A novel seasonal adaptive grey model with the data-restacking technique for monthly renewable energy consumption forecasting

作者：

Highlights：

• A novel structure-adaptive grey model is initially designed.

• The proposed model can grasp the nonlinear and seasonal patterns.

• This method exhibits generalizability in predicting renewable energy generation.

• The proposed technique strikingly outperforms many prevalent benchmarks.

摘要

•A novel structure-adaptive grey model is initially designed.•The proposed model can grasp the nonlinear and seasonal patterns.•This method exhibits generalizability in predicting renewable energy generation.•The proposed technique strikingly outperforms many prevalent benchmarks.

论文关键词：Seasonal adaptive grey model,Data-restacking technique,Particle swarm optimization,Renewable energy consumption

论文评审过程：Received 2 August 2021, Revised 15 May 2022, Accepted 6 July 2022, Available online 9 July 2022, Version of Record 20 July 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118115