IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v245y2025ics0960148125004471.html

A novel time-lag discrete grey Euler model and its application in renewable energy generation prediction

Author

Listed:
  • Wang, Yong
  • Yang, Rui
  • Sun, Lang
  • Yang, Zhongsen
  • Sapnken, Flavian Emmanuel
  • Li, Hong-Li

Abstract

Accurate prediction of renewable energy development plays an important role in the macro-control of the energy system. Therefore, in this paper, a novel discrete grey Euler model ATDGEM(1,1) is developed to forecast renewable energy generation in some regions. The novel model is improved in both the accumulation method and the model structure. Based on the integer-order accumulation method of the grey Euler model, a new fractional order cumulative generation operator is proposed, which can differentially utilize the raw data information. In particular, for the time lag effect that exists between economic development and energy growth, a time-lag structure with a new form is proposed, which improves the model's ability to characterize the time lag. In addition, this paper compares the different optimization algorithms as well as the grey model respectively by setting up numerical experiments, which not only selects the optimal algorithm for parameter optimization (PSO), but also verifies the predictive effectiveness of the novel model. Finally, the novel model is uesd to forecast the development trend of the renewable energy generation data, and the reliable prediction result is obtained. Besides, some analyses and recommendations are made based on the results. This study provides a reference for energy policy makers or related departments and enterprises.

Suggested Citation

  • Wang, Yong & Yang, Rui & Sun, Lang & Yang, Zhongsen & Sapnken, Flavian Emmanuel & Li, Hong-Li, 2025. "A novel time-lag discrete grey Euler model and its application in renewable energy generation prediction," Renewable Energy, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:renene:v:245:y:2025:i:c:s0960148125004471
    DOI: 10.1016/j.renene.2025.122785
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148125004471
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2025.122785?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Yong & Yang, Zhongsen & Luo, Yongxian & Yang, Rui & Sun, Lang & Sapnken, Flavian Emmanuel & Narayanan, Govindasami, 2024. "A novel structural adaptive Caputo fractional order derivative multivariate grey model and its application in China's energy production and consumption prediction," Energy, Elsevier, vol. 312(C).
    2. Wang, Yong & Sun, Lang & Yang, Rui & He, Wenao & Tang, Yanbing & Zhang, Zejia & Wang, Yunhui & Sapnken, Flavian Emmanuel, 2023. "A novel structure adaptive fractional derivative grey model and its application in energy consumption prediction," Energy, Elsevier, vol. 282(C).
    3. Wang, Yong & He, Xinbo & Zhou, Ying & Luo, Yongxian & Tang, Yanbing & Narayanan, Govindasami, 2024. "A novel structure adaptive grey seasonal model with data reorganization and its application in solar photovoltaic power generation prediction," Energy, Elsevier, vol. 302(C).
    4. Wu, Wenqing & Ma, Xin & Zeng, Bo & Wang, Yong & Cai, Wei, 2018. "Application of the novel fractional grey model FAGMO(1,1,k) to predict China's nuclear energy consumption," Energy, Elsevier, vol. 165(PB), pages 223-234.
    5. Wang, Yong & Yang, Rui & Zhang, Juan & Sun, Lang & Xiao, Wenlian & Saxena, Akash, 2024. "A novel structure adaptive discrete grey Bernoulli prediction model and its applications in energy consumption and production," Energy, Elsevier, vol. 291(C).
    6. Wang, Yong & Yang, Zhongsen & Zhou, Ying & Liu, Hao & Yang, Rui & Sun, Lang & Sapnken, Flavian Emmanuel & Narayanan, Govindasami, 2025. "A novel structure adaptive new information priority grey Bernoulli model and its application in China's renewable energy production," Renewable Energy, Elsevier, vol. 239(C).
    7. Wang, Yong & Yang, Zhongsen & Wang, Li & Ma, Xin & Wu, Wenqing & Ye, Lingling & Zhou, Ying & Luo, Yongxian, 2022. "Forecasting China's energy production and consumption based on a novel structural adaptive Caputo fractional grey prediction model," Energy, Elsevier, vol. 259(C).
    8. Wu, Wenqing & Ma, Xin & Zeng, Bo & Wang, Yong & Cai, Wei, 2019. "Forecasting short-term renewable energy consumption of China using a novel fractional nonlinear grey Bernoulli model," Renewable Energy, Elsevier, vol. 140(C), pages 70-87.
    9. Wang, Yong & Yang, Zhongsen & Ye, Lingling & Wang, Li & Zhou, Ying & Luo, Yongxian, 2023. "A novel self-adaptive fractional grey Euler model with dynamic accumulation order and its application in energy production prediction of China," Energy, Elsevier, vol. 265(C).
    10. He, Xinbo & Wang, Yong & Zhang, Yuyang & Ma, Xin & Wu, Wenqing & Zhang, Lei, 2022. "A novel structure adaptive new information priority discrete grey prediction model and its application in renewable energy generation forecasting," Applied Energy, Elsevier, vol. 325(C).
    11. Wang, Yong & Chi, Pei & Nie, Rui & Ma, Xin & Wu, Wenqing & Guo, Binghong, 2022. "Self-adaptive discrete grey model based on a novel fractional order reverse accumulation sequence and its application in forecasting clean energy power generation in China," Energy, Elsevier, vol. 253(C).
    12. Yang, Zhongsen & Wang, Yong & Zhou, Ying & Wang, Li & Ye, Lingling & Luo, Yongxian, 2023. "Forecasting China's electricity generation using a novel structural adaptive discrete grey Bernoulli model," Energy, Elsevier, vol. 278(C).
    13. Ding, Song & Hu, Jiaqi & Lin, Qianqian, 2023. "Accurate forecasts and comparative analysis of Chinese CO2 emissions using a superior time-delay grey model," Energy Economics, Elsevier, vol. 126(C).
    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. Peng Zhang & Jinsong Hu & Kelong Zheng & Wenqing Wu & Xin Ma, 2025. "Forecasting Renewable Power Generation by Employing a Probabilistic Accumulation Non-Homogeneous Grey Model," Energies, MDPI, vol. 18(18), pages 1-33, September.
    2. Lv, Yichen & Gao, Mingyun & Xiao, Xinping, 2026. "Unbiased forecasting of seasonal wind power generation based on a novel seasonal multivariable grey model," Renewable Energy, Elsevier, vol. 258(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. Wang, Yong & Wang, Yunhui & Zhang, Zejia & Sun, Lang & Yang, Rui & Sapnken, Flavian Emmanuel & Xiao, Wenlian, 2025. "A novel fractional-order kernel regularized non-homogeneous grey Riccati model and its application in oil reserves prediction," Energy, Elsevier, vol. 316(C).
    2. Wang, Yong & Sun, Lang & Yang, Rui & Yang, Zhongsen & Sapnken, Flavian Emmanuel & Yang, Mou, 2025. "A novel variable weight accumulation multiple power-law grey Bernoulli model and its application in China's electricity supply and consumption prediction," Energy, Elsevier, vol. 317(C).
    3. Wang, Yong & Yang, Zhongsen & Zhou, Ying & Liu, Hao & Yang, Rui & Sun, Lang & Sapnken, Flavian Emmanuel & Narayanan, Govindasami, 2025. "A novel structure adaptive new information priority grey Bernoulli model and its application in China's renewable energy production," Renewable Energy, Elsevier, vol. 239(C).
    4. Wang, Yong & Yang, Zhongsen & Luo, Yongxian & Yang, Rui & Sun, Lang & Sapnken, Flavian Emmanuel & Narayanan, Govindasami, 2024. "A novel structural adaptive Caputo fractional order derivative multivariate grey model and its application in China's energy production and consumption prediction," Energy, Elsevier, vol. 312(C).
    5. Yang, Zhongsen & Wang, Yong & Fan, Neng & Wen, Shixiong & Kuang, Wenyu & Yang, Mou & Sapnken, Flavian Emmanuel & Narayanan, Govindasami & Li, Hong-Li, 2025. "A novel fractional order grey Euler model and its application in clean energy prediction," Energy, Elsevier, vol. 322(C).
    6. Wang, Yong & Wen, Shixiong & Kuang, Wenyu & Fan, Neng & Yang, Zhongsen & Yang, Mou & Li, Hong-Li & Sapnken, Flavian Emmanuel & Narayanan, Govindasami, 2025. "A novel structure adaptive discrete grey Riccati model and its application in energy production and consumption," Energy, Elsevier, vol. 333(C).
    7. Wang, Yong & Yang, Zhongsen & Fan, Neng & Wen, Shixiong & Kuang, Wenyu & Yang, Mou & Li, Hong-Li & Narayanan, Govindasami & Sapnken, Flavian Emmanuel, 2025. "A novel fractional nonlinear discrete grey model with kernel-markov adaptation for clean energy forecasting," Energy, Elsevier, vol. 323(C).
    8. Wang, Yong & He, Xinbo & Zhou, Ying & Luo, Yongxian & Tang, Yanbing & Narayanan, Govindasami, 2024. "A novel structure adaptive grey seasonal model with data reorganization and its application in solar photovoltaic power generation prediction," Energy, Elsevier, vol. 302(C).
    9. Wang, Yong & Zhang, Zejia & Wang, Yunhui & Sun, Lang & Yang, Rui & He, Wenao & Sapnken, Flavian Emmanuel & Li, Hong-Li, 2025. "A novel time-varying parameters structural adaptive Hausdorff fractional discrete grey model and its application in renewable energy production and consumption prediction," Energy, Elsevier, vol. 318(C).
    10. Wang, Yong & Yang, Zhongsen & Ye, Lingling & Wang, Li & Zhou, Ying & Luo, Yongxian, 2023. "A novel self-adaptive fractional grey Euler model with dynamic accumulation order and its application in energy production prediction of China," Energy, Elsevier, vol. 265(C).
    11. Wang, Yong & Sun, Lang & Yang, Rui & He, Wenao & Tang, Yanbing & Zhang, Zejia & Wang, Yunhui & Sapnken, Flavian Emmanuel, 2023. "A novel structure adaptive fractional derivative grey model and its application in energy consumption prediction," Energy, Elsevier, vol. 282(C).
    12. Peng Zhang & Jinsong Hu & Kelong Zheng & Wenqing Wu & Xin Ma, 2025. "Forecasting Renewable Power Generation by Employing a Probabilistic Accumulation Non-Homogeneous Grey Model," Energies, MDPI, vol. 18(18), pages 1-33, September.
    13. Yang, Zhongsen & Wang, Yong & Zhou, Ying & Wang, Li & Ye, Lingling & Luo, Yongxian, 2023. "Forecasting China's electricity generation using a novel structural adaptive discrete grey Bernoulli model," Energy, Elsevier, vol. 278(C).
    14. Wang, Yong & Fan, Neng & Wen, Shixiong & Kuang, Wenyu & Yang, Zhongsen & Xiao, Wenlian & Li, Hong-Li & Narayanan, Govindasami & Sapnken, Flavian Emmanuel, 2025. "A novel structural adaptive discrete grey Euler model and its application in clean energy production and consumption," Energy, Elsevier, vol. 323(C).
    15. Yu, Yue & Xiao, Xinping & Gao, Mingyun & Rao, Congjun, 2025. "Dynamic time-delay discrete grey model based on GOWA operator for renewable energy generation cost prediction," Renewable Energy, Elsevier, vol. 242(C).
    16. Li, Hui & Duan, Huiming & Song, Yuxin & Wang, Xingwu, 2025. "A novel conformable fractional logistic grey model and its application to natural gas and electricity consumption in China," Renewable Energy, Elsevier, vol. 243(C).
    17. Li, Xuemei & Li, Jiakai & Zhao, Yufeng & Zhou, Shiwei, 2025. "A novel discrete multivariable grey model with seasonal time-lag effect for clean energy generation forecasting," Energy, Elsevier, vol. 334(C).
    18. Zhenguo Xu & Wanli Xie & Caixia Liu, 2023. "An Optimized Fractional Nonlinear Grey System Model and Its Application in the Prediction of the Development Scale of Junior Secondary Schools in China," Sustainability, MDPI, vol. 15(4), pages 1-12, February.
    19. He, Xinbo & Wang, Yong & Zhang, Yuyang & Ma, Xin & Wu, Wenqing & Zhang, Lei, 2022. "A novel structure adaptive new information priority discrete grey prediction model and its application in renewable energy generation forecasting," Applied Energy, Elsevier, vol. 325(C).
    20. He, Jing & Mao, Shuhua & Kang, Yuxiao, 2023. "Augmented fractional accumulation grey model and its application: Class ratio and restore error perspectives," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 209(C), pages 220-247.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:renene:v:245:y:2025:i:c:s0960148125004471. 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/renewable-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.