IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v296y2024ics0360544224009368.html
   My bibliography  Save this article

CGH-GTO method for model parameter identification based on improved grey wolf optimizer, honey badger algorithm, and gorilla troops optimizer

Author

Listed:
  • Jiang, Meng
  • Ding, Kun
  • Chen, Xiang
  • Cui, Liu
  • Zhang, Jingwei
  • Cang, Yi
  • Yang, Hang
  • Gao, Ruiguang

Abstract

The current–voltage (I–V) characteristics are significant for applied research in photovoltaics (PV). The I–V characteristics calculated by double diode model (DDM) are accurate. DDM contains seven parameters, which are hard to solve. The combination method (CGH-GTO) based on improved grey wolf optimizer (IGWO), honey badger algorithm (HBA), and gorilla troops optimizer (GTO) for model parameter identification is proposed. First, the random initialization of GWO is replaced by Circle chaotic mapping (CCM). IGWO is employed to provide good initial values of parameters. Then, the bird-guided method of HBA is applied to optimize GTO for precise identification. Finally, the effectiveness, stability, and practicality of CGH-GTO are verified through experiments. The optimal RMSE (Root Mean Square Error) and R2 (Coefficient of determination) of CGH-GTO are 0.00241A and 0.99999 for TSM-240. Compared to the reference method GTO, the improvement ratio of RMSE for CGH-GTO can reach 7.3%. For Photowatt-PWP 201, the average RMSE of CGH-GTO is 0.00184A in the stability experiment. The RMSE of CGH-GTO is stabilized at [0.00182A, 0.00350A]. For three PV cell models, the results of evaluation metrics for DDM present the optimum. CGH-GTO achieves the highest accuracy in model parameter identification for DDM with RMSE and R2 of 0.00182A and 0.99999.

Suggested Citation

  • Jiang, Meng & Ding, Kun & Chen, Xiang & Cui, Liu & Zhang, Jingwei & Cang, Yi & Yang, Hang & Gao, Ruiguang, 2024. "CGH-GTO method for model parameter identification based on improved grey wolf optimizer, honey badger algorithm, and gorilla troops optimizer," Energy, Elsevier, vol. 296(C).
    • Handle: RePEc:eee:energy:v:296:y:2024:i:c:s0360544224009368
    DOI: 10.1016/j.energy.2024.131163
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224009368
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.131163?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Song, Zhe & Cao, Sunliang & Yang, Hongxing, 2023. "Assessment of solar radiation resource and photovoltaic power potential across China based on optimized interpretable machine learning model and GIS-based approaches," Applied Energy, Elsevier, vol. 339(C).
    2. Ridha, Hussein Mohammed & Hizam, Hashim & Gomes, Chandima & Heidari, Ali Asghar & Chen, Huiling & Ahmadipour, Masoud & Muhsen, Dhiaa Halboot & Alghrairi, Mokhalad, 2021. "Parameters extraction of three diode photovoltaic models using boosted LSHADE algorithm and Newton Raphson method," Energy, Elsevier, vol. 224(C).
    3. Ahmed Ginidi & Sherif M. Ghoneim & Abdallah Elsayed & Ragab El-Sehiemy & Abdullah Shaheen & Attia El-Fergany, 2021. "Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    4. Fares, Dalila & Fathi, Mohamed & Mekhilef, Saad, 2022. "Performance evaluation of metaheuristic techniques for optimal sizing of a stand-alone hybrid PV/wind/battery system," Applied Energy, Elsevier, vol. 305(C).
    5. 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).
    6. Arabshahi, M.R. & Torkaman, H. & Keyhani, A., 2020. "A method for hybrid extraction of single-diode model parameters of photovoltaics," Renewable Energy, Elsevier, vol. 158(C), pages 236-252.
    7. Yin, Chen & Mao, Shuhua, 2023. "Fractional multivariate grey Bernoulli model combined with improved grey wolf algorithm: Application in short-term power load forecasting," Energy, Elsevier, vol. 269(C).
    8. Nassef, Ahmed M. & Houssein, Essam H. & Helmy, Bahaa El-din & Rezk, Hegazy, 2022. "Modified honey badger algorithm based global MPPT for triple-junction solar photovoltaic system under partial shading condition and global optimization," Energy, Elsevier, vol. 254(PA).
    9. Fan, Yi & Wang, Pengjun & Heidari, Ali Asghar & Chen, Huiling & HamzaTurabieh, & Mafarja, Majdi, 2022. "Random reselection particle swarm optimization for optimal design of solar photovoltaic modules," Energy, Elsevier, vol. 239(PA).
    10. Mukhopadhyay, Bineeta & Das, Debapriya, 2021. "Optimal multi-objective expansion planning of a droop-regulated islanded microgrid," Energy, Elsevier, vol. 218(C).
    11. Thitiphat Klinsuwan & Wachiraphong Ratiphaphongthon & Rabian Wangkeeree & Rattanaporn Wangkeeree & Chatchai Sirisamphanwong, 2023. "Evaluation of Machine Learning Algorithms for Supervised Anomaly Detection and Comparison between Static and Dynamic Thresholds in Photovoltaic Systems," Energies, MDPI, vol. 16(4), pages 1-22, February.
    12. Seera, Manjeevan & Tan, Choo Jun & Chong, Kok-Keong & Lim, Chee Peng, 2021. "Performance analyses of various commercial photovoltaic modules based on local spectral irradiances in Malaysia using genetic algorithm," Energy, Elsevier, vol. 223(C).
    13. Muhammad Ali Mughal & Qishuang Ma & Chunyan Xiao, 2017. "Photovoltaic Cell Parameter Estimation Using Hybrid Particle Swarm Optimization and Simulated Annealing," Energies, MDPI, vol. 10(8), pages 1-14, August.
    14. Sammy J. Martínez-Deusa & Carlos A. Gómez-García & Jaime Velasco-Medina, 2023. "A Platform for Outdoor Real-Time Characterization of Photovoltaic Technologies," Energies, MDPI, vol. 16(6), pages 1-16, March.
    Full references (including those not matched with items on IDEAS)

    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. Papul Changmai & Sunil Deka & Shashank Kumar & Thanikanti Sudhakar Babu & Belqasem Aljafari & Benedetto Nastasi, 2022. "A Critical Review on the Estimation Techniques of the Solar PV Cell’s Unknown Parameters," Energies, MDPI, vol. 15(19), pages 1-20, September.
    2. Liu, Yun & Heidari, Ali Asghar & Ye, Xiaojia & Liang, Guoxi & Chen, Huiling & He, Caitou, 2021. "Boosting slime mould algorithm for parameter identification of photovoltaic models," Energy, Elsevier, vol. 234(C).
    3. Ridha, Hussein Mohammed & Hizam, Hashim & Mirjalili, Seyedali & Othman, Mohammad Lutfi & Ya'acob, Mohammad Effendy & Ahmadipour, Masoud, 2022. "Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    4. El-Dabah, Mahmoud A. & El-Sehiemy, Ragab A. & Hasanien, Hany M. & Saad, Bahaa, 2023. "Photovoltaic model parameters identification using Northern Goshawk Optimization algorithm," Energy, Elsevier, vol. 262(PB).
    5. Long, Wen & Jiao, Jianjun & Liang, Ximing & Xu, Ming & Tang, Mingzhu & Cai, Shaohong, 2022. "Parameters estimation of photovoltaic models using a novel hybrid seagull optimization algorithm," Energy, Elsevier, vol. 249(C).
    6. Shaheen, Abdullah M. & Ginidi, Ahmed R. & El-Sehiemy, Ragab A. & El-Fergany, Attia & Elsayed, Abdallah M., 2023. "Optimal parameters extraction of photovoltaic triple diode model using an enhanced artificial gorilla troops optimizer," Energy, Elsevier, vol. 283(C).
    7. Hossam Hassan Ali & Mohamed Ebeed & Ahmed Fathy & Francisco Jurado & Thanikanti Sudhakar Babu & Alaa A. Mahmoud, 2023. "A New Hybrid Multi-Population GTO-BWO Approach for Parameter Estimation of Photovoltaic Cells and Modules," Sustainability, MDPI, vol. 15(14), pages 1-33, July.
    8. Mohd Bilal & Pitshou N. Bokoro & Gulshan Sharma & Giovanni Pau, 2024. "A Cost-Effective Energy Management Approach for On-Grid Charging of Plug-in Electric Vehicles Integrated with Hybrid Renewable Energy Sources," Energies, MDPI, vol. 17(16), pages 1-35, August.
    9. Ashraf K. Abdelaal & Elshahat F. Mohamed & Attia A. El-Fergany, 2022. "Optimal Scheduling of Hybrid Sustainable Energy Microgrid: A Case Study for a Resort in Sokhna, Egypt," Sustainability, MDPI, vol. 14(19), pages 1-13, October.
    10. Daxini, Rajiv & Wu, Yupeng, 2024. "Review of methods to account for the solar spectral influence on photovoltaic device performance," Energy, Elsevier, vol. 286(C).
    11. Zhou, Jianguo & Xu, Zhongtian, 2023. "Optimal sizing design and integrated cost-benefit assessment of stand-alone microgrid system with different energy storage employing chameleon swarm algorithm: A rural case in Northeast China," Renewable Energy, Elsevier, vol. 202(C), pages 1110-1137.
    12. Du, Hua & Han, Qi & de Vries, Bauke & Sun, Jun, 2024. "Community solar PV adoption in residential apartment buildings: A case study on influencing factors and incentive measures in Wuhan," Applied Energy, Elsevier, vol. 354(PA).
    13. Khasanzoda, Nasrullo & Safaraliev, Murodbek & Zicmane, Inga & Beryozkina, Svetlana & Rahimov, Jamshed & Ahyoev, Javod, 2022. "Use of smart grid based wind resources in isolated power systems," Energy, Elsevier, vol. 253(C).
    14. Manish Kumar Singla & Jyoti Gupta & Mohammed H. Alsharif & Abu Jahid & Khalid Yahya, 2023. "Sustainable Development of a Direct Methanol Fuel Cell Using the Enhanced LSHADE Algorithm and Newton Raphson Method," Sustainability, MDPI, vol. 16(1), pages 1-16, December.
    15. Xuliang Tang & Heng Wan & Weiwen Wang & Mengxu Gu & Linfeng Wang & Linfeng Gan, 2023. "Lithium-Ion Battery Remaining Useful Life Prediction Based on Hybrid Model," Sustainability, MDPI, vol. 15(7), pages 1-18, April.
    16. Jacek Kusznier, 2023. "Influence of Environmental Factors on the Intelligent Management of Photovoltaic and Wind Sections in a Hybrid Power Plant," Energies, MDPI, vol. 16(4), pages 1-15, February.
    17. Jayashree Piri & Puspanjali Mohapatra & Biswaranjan Acharya & Farhad Soleimanian Gharehchopogh & Vassilis C. Gerogiannis & Andreas Kanavos & Stella Manika, 2022. "Feature Selection Using Artificial Gorilla Troop Optimization for Biomedical Data: A Case Analysis with COVID-19 Data," Mathematics, MDPI, vol. 10(15), pages 1-31, August.
    18. Xinghua Liu & Siwei Qiao & Zhiwei Liu, 2023. "A Survey on Load Frequency Control of Multi-Area Power Systems: Recent Challenges and Strategies," Energies, MDPI, vol. 16(5), pages 1-22, February.
    19. Davoudkhani, Iraj Faraji & Dejamkhooy, Abdolmajid & Nowdeh, Saber Arabi, 2023. "A novel cloud-based framework for optimal design of stand-alone hybrid renewable energy system considering uncertainty and battery aging," Applied Energy, Elsevier, vol. 344(C).
    20. Muhyaddin Rawa & Abdullah Abusorrah & Yusuf Al-Turki & Martin Calasan & Mihailo Micev & Ziad M. Ali & Saad Mekhilef & Hussain Bassi & Hatem Sindi & Shady H. E. Abdel Aleem, 2022. "Estimation of Parameters of Different Equivalent Circuit Models of Solar Cells and Various Photovoltaic Modules Using Hybrid Variants of Honey Badger Algorithm and Artificial Gorilla Troops Optimizer," Mathematics, MDPI, vol. 10(7), pages 1-31, March.

    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:eee:energy:v:296:y:2024:i:c:s0360544224009368. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.