期刊名称：International Journal of Energy Economics and Policy
电子版ISSN：2146-4553
出版年度：2021
卷号：11
期号：4
页码：59-68
DOI：10.32479/ijeep.11364
出版社：EconJournals
摘要：This research aims at diagnosing such priority areas for the development of petrochemicals in Russia as sustainable development and energy efficiency, at identifying trends and forecasting the development of the industry, taking into account the greening of the industry. Achieving the goal is based on the use of methods such as graphical, comparative, economic and mathematical (neural network modeling, correlation regression analysis), and prognostic. The article contains an assessment of the achievement of the Sustainable Development Goals focused on energy saving and environmental protection; forecasting the level of greenhouse gas emissions in Russia based on the construction of a neural network and a regression model; comparative analysis of the rates of transition to sustainable development of chemical production and production of coke and petroleum products in the Russian economy. The scientific results of the research are a neural network model trained on the indicators of sustainable and energy efficient development of the Russian economy, on the basis of which the relationship between the level of greenhouse gas emissions, the energy intensity of GDP and the share of electricity from renewable energy sources is formalized; a predictive model that made it possible to calculate future values of greenhouse gas emissions depending on the target values of predictive variables; features of the greening of petrochemical industries in Russia.
其他摘要：This research aims at diagnosing such priority areas for the development of petrochemicals in Russia as sustainable development and energy efficiency, at identifying trends and forecasting the development of the industry, taking into account the greening of the industry. Achieving the goal is based on the use of methods such as graphical, comparative, economic and mathematical (neural network modeling, correlation regression analysis), and prognostic. The article contains an assessment of the achievement of the Sustainable Development Goals focused on energy saving and environmental protection; forecasting the level of greenhouse gas emissions in Russia based on the construction of a neural network and a regression model; comparative analysis of the rates of transition to sustainable development of chemical production and production of coke and petroleum products in the Russian economy. The scientific results of the research are a neural network model trained on the indicators of sustainable and energy efficient development of the Russian economy, on the basis of which the relationship between the level of greenhouse gas emissions, the energy intensity of GDP and the share of electricity from renewable energy sources is formalized; a predictive model that made it possible to calculate future values of greenhouse gas emissions depending on the target values of predictive variables; features of the greening of petrochemical industries in Russia.
其他关键词：petrochemical industry; state priorities; sustainable development; green industry; energy efficiency; Russia.
