Abstract
Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonhomogeneous grey model with fractional-order accumulation is introduced along with discussions between other existing grey models. A random search optimization scheme is then introduced to optimize the nonlinear parameter of the grey model. And the complete forecasting scheme is built based on the rolling mechanism. The case study is executed based on the updated data set of natural gas consumption of the power sector in the United States. The comparison of results is analyzed from different step sizes, different grey system models, and benchmark models. They all show that the proposed method has significant advantages over the other existing methods, which indicates the proposed method has high potential in short-term forecasting for natural gas consumption of the power sector in United States.
Highlights
Electricity facilitates the development of the national economy and promotes the progress of the industrial society in the present age
The forecasting results of the first three steps of the fractional nonhomogeneous grey model (FNGM) after random search and tuning parameters are used for comparative analysis, as shown in Table 2. e MAE, MAPE, and RMSE of the one-step forecasting are 24.45, 2.58%, and 35.26, and all of them are smaller than other step forecasting
In order to further evaluate the accuracy of the rolling forecast of the FNGM with random search, we selected the remaining 11 models mentioned in Section 3 for comparative analysis
Summary
Electricity facilitates the development of the national economy and promotes the progress of the industrial society in the present age. According to the literature study, this paper uses the random search to optimize the fractional nonlinear parameters in the nonhomogeneous grey model and designs an application of natural gas consumption in the US power sector which uses the rolling forecast mechanism to forecast the results.
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