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

Yong Wang, Rui Yang, Lang Sun, Zhongsen Yang, Flavian Emmanuel Sapnken and Hong-Li Li

Renewable Energy, 2025, vol. 245, issue C

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.

Keywords: Fractional order; Structural self-adaptation; Renewable energy generation; Particle swarm optimization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:245:y:2025:i:c:s0960148125004471

DOI: 10.1016/j.renene.2025.122785

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