IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i18p3527-d267072.html
   My bibliography  Save this article

Parameters Extraction of Photovoltaic Models Using an Improved Moth-Flame Optimization

Author

Listed:
  • Huawen Sheng

    (School of Information Engineering, Nanchang University, Nanchang 330029, China)

  • Chunquan Li

    (School of Information Engineering, Nanchang University, Nanchang 330029, China)

  • Hanming Wang

    (School of Information Engineering, Nanchang University, Nanchang 330029, China)

  • Zeyuan Yan

    (School of Information Engineering, Nanchang University, Nanchang 330029, China)

  • Yin Xiong

    (School of Information Engineering, Nanchang University, Nanchang 330029, China)

  • Zhenting Cao

    (School of Information Engineering, Nanchang University, Nanchang 330029, China)

  • Qianying Kuang

    (School of Information Engineering, Nanchang University, Nanchang 330029, China)

Abstract

Photovoltaic (PV) models’ parameter extraction with the tested current-voltage values is vital for the optimization, control, and evaluation of the PV systems. To reliably and accurately extract their parameters, this paper presents one improved moths-flames optimization (IMFO) method. In the IMFO, a double flames generation (DFG) strategy is proposed to generate two different types of target flames for guiding the flying of moths. Furthermore, two different update strategies are developed for updating the positions of moths. To greatly balance the exploitation and exploration, we adopt a probability to rationally select one of the two update strategies for each moth at each iteration. The proposed IMFO is used to distinguish the parameter of three test PV models including single diode model (SDM), double diode model (DDM), and PV module model (PMM). The results indicate that, compared with other well-established methods, the proposed IMFO can obtain an extremely promising performance.

Suggested Citation

  • Huawen Sheng & Chunquan Li & Hanming Wang & Zeyuan Yan & Yin Xiong & Zhenting Cao & Qianying Kuang, 2019. "Parameters Extraction of Photovoltaic Models Using an Improved Moth-Flame Optimization," Energies, MDPI, vol. 12(18), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:18:p:3527-:d:267072
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/18/3527/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/18/3527/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jiang, Lian Lian & Maskell, Douglas L. & Patra, Jagdish C., 2013. "Parameter estimation of solar cells and modules using an improved adaptive differential evolution algorithm," Applied Energy, Elsevier, vol. 112(C), pages 185-193.
    2. Patel, Sanjaykumar J. & Panchal, Ashish K. & Kheraj, Vipul, 2014. "Extraction of solar cell parameters from a single current–voltage characteristic using teaching learning based optimization algorithm," Applied Energy, Elsevier, vol. 119(C), pages 384-393.
    3. Oliva, Diego & Cuevas, Erik & Pajares, Gonzalo, 2014. "Parameter identification of solar cells using artificial bee colony optimization," Energy, Elsevier, vol. 72(C), pages 93-102.
    4. Bastidas-Rodriguez, J.D. & Petrone, G. & Ramos-Paja, C.A. & Spagnuolo, G., 2017. "A genetic algorithm for identifying the single diode model parameters of a photovoltaic panel," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 38-54.
    5. Chen, Zhicong & Wu, Lijun & Lin, Peijie & Wu, Yue & Cheng, Shuying, 2016. "Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy," Applied Energy, Elsevier, vol. 182(C), pages 47-57.
    6. Oliva, Diego & Abd El Aziz, Mohamed & Ella Hassanien, Aboul, 2017. "Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm," Applied Energy, Elsevier, vol. 200(C), pages 141-154.
    7. Wu, Zhou & Tazvinga, Henerica & Xia, Xiaohua, 2015. "Demand side management of photovoltaic-battery hybrid system," Applied Energy, Elsevier, vol. 148(C), pages 294-304.
    8. Lau, Lee Chung & Lee, Keat Teong & Mohamed, Abdul Rahman, 2012. "Global warming mitigation and renewable energy policy development from the Kyoto Protocol to the Copenhagen Accord—A comment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 5280-5284.
    9. Chen, Xu & Yu, Kunjie & Du, Wenli & Zhao, Wenxiang & Liu, Guohai, 2016. "Parameters identification of solar cell models using generalized oppositional teaching learning based optimization," Energy, Elsevier, vol. 99(C), pages 170-180.
    10. Jieming Ma & T. O. Ting & Ka Lok Man & Nan Zhang & Sheng-Uei Guan & Prudence W. H. Wong, 2013. "Parameter Estimation of Photovoltaic Models via Cuckoo Search," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-8, August.
    11. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    12. Fathy, Ahmed & Rezk, Hegazy, 2017. "Parameter estimation of photovoltaic system using imperialist competitive algorithm," Renewable Energy, Elsevier, vol. 111(C), pages 307-320.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Yiying & Ma, Maode & Jin, Zhigang, 2020. "Comprehensive learning Jaya algorithm for parameter extraction of photovoltaic models," Energy, Elsevier, vol. 211(C).
    2. Abd-ElHady Ramadan & Salah Kamel & Tahir Khurshaid & Seung-Ryle Oh & Sang-Bong Rhee, 2021. "Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer," Sustainability, MDPI, vol. 13(12), pages 1-16, June.
    3. Chennoufi, Khalid & Ferfra, Mohammed & Mokhlis, Mohcine, 2021. "An accurate modelling of Photovoltaic modules based on two-diode model," Renewable Energy, Elsevier, vol. 167(C), pages 294-305.
    4. Mehmet Yesilbudak, 2021. "Parameter Extraction of Photovoltaic Cells and Modules Using Grey Wolf Optimizer with Dimension Learning-Based Hunting Search Strategy," Energies, MDPI, vol. 14(18), pages 1-27, September.
    5. Li, Shuijia & Gong, Wenyin & Gu, Qiong, 2021. "A comprehensive survey on meta-heuristic algorithms for parameter extraction of photovoltaic models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    6. Luis Miguel Pérez Archila & Juan David Bastidas-Rodríguez & Rodrigo Correa & Luz Adriana Trejos Grisales & Daniel Gonzalez-Montoya, 2020. "A Solution of Implicit Model of Series-Parallel Photovoltaic Arrays by Using Deterministic and Metaheuristic Global Optimization Algorithms," Energies, MDPI, vol. 13(4), pages 1-22, February.
    7. Li, Shuijia & Gong, Wenyin & Hu, Chengyu & Yan, Xuesong & Wang, Ling & Gu, Qiong, 2021. "Adaptive constraint differential evolution for optimal power flow," Energy, Elsevier, vol. 235(C).
    8. Fan Wang & Xiang Liao & Na Fang & Zhiqiang Jiang, 2022. "Optimal Scheduling of Regional Combined Heat and Power System Based on Improved MFO Algorithm," Energies, MDPI, vol. 15(9), pages 1-30, May.
    9. Ahmadianfar, Iman & Samadi-Koucheksaraee, Arvin & Razavi, Saman, 2023. "Design of optimal operating rule curves for hydropower multi-reservoir systems by an influential optimization method," Renewable Energy, Elsevier, vol. 211(C), pages 508-521.
    10. Xing Zhang & Chongchong Zhang & Zhuoqun Wei, 2019. "Carbon Price Forecasting Based on Multi-Resolution Singular Value Decomposition and Extreme Learning Machine Optimized by the Moth–Flame Optimization Algorithm Considering Energy and Economic Factors," Energies, MDPI, vol. 12(22), pages 1-23, November.
    11. Rizk-Allah, Rizk M. & El-Fergany, Attia A., 2021. "Emended heap-based optimizer for characterizing performance of industrial solar generating units using triple-diode model," Energy, Elsevier, vol. 237(C).
    12. Chen, Xu & Yue, Hong & Yu, Kunjie, 2019. "Perturbed stochastic fractal search for solar PV parameter estimation," Energy, Elsevier, vol. 189(C).
    13. Piotr Olczak & Dominika Matuszewska & Jadwiga Zabagło, 2020. "The Comparison of Solar Energy Gaining Effectiveness between Flat Plate Collectors and Evacuated Tube Collectors with Heat Pipe: Case Study," Energies, MDPI, vol. 13(7), pages 1-14, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu, Kunjie & Liang, J.J. & Qu, B.Y. & Cheng, Zhiping & Wang, Heshan, 2018. "Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models," Applied Energy, Elsevier, vol. 226(C), pages 408-422.
    2. Abbassi, Rabeh & Abbassi, Abdelkader & Jemli, Mohamed & Chebbi, Souad, 2018. "Identification of unknown parameters of solar cell models: A comprehensive overview of available approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 453-474.
    3. Martin Ćalasan & Dražen Jovanović & Vesna Rubežić & Saša Mujović & Slobodan Đukanović, 2019. "Estimation of Single-Diode and Two-Diode Solar Cell Parameters by Using a Chaotic Optimization Approach," Energies, MDPI, vol. 12(21), pages 1-14, November.
    4. Nunes, H.G.G. & Pombo, J.A.N. & Mariano, S.J.P.S. & Calado, M.R.A. & Felippe de Souza, J.A.M., 2018. "A new high performance method for determining the parameters of PV cells and modules based on guaranteed convergence particle swarm optimization," Applied Energy, Elsevier, vol. 211(C), pages 774-791.
    5. Chin, Vun Jack & Salam, Zainal, 2019. "A New Three-point-based Approach for the Parameter Extraction of Photovoltaic Cells," Applied Energy, Elsevier, vol. 237(C), pages 519-533.
    6. Li, Shuijia & Gong, Wenyin & Gu, Qiong, 2021. "A comprehensive survey on meta-heuristic algorithms for parameter extraction of photovoltaic models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    7. Mehmet Yesilbudak, 2021. "Parameter Extraction of Photovoltaic Cells and Modules Using Grey Wolf Optimizer with Dimension Learning-Based Hunting Search Strategy," Energies, MDPI, vol. 14(18), pages 1-27, September.
    8. Wu, Lijun & Chen, Zhicong & Long, Chao & Cheng, Shuying & Lin, Peijie & Chen, Yixiang & Chen, Huihuang, 2018. "Parameter extraction of photovoltaic models from measured I-V characteristics curves using a hybrid trust-region reflective algorithm," Applied Energy, Elsevier, vol. 232(C), pages 36-53.
    9. Blaifi, Sid-ali & Moulahoum, Samir & Taghezouit, Bilal & Saim, Abdelhakim, 2019. "An enhanced dynamic modeling of PV module using Levenberg-Marquardt algorithm," Renewable Energy, Elsevier, vol. 135(C), pages 745-760.
    10. Chen, Xu & Xu, Bin & Mei, Congli & Ding, Yuhan & Li, Kangji, 2018. "Teaching–learning–based artificial bee colony for solar photovoltaic parameter estimation," Applied Energy, Elsevier, vol. 212(C), pages 1578-1588.
    11. Samuel R. Fahim & Hany M. Hasanien & Rania A. Turky & Shady H. E. Abdel Aleem & Martin Ćalasan, 2022. "A Comprehensive Review of Photovoltaic Modules Models and Algorithms Used in Parameter Extraction," Energies, MDPI, vol. 15(23), pages 1-56, November.
    12. Yu, Kunjie & Qu, Boyang & Yue, Caitong & Ge, Shilei & Chen, Xu & Liang, Jing, 2019. "A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module," Applied Energy, Elsevier, vol. 237(C), pages 241-257.
    13. Long, Wen & Wu, Tiebin & Xu, Ming & Tang, Mingzhu & Cai, Shaohong, 2021. "Parameters identification of photovoltaic models by using an enhanced adaptive butterfly optimization algorithm," Energy, Elsevier, vol. 229(C).
    14. Hassan Shaban & Essam H. Houssein & Marco Pérez-Cisneros & Diego Oliva & Amir Y. Hassan & Alaa A. K. Ismaeel & Diaa Salama AbdElminaam & Sanchari Deb & Mokhtar Said, 2021. "Identification of Parameters in Photovoltaic Models through a Runge Kutta Optimizer," Mathematics, MDPI, vol. 9(18), pages 1-22, September.
    15. Arooj Tariq Kiani & Muhammad Faisal Nadeem & Ali Ahmed & Irfan Khan & Rajvikram Madurai Elavarasan & Narottam Das, 2020. "Optimal PV Parameter Estimation via Double Exponential Function-Based Dynamic Inertia Weight Particle Swarm Optimization," Energies, MDPI, vol. 13(15), pages 1-26, August.
    16. Khan, Firoz & Al-Ahmed, Amir & Al-Sulaiman, Fahad A., 2021. "Critical analysis of the limitations and validity of the assumptions with the analytical methods commonly used to determine the photovoltaic cell parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    17. Peñaranda Chenche, Luz Elena & Hernandez Mendoza, Oscar Saul & Bandarra Filho, Enio Pedone, 2018. "Comparison of four methods for parameter estimation of mono- and multi-junction photovoltaic devices using experimental data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2823-2838.
    18. Ebrahimi, S. Mohammadreza & Salahshour, Esmaeil & Malekzadeh, Milad & Francisco Gordillo,, 2019. "Parameters identification of PV solar cells and modules using flexible particle swarm optimization algorithm," Energy, Elsevier, vol. 179(C), pages 358-372.
    19. Adeel, Muhammad & Hassan, Ahmad Kamal & Sher, Hadeed Ahmed & Murtaza, Ali Faisal, 2021. "A grade point average assessment of analytical and numerical methods for parameter extraction of a practical PV device," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    20. Chen, Xu & Yue, Hong & Yu, Kunjie, 2019. "Perturbed stochastic fractal search for solar PV parameter estimation," Energy, Elsevier, vol. 189(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:18:p:3527-:d:267072. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.