fast multi-changing solar irradiances," Applied Energy, Elsevier, vol. 210(C), pages 303-316.
    • Handle: RePEc:eee:appene:v:210:y:2018:i:c:p:303-316
    DOI: 10.1016/j.apenergy.2017.11.017
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    5. 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.
    6. Ehtisham Lodhi & Fei-Yue Wang & Gang Xiong & Ghulam Ali Mallah & Muhammad Yaqoob Javed & Tariku Sinshaw Tamir & David Wenzhong Gao, 2021. "A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
    7. Singh, Bhuwan Pratap & Goyal, Sunil Kumar & Siddiqui, Shahbaz Ahmed & Saraswat, Amit & Ucheniya, Ravi, 2022. "Intersection Point Determination Method: A novel MPPT approach for sudden and fast changing environmental conditions," Renewable Energy, Elsevier, vol. 200(C), pages 614-632.
    8. Zheng, Jianan & Liu, Wenjun & Cui, Ting & Wang, Hanchun & Chen, Fangcai & Gao, Yang & Fan, Liulu & Ali Abaker Omer, Altyeb & Ingenhoff, Jan & Zhang, Xinyu & Liu, Wen, 2023. "A novel domino-like snow removal system for roof PV arrays: Feasibility, performance, and economic benefits," Applied Energy, Elsevier, vol. 333(C).

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