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 effecti...

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Bibliographic Details
Published in2020 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon) pp. 1 - 5
Main Authors Abramovich, B.N., Babanova, I.S., Tokarev, I.S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.10.2020
Subjects
Analytical models
artificial neural network
captive power plants
Forecasting
Indexes
Load modeling
Predictive models
seasonal index
Time series analysis
Transportation
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Summary: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.
DOI:10.1109/FarEastCon50210.2020.9271495