Development of Forecasting Models to Manage the Power Consumption Modes of the Gas Industry Facilities

The paper proposes the solution to the problem of forecasting the power load for various gas industry enterprises in the regions of Siberia and the Far East, considering the seasonal index and cyclic load and irregularity factors, and using neural network algorithms. The data obtained are an effective tool to improve the tariff policy and determine further personnel actions aimed at optimizing the contractual work and minimizing the expenses for power consumed based on the artificial neural network models developed considering the pattern and parameters of power consumption. The study results can be used to optimize the operating modes of the existing mineral resource sector facilities to save on electric energy or fuel gas at a self-contained power supply. © 2020 IEEE