IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v174y2019icp1079-1090.html
   My bibliography  Save this article

Memetic reinforcement learning based maximum power point tracking design for PV systems under partial shading condition

Author

Listed:
  • Zhang, Xiaoshun
  • Li, Shengnan
  • He, Tingyi
  • Yang, Bo
  • Yu, Tao
  • Li, Haofei
  • Jiang, Lin
  • Sun, Liming

Abstract

Solar energy has attracted significant attentions around the globe, while one of its most crucial task is to harvest the maximum available solar power under different weather conditions, also known as maximum power point tracking (MPPT). This paper proposes a novel memetic reinforcement learning (MRL) based MPPT scheme for photovoltaic (PV) systems under partial shading condition (PSC). In order to enhance the searching ability of MRL, the memetic computing structure is incorporated into reinforcement learning (RL). In particular, a virtual population is used for the global information exchange between different agents, such that the learning rate can be dramatically accelerated. Besides, a RL based local search is designed in each memeplex, which can effectively improve the optimum quality. Comprehensive case studies are undertaken, such as start-up test, step change of solar irradiation, ramp change of solar irradiation and temperature, and field atmospheric data of Hong Kong. The PV system responses are then evaluated and compared to that of seven typical MPPT algorithms.

Suggested Citation

  • Zhang, Xiaoshun & Li, Shengnan & He, Tingyi & Yang, Bo & Yu, Tao & Li, Haofei & Jiang, Lin & Sun, Liming, 2019. "Memetic reinforcement learning based maximum power point tracking design for PV systems under partial shading condition," Energy, Elsevier, vol. 174(C), pages 1079-1090.
    • Handle: RePEc:eee:energy:v:174:y:2019:i:c:p:1079-1090
    DOI: 10.1016/j.energy.2019.03.053
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219304578
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.03.053?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. Daraban, Stefan & Petreus, Dorin & Morel, Cristina, 2014. "A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading," Energy, Elsevier, vol. 74(C), pages 374-388.
    2. Belhachat, Faiza & Larbes, Cherif, 2018. "A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 513-553.
    3. Chen, Jian & Yao, Wei & Zhang, Chuan-Ke & Ren, Yaxing & Jiang, Lin, 2019. "Design of robust MPPT controller for grid-connected PMSG-Based wind turbine via perturbation observation based nonlinear adaptive control," Renewable Energy, Elsevier, vol. 134(C), pages 478-495.
    4. Qi, Jun & Zhang, Youbing & Chen, Yi, 2014. "Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions," Renewable Energy, Elsevier, vol. 66(C), pages 337-345.
    5. Jately, V. & Arora, S., 2017. "Development of a dual-tracking technique for extracting maximum power from PV systems under rapidly changing environmental conditions," Energy, Elsevier, vol. 133(C), pages 557-571.
    6. Rezk, Hegazy & Fathy, Ahmed & Abdelaziz, Almoataz Y., 2017. "A comparison of different global MPPT techniques based on meta-heuristic algorithms for photovoltaic system subjected to partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 377-386.
    7. Kandemir, Ekrem & Cetin, Numan S. & Borekci, Selim, 2017. "A comprehensive overview of maximum power extraction methods for PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 93-112.
    8. Zhang, Xiaoshun & Bao, Tao & Yu, Tao & Yang, Bo & Han, Chuanjia, 2017. "Deep transfer Q-learning with virtual leader-follower for supply-demand Stackelberg game of smart grid," Energy, Elsevier, vol. 133(C), pages 348-365.
    9. Yang, Bo & Yu, Tao & Shu, Hongchun & Zhang, Yuming & Chen, Jian & Sang, Yiyan & Jiang, Lin, 2018. "Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine," Renewable Energy, Elsevier, vol. 119(C), pages 577-589.
    10. Liao, Shiwu & Yao, Wei & Han, Xingning & Wen, Jinyu & Cheng, Shijie, 2017. "Chronological operation simulation framework for regional power system under high penetration of renewable energy using meteorological data," Applied Energy, Elsevier, vol. 203(C), pages 816-828.
    11. Yang, Bo & Yu, Tao & Shu, Hongchun & Dong, Jun & Jiang, Lin, 2018. "Robust sliding-mode control of wind energy conversion systems for optimal power extraction via nonlinear perturbation observers," Applied Energy, Elsevier, vol. 210(C), pages 711-723.
    12. Ahmed, Jubaer & Salam, Zainal, 2014. "A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability," Applied Energy, Elsevier, vol. 119(C), pages 118-130.
    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. Li, Qingxiang & Zhu, Li & Sun, Yong & Lu, Lin & Yang, Yang, 2020. "Performance prediction of Building Integrated Photovoltaics under no-shading, shading and masking conditions using a multi-physics model," Energy, Elsevier, vol. 213(C).
    2. Noureddine Bouarroudj & Yehya Houam & Abdelhamid Djari & Vicente Feliu-Batlle & Abdelkader Lakhdari & Boualam Benlahbib, 2023. "A Linear Quadratic Integral Controller for PV-Module Voltage Regulation for the Purpose of Enhancing the Classical Incremental Conductance Algorithm," Energies, MDPI, vol. 16(11), pages 1-17, June.
    3. Zhang, Xiaoshun & Meng, Die & Cai, Jiahui & Zhang, Guiyuan & Yu, Tao & Pan, Feng & Yang, Yuyao, 2023. "A swarm based double Q-learning for optimal PV array reconfiguration with a coordinated control of hydrogen energy storage system," Energy, Elsevier, vol. 266(C).
    4. Hou, Guolian & Ke, Yin & Huang, Congzhi, 2021. "A flexible constant power generation scheme for photovoltaic system by error-based active disturbance rejection control and perturb & observe," Energy, Elsevier, vol. 237(C).
    5. Pei Ye, Song & Hua Liu, Yi & Chung Wang, Shun & Yu Pai, Hung, 2022. "A novel global maximum power point tracking algorithm based on Nelder-Mead simplex technique for complex partial shading conditions," Applied Energy, Elsevier, vol. 321(C).
    6. 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).
    7. Liu, Zhengguang & Guo, Zhiling & Chen, Qi & Song, Chenchen & Shang, Wenlong & Yuan, Meng & Zhang, Haoran, 2023. "A review of data-driven smart building-integrated photovoltaic systems: Challenges and objectives," Energy, Elsevier, vol. 263(PE).
    8. Galal Al-Muthanna & Shuhua Fang & Ibrahim AL-Wesabi & Khaled Ameur & Hossam Kotb & Kareem M. AboRas & Hassan Z. Al Garni & Abdullahi Abubakar Mas’ud, 2023. "A High Speed MPPT Control Utilizing a Hybrid PSO-PID Controller under Partially Shaded Photovoltaic Battery Chargers," Sustainability, MDPI, vol. 15(4), pages 1-28, February.
    9. Perera, A.T.D. & Kamalaruban, Parameswaran, 2021. "Applications of reinforcement learning in energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    10. Mirza, Adeel Feroz & Mansoor, Majad & Zhan, Keyu & Ling, Qiang, 2021. "High-efficiency swarm intelligent maximum power point tracking control techniques for varying temperature and irradiance," Energy, Elsevier, vol. 228(C).

    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. Rezk, Hegazy & AL-Oran, Mazen & Gomaa, Mohamed R. & Tolba, Mohamed A. & Fathy, Ahmed & Abdelkareem, Mohammad Ali & Olabi, A.G. & El-Sayed, Abou Hashema M., 2019. "A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    2. Yang, Bo & Wang, Jingbo & Sang, Yiyan & Yu, Lei & Shu, Hongchun & Li, Shengnan & He, Tingyi & Yang, Lei & Zhang, Xiaoshun & Yu, Tao, 2019. "Applications of supercapacitor energy storage systems in microgrid with distributed generators via passive fractional-order sliding-mode control," Energy, Elsevier, vol. 187(C).
    3. 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).
    4. Yang, Bo & Wang, Junting & Zhang, Xiaoshun & Yu, Lei & Shu, Hongchun & Yu, Tao & Sun, Liming, 2020. "Control of SMES systems in distribution networks with renewable energy integration: A perturbation estimation approach," Energy, Elsevier, vol. 202(C).
    5. Yang, Bo & Zhu, Tianjiao & Zhang, Xiaoshun & Wang, Jingbo & Shu, Hongchun & Li, Shengnan & He, Tingyi & Yang, Lei & Yu, Tao, 2020. "Design and implementation of Battery/SMES hybrid energy storage systems used in electric vehicles: A nonlinear robust fractional-order control approach," Energy, Elsevier, vol. 191(C).
    6. Zhang, Xiaoshun & Tan, Tian & Yang, Bo & Wang, Jingbo & Li, Shengnan & He, Tingyi & Yang, Lei & Yu, Tao & Sun, Liming, 2020. "Greedy search based data-driven algorithm of centralized thermoelectric generation system under non-uniform temperature distribution," Applied Energy, Elsevier, vol. 260(C).
    7. Ramli, Makbul A.M. & Twaha, Ssennoga & Ishaque, Kashif & Al-Turki, Yusuf A., 2017. "A review on maximum power point tracking for photovoltaic systems with and without shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 144-159.
    8. Yang, Bo & Wu, Shaocong & Li, Qiang & Yan, Yingjie & Li, Danyang & Luo, Enbo & Zeng, Chunyuan & Chen, Yijun & Guo, Zhengxun & Shu, Hongchun & Li, Zilin & Wang, Jingbo, 2023. "Jellyfish search algorithm based optimal thermoelectric generation array reconfiguration under non-uniform temperature distribution condition," Renewable Energy, Elsevier, vol. 204(C), pages 197-217.
    9. Huazhen Cao & Chong Gao & Xuan He & Yang Li & Tao Yu, 2020. "Multi-Agent Cooperation Based Reduced-Dimension Q(λ) Learning for Optimal Carbon-Energy Combined-Flow," Energies, MDPI, vol. 13(18), pages 1-22, September.
    10. Fahd A. Alturki & Abdullrahman A. Al-Shamma’a & Hassan M. H. Farh, 2020. "Simulations and dSPACE Real-Time Implementation of Photovoltaic Global Maximum Power Extraction under Partial Shading," Sustainability, MDPI, vol. 12(9), pages 1-16, May.
    11. Pulin Cao & Hongchun Shu & Bo Yang & Na An & Dalin Qiu & Weiye Teng & Jun Dong, 2018. "Voltage Distribution–Based Fault Location for Half-Wavelength Transmission Line with Large-Scale Wind Power Integration in China," Energies, MDPI, vol. 11(3), pages 1-22, March.
    12. Yan, Cai & Yao, Wei & Wen, Jianfeng & Fang, Jiakun & Ai, Xiaomeng & Wen, Jinyu, 2020. "Optimal design of probabilistic robust damping controllers to suppress multiband oscillations of power systems integrated with wind farm," Renewable Energy, Elsevier, vol. 158(C), pages 75-90.
    13. Chen, Jian & Yao, Wei & Zhang, Chuan-Ke & Ren, Yaxing & Jiang, Lin, 2019. "Design of robust MPPT controller for grid-connected PMSG-Based wind turbine via perturbation observation based nonlinear adaptive control," Renewable Energy, Elsevier, vol. 134(C), pages 478-495.
    14. Waleed Al Abri & Rashid Al Abri & Hassan Yousef & Amer Al-Hinai, 2021. "A Simple Method for Detecting Partial Shading in PV Systems," Energies, MDPI, vol. 14(16), pages 1-12, August.
    15. Hongchun Shu & Na An & Bo Yang & Yue Dai & Yu Guo, 2020. "Single Pole-to-Ground Fault Analysis of MMC-HVDC Transmission Lines Based on Capacitive Fuzzy Identification Algorithm," Energies, MDPI, vol. 13(2), pages 1-18, January.
    16. Guo, Lei & Meng, Zhuo & Sun, Yize & Wang, Libiao, 2018. "A modified cat swarm optimization based maximum power point tracking method for photovoltaic system under partially shaded condition," Energy, Elsevier, vol. 144(C), pages 501-514.
    17. Yang, Chao & Yao, Wei & Fang, Jiakun & Ai, Xiaomeng & Chen, Zhe & Wen, Jinyu & He, Haibo, 2019. "Dynamic event-triggered robust secondary frequency control for islanded AC microgrid," Applied Energy, Elsevier, vol. 242(C), pages 821-836.
    18. Hongchun Shu & Yiming Han & Ran Huang & Yutao Tang & Pulin Cao & Bo Yang & Yu Zhang, 2020. "Fault Model and Travelling Wave Matching Based Single Terminal Fault Location Algorithm for T-Connection Transmission Line: A Yunnan Power Grid Study," Energies, MDPI, vol. 13(6), pages 1-22, March.
    19. Paula Andrea Ortiz Valencia & Carlos Andres Ramos-Paja, 2015. "Sliding-Mode Controller for Maximum Power Point Tracking in Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 8(11), pages 1-25, November.
    20. Soudan, Bassel, 2019. "Community-scale baseload generation from marine energy," 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:eee:energy:v:174:y:2019:i:c:p:1079-1090. 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.