Forecasting Global Solar Energy Consumption Using Conformable Fractional Incomplete Gamma Grey Model

Peng Zhang, Jinsong Hu (), Kelong Zheng, Wenqing Wu and Xin Ma
Additional contact information
Peng Zhang: College of Big Data and Artificial Intelligence, Chengdu Technological University, Chengdu 611730, China
Jinsong Hu: College of Big Data and Artificial Intelligence, Chengdu Technological University, Chengdu 611730, China
Kelong Zheng: Faculty of Science, Civil Aviation Flight University of China, Guanghan 618307, China
Wenqing Wu: Faculty of Science, Civil Aviation Flight University of China, Guanghan 618307, China
Xin Ma: School of Mathematics and Physics, Southwest University of Science and Technology, Mianyang 621010, China

Sustainability, 2025, vol. 17, issue 18, 1-23

Abstract: Solar energy has become the core driver of global energy transformation. To achieve a more accurate prediction of the global solar energy consumption, this study presents a novel conformable fractional incomplete gamma grey model (denoted as CFIGGM). In this new model, the conformable fractional-order accumulation operator is introduced to fully mine the information of small samples and reduce the dependence on data distribution. Meanwhile, the Whale Optimization Algorithm is also utilized to solve the optimal value of nonlinear parameters in the newly proposed model to enhance its prediction performance. Moreover, numerical experiments are carried out on five sequences to verify the performance of the new model. The experiments’ results show that the proposed model has better prediction performance than the comparative models. Then, the new model is applied to forecast the global solar energy consumption. The fitting MAPE of the newly proposed model is 0.07% on the training set, and the prediction MAPE is 0.78% on the test set. As an application, the trend in global solar energy consumption is predicted by using the proposed model. Its result shows that the global solar energy consumption is projected to maintain a strong growth momentum, but the growth rate will slow down in the future. The results can serve as strong supporting data for relevant departments and enterprises.

Keywords: conformable fractional accumulation; conformable fractional incomplete gamma grey model; energy consumption prediction; solar energy consumption (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/18/8256/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/18/8256/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:18:p:8256-:d:1749189

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().