Forecasting Renewable Power Generation by Employing a Probabilistic Accumulation Non-Homogeneous Grey Model

Peng Zhang (), Jinsong Hu (), Kelong Zheng, Wenqing Wu and Xin Ma
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Peng Zhang: School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, 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

Energies, 2025, vol. 18, issue 18, 1-33

Abstract: Accurately predicting annual renewable power generation is critical for advancing energy structure transformation, ensuring energy security, and fostering sustainable development. In this study, a probabilistic non-homogeneous grey model (PNGM) is proposed to address this forecasting challenge. Firstly, the proposed model is constructed by integrating a Probabilistic Accumulation Generation Operator with the classical non-homogeneous grey model. Secondly, the Whale Optimization Algorithm is utilized to tune the parameters of the operator, thereby enhancing the extraction of valid information required for modeling. Furthermore, the superiority of the new model in information extraction and predictive performance is validated using synthetic datasets. Finally, it is applied to forecast renewable power generation in the United States, Russia, and India. The result exhibits significantly superior performance compared to the comparative models. Additionally, this study provides projections of renewable power generation for the United States, Russia, and India from 2025 to 2030, and the uncertainty intervals of the predicted values are estimated using the Bootstrap method. These results can provide reliable decision support for energy sectors and policymakers.

Keywords: probabilistic accumulation generation operator; probabilistic non-homogeneous grey model; optimized grey model; forecasting renewable power generation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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