An Econometric Model of the Operation of the Steel Industry in POLAND in the Context of Process Heat and Energy Consumption

The analyses presented in the publication allowed, on the basis of the data collected, development of an econometric model for the Polish steel industry from the point of view of the relationship between heat and energy management in the steel production process. The developed model is the main novelty of the paper. The main objective of the study was to develop an econometric model of Poland’s heat and energy economy. The following research questions were raised: Is there an econometric model describing heat consumption (intensity) in the steel industry in Poland in relation to steel production and the energy economy? What are the relations between heat intensity and energy prices and steel production in Poland? How might the current energy crisis affect steel production? In the analysis we used data of energy and heat management in the Polish steel industry. An econometric model was developed of the dependence of heat consumption (Yt) on electricity prices (X1t) and steel production (X2t) in Poland. The authors took advantage of open access to data. Annual volumes of heat consumption in steel production processes in Poland were analysed as a function of the annual volume of steel production and the prices of electricity, which are consumed in technological processes in steel mills. We analyzed data for years 2004–2020. The analyses carried out showed that there is an inversely proportional relationship between electricity prices and the intensity of heat consumption by the steel industry. Research shows that rising energy prices lead to lower steel production. This is a dangerous phenomenon for the steel industry in the context of the current energy crisis caused by the pandemic and war in Ukraine. We think that the significance of our results is connected with the fact that the developed model is a useful analytical tool, as it not only allows the analysis of historical data, but can also be used to predict how steel industry parameters will change in the future under the influence of changes in external factors, such as energy prices. This gives a wide range of analytical possibilities for the use of the model.