The development trend of China's natural gas consumption: A forecasting viewpoint based on grey forecasting model

In the context of global emission reduction, as a type of clean and eco-friendly energy, natural gas has attracted wide attention. Accurate prediction of natural gas consumption can provide reference for relevant departments to formulate the corresponding development plans and strategies. At present, there are many forecasting tools for processing and analysing natural gas consumption, but most of them have the disadvantages of complex modelling or low precision. In order to solve this problem, inspired by the polynomial regression prediction model and the discrete grey prediction model, a novel polynomial discrete grey prediction model with fractional order accumulation (abbreviated as FPDGM(1,1) model) is established in this paper. In order to find the optimal parameters of the FPDGM(1,1) model, three most popular intelligent algorithms are used to solve the parameters of the model, and then the optimal parameters from the three intelligent algorithms are selected in this paper. In addition, the advantages of the FPDGM(1,1) model over other four forecasting models are confirmed through two parts in this paper. First, the natural gas consumptions of four municipalities in China are used as cases to verify the effectiveness of the FPDGM(1,1) model in this paper. Subsequently, the FPDGM(1,1) model and several kinds of frequently used forecasting models are applied to analyse and predict China's natural gas consumption, and the FPDGM(1,1) model is used to predict China's natural gas consumption in the next 5 years. The results of these two parts indicate that the FPDGM(1,1) model shows the best predictive performance in all cases. Lastly, based on the predicted results of the FPDGM(1,1) model, some reasonable suggestions are put forward for China's natural gas development plan. (C) 2021 Published by Elsevier Ltd.

Automated summary

This research introduces a novel FPDGM(1,1) model for predicting natural gas consumption, which is validated through cases in various cities in China, demonstrating its superiority over other models. Ultimately, suggestions for China's natural gas development plan are proposed based on the predictive results of the model.