Forecasting Study of Natural Gas Consumption by Combined Models Based on LASSO and WOA

Abstract

As the impact of the Russia-Ukraine war continues to expand, energy shortages appear in Europe. After Russia cut off the Nord Stream 1 pipeline that transported natural gas to Europe, most European countries experienced a natural gas crisis, severely affecting Germany. In order to effectively predict the consumption of natural gas, this paper combines the Least Absolute Shrinkage and Select Operator model with the Whale Optimization Algorithm, uses the NAR model to reconstruct the phase space of the original time series, and performs a 5-step forward forecast. Use the model to forecast a German monthly natural gas consumption dataset. Comparing the results of WOA-LASSO  with other five other WOA-based hybrid models and Cross-Validation based models for prediction results, it is found that WOA-LASSO  has the smallest MAPE in each step of the 5-step prediction, and the numerical results are between 8.273% and 9.867%. Moreover, when comparing WOA with the conventional optimization scheme Cross-Validation, it is found that WOA can obtain better model hyperparameters, which can effectively enhance the generalization performance and prediction accuracy of the model.