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Series–Parallel PV array re-configuration: Maximization of the extraction of energy and much more

Author

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  • Balato, M.
  • Costanzo, L.
  • Vitelli, M.

Abstract

In this paper a simple and fast re-configuration algorithm which is suitable for a PV array with Series–Parallel architecture is presented and discussed. The main advantage of such an algorithm is represented by its capability to find a nearly optimal configuration by testing only a very small subset of all the possible configurations. In particular it is shown that, in an actual PV array composed by 24 PV modules which operate under mismatching conditions (which are quite common in urban environments due to chimneys, streets lighting poles, antennas, neighboring buildings, etc.), the proposed algorithm is able to lead to energetic performances which are more or less comparable with those ones which can be obtained by adopting a Monte Carlo based algorithm employing a much higher number of trials. Moreover, by means of a specific example, it is shown that maximization of extracted energy and absence of dangerous operating conditions, possibly leading to the premature aging of the PV field and/or to hot spot phenomena, are contrasting requirements. It is nonetheless possible to find proper configurations able to lead to a suitable compromise between such two contrasting requirements. Further work is needed and is in progress in order to design suitable re-configuration algorithms able to identify such compromise configurations.

Suggested Citation

  • Balato, M. & Costanzo, L. & Vitelli, M., 2015. "Series–Parallel PV array re-configuration: Maximization of the extraction of energy and much more," Applied Energy, Elsevier, vol. 159(C), pages 145-160.
  • Handle: RePEc:eee:appene:v:159:y:2015:i:c:p:145-160
    DOI: 10.1016/j.apenergy.2015.08.073
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    Cited by:

    1. Mohammed Alkahtani & Yihua Hu & Zuyu Wu & Colin Sokol Kuka & Muflih S. Alhammad & Chen Zhang, 2020. "Gene Evaluation Algorithm for Reconfiguration of Medium and Large Size Photovoltaic Arrays Exhibiting Non-Uniform Aging," Energies, MDPI, vol. 13(8), pages 1-19, April.
    2. Jung, Tae Hee & Lee, Jeong In & Song, Hee-eun & Ju, Young Chul & Ko, Suk Whan & Jung, Young-Seok & Kang, Gi Hwan, 2017. "Classification conditions of cells to reduce cell-to-module conversion loss at the production stage of PV modules," Renewable Energy, Elsevier, vol. 103(C), pages 582-593.
    3. Walker, Linus & Hofer, Johannes & Schlueter, Arno, 2019. "High-resolution, parametric BIPV and electrical systems modeling and design," Applied Energy, Elsevier, vol. 238(C), pages 164-179.
    4. Shan, Chuan & Sun, Kangwen & Ji, Xinzhe & Cheng, Dongji, 2023. "A reconfiguration method for photovoltaic array of stratospheric airship based on multilevel optimization algorithm," Applied Energy, Elsevier, vol. 352(C).
    5. Mahdavyfakhr, Mohammad & Rashidirad, Nasim & Hamzeh, Mohsen & Sheshyekani, Keyhan & Afjei, Ebrahim, 2017. "Stability improvement of DC grids involving a large number of parallel solar power optimizers: An active damping approach," Applied Energy, Elsevier, vol. 203(C), pages 364-372.
    6. Tang, Ruoli & Lin, Qiao & Zhou, Jinxiang & Zhang, Shangyu & Lai, Jingang & Li, Xin & Dong, Zhengcheng, 2020. "Suppression strategy of short-term and long-term environmental disturbances for maritime photovoltaic system," Applied Energy, Elsevier, vol. 259(C).
    7. Marco Balato & Carlo Petrarca, 2020. "The Impact of Reconfiguration on the Energy Performance of the Distributed Maximum Power Point Tracking Approach in PV Plants," Energies, MDPI, vol. 13(6), pages 1-19, March.
    8. Jian Zhao & Xuesong Zhou & Youjie Ma & Yiqi Liu, 2017. "Analysis of Dynamic Characteristic for Solar Arrays in Series and Global Maximum Power Point Tracking Based on Optimal Initial Value Incremental Conductance Strategy under Partially Shaded Conditions," Energies, MDPI, vol. 10(1), pages 1-23, January.
    9. Marco Balato & Annalisa Liccardo & Carlo Petrarca, 2020. "Dynamic Boost Based DMPPT Emulator," Energies, MDPI, vol. 13(11), pages 1-16, June.
    10. Giuseppe Schettino & Filippo Pellitteri & Guido Ala & Rosario Miceli & Pietro Romano & Fabio Viola, 2020. "Dynamic Reconfiguration Systems for PV Plant: Technical and Economic Analysis," Energies, MDPI, vol. 13(8), pages 1-21, April.
    11. Mohammad Nor Rafiq Nazeri & Mohammad Faridun Naim Tajuddin & Thanikanti Sudhakar Babu & Azralmukmin Azmi & Maria Malvoni & Nallapaneni Manoj Kumar, 2021. "Firefly Algorithm-Based Photovoltaic Array Reconfiguration for Maximum Power Extraction during Mismatch Conditions," Sustainability, MDPI, vol. 13(6), pages 1-30, March.
    12. Xiaoguang Liu & Yuefeng Wang, 2019. "Reconfiguration Method to Extract More Power from Partially Shaded Photovoltaic Arrays with Series-Parallel Topology," Energies, MDPI, vol. 12(8), pages 1-16, April.
    13. Bradai, R. & Boukenoui, R. & Kheldoun, A. & Salhi, H. & Ghanes, M. & Barbot, J-P. & Mellit, A., 2017. "Experimental assessment of new fast MPPT algorithm for PV systems under non-uniform irradiance conditions," Applied Energy, Elsevier, vol. 199(C), pages 416-429.
    14. Dong Ji & Cai Zhang & Mingsong Lv & Ye Ma & Nan Guan, 2017. "Photovoltaic Array Fault Detection by Automatic Reconfiguration," Energies, MDPI, vol. 10(5), pages 1-13, May.

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