IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v312y2024ics0360544224034005.html
   My bibliography  Save this article

A novel structural adaptive Caputo fractional order derivative multivariate grey model and its application in China's energy production and consumption prediction

Author

Listed:
  • Wang, Yong
  • Yang, Zhongsen
  • Luo, Yongxian
  • Yang, Rui
  • Sun, Lang
  • Sapnken, Flavian Emmanuel
  • Narayanan, Govindasami

Abstract

With the deepening of economic globalization and the intensification of global warming, all countries are faced with the challenges of low-carbon transition and continuous growth of energy demand. Therefore, precise forecasting of future energy development patterns is critical for our government to optimize its energy structure. Based on this, by introducing Caputo fractional order derivative, power exponential term, linear correction term, and stochastic perturbation term, a novel structural adaptive nonlinear multivariate grey prediction model constructed using Caputo fractional order derivatives is presented. To increase the adaptability of the model, the Grey Wolf Optimization (GWO) technique is used to optimize the model's adaptive parameters. To evaluate the model's validity, seven current grey prediction models are compared to the CFNGMC(p, n) model using three real-world examples of electricity production, energy processing and conversion efficiency, and energy consumption per capita. Experimental findings suggest that the CFNGMC(p, n) is highly predictive and adaptable. Furthermore, Monte Carlo simulation and probability density analysis are used to evaluate the robustness of the CFNGMC(p, n), further confirming its superiority. It demonstrates that the proposed model is an effective way to anticipate energy data in China.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:312:y:2024:i:c:s0360544224034005
    DOI: 10.1016/j.energy.2024.133622
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224034005
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.133622?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. Ozcan, Burcu & Danish, & Temiz, Mehmet, 2022. "An empirical investigation between renewable energy consumption, globalization and human capital: A dynamic auto-regressive distributive lag simulation," Renewable Energy, Elsevier, vol. 193(C), pages 195-203.
    2. Elamin, Niematallah & Fukushige, Mototsugu, 2018. "Modeling and forecasting hourly electricity demand by SARIMAX with interactions," Energy, Elsevier, vol. 165(PB), pages 257-268.
    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. Shahbaz, Muhammad & Loganathan, Nanthakumar & Zeshan, Mohammad & Zaman, Khalid, 2015. "Does renewable energy consumption add in economic growth? An application of auto-regressive distributed lag model in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 576-585.
    5. 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).
    6. 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).
    7. 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).
    8. Xu, Lei & Hou, Lei & Zhu, Zhenyu & Li, Yu & Liu, Jiaquan & Lei, Ting & Wu, Xingguang, 2021. "Mid-term prediction of electrical energy consumption for crude oil pipelines using a hybrid algorithm of support vector machine and genetic algorithm," Energy, Elsevier, vol. 222(C).
    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. Wang, Yanan & Yin, Shiwen & Fang, Xiaoli & Chen, Wei, 2022. "Interaction of economic agglomeration, energy conservation and emission reduction: Evidence from three major urban agglomerations in China," Energy, Elsevier, vol. 241(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. 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.
    13. 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).
    14. Zhang, Meng & Guo, Huan & Sun, Ming & Liu, Sifeng & Forrest, Jeffrey, 2022. "A novel flexible grey multivariable model and its application in forecasting energy consumption in China," Energy, Elsevier, vol. 239(PE).
    15. Jiang, Junyu & Yu, Yuanbin & Min, Haitao & Cao, Qiming & Sun, Weiyi & Zhang, Zhaopu & Luo, Chunqi, 2023. "Trip-level energy consumption prediction model for electric bus combining Markov-based speed profile generation and Gaussian processing regression," Energy, Elsevier, vol. 263(PD).
    16. Lu, Hongfang & Cheng, Feifei & Ma, Xin & Hu, Gang, 2020. "Short-term prediction of building energy consumption employing an improved extreme gradient boosting model: A case study of an intake tower," Energy, Elsevier, vol. 203(C).
    17. 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).
    18. Li, Pengshun & Zhang, Yuhang & Zhang, Yi & Zhang, Yi & Zhang, Kai, 2021. "Prediction of electric bus energy consumption with stochastic speed profile generation modelling and data driven method based on real-world big data," Applied Energy, Elsevier, vol. 298(C).
    19. Zou, Tong & Guo, Pibin & Li, Fanrong & Wu, Qinglong, 2024. "Research topic identification and trend prediction of China's energy policy: A combined LDA-ARIMA approach," Renewable Energy, Elsevier, vol. 220(C).
    20. 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.
    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. 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).
    2. 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).
    3. 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).
    4. 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).

    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 & 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).
    2. 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).
    3. 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).
    4. 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).
    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 & 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).
    7. 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).
    8. 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).
    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 & 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).
    11. 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).
    12. 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).
    13. Duan, Tianyao & Guo, Huan & Qi, Xiao & Sun, Ming & Forrest, Jeffrey, 2024. "A novel information enhanced Grey Lotka–Volterra model driven by system mechanism and data for energy forecasting of WEET project in China," Energy, Elsevier, vol. 304(C).
    14. 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.
    15. Ding, Yuanping & Dang, Yaoguo, 2023. "Forecasting renewable energy generation with a novel flexible nonlinear multivariable discrete grey prediction model," Energy, Elsevier, vol. 277(C).
    16. 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.
    17. 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).
    18. 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).
    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. 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).

    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:energy:v:312:y:2024:i:c:s0360544224034005. 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.