Regional Demand Forecasting of Refined Oil under Alternative Energy Market’s Competition

Abstract

Refined oil, including gasoline, diesel, et al., is an important fuel for transportation and other industries. With the promotion of new energy, the demand for refined oil market has formed a competitive relationship with the alternative energies’ market. It is necessary to design and transform the refined oil supply chain to meet market requirements and ensure the balance of supply and demand. Forecasting the demand of refined oil market is the important basis for designing and transforming the refined oil supply chain. Because BP neural network shows strong adaptability when solving multi-parameter nonlinear problems, this paper proposed a BP neural network model from the analysis of conventional influence factors and special impact factors such as the share of alternative energies’ market. The actual data was tested to prove that the model could reflect the relationship between the market share of alternative energy and the market demand of refined oil. Analysis was given about the future development of the refined oil market and alternative energy based on the experimental results.