Natural gas is one of the main energy sources in Poland and accounts for about 15% of the primary energy consumed in the country. Poland covers only 1/5 of its demand from domestic deposits. The rest is imported from Russia, Germany, Norway, the Czech Republic, Ukraine, and Central Asia. An important issue concerning the market of energy resources is the question of the direct impact of the prices of energy resources on the income of exporting and importing countries. It should also be remembered that unexpected and large fluctuations are detrimental to both exporters and importers of primary fuels. The article analyzes natural gas deposits in Poland, raw material trade and proposes a model for forecasting the volume of its consumption, which takes into account historical consumption, prices of energy resources and assumptions of Poland’s energy policy until 2040. A hybrid model was built by combining ARIMA with LSTM artificial neural networks. The validity of the constructed model was assessed using ME, MAE, RMSE and MSE. The average percentage error is 2%, which means that the model largely represents the real gas consumption course. The obtained forecasts indicate an increase in consumption by 2040.

Research on the analysis of the correlation between cutting speed and methane emission in longwalls has so far focused on determining the daily progress of a longwall that is related to limit values of methane bearing capacity. It seems that in the case of increased cutting speed, there should be a correlation between the current of the cutting heads and the amount of methane released from the longwall due to the faster exposure of fresh coal solid and more coal on conveyors. As shown in previous publications, the coal solids and mined coal on conveyors are important or even the most important sources of methane in the longwall. Therefore, if it was possible to confirm the correlation between the cutting head current and methane release at the outlet, it would be possible to use this information in short-term forecasting algorithms. This study presents preliminary results of the research on the correlation between the cutting head current and the methane concentration at the longwall outlet.

The flow rate of solids is subject to random disturbances of the changing feed and can significantly affect the quantitative and qualitative parameters of the coal flotation products. This quantity can be described as a stochastic process. The paper presents the results of the solids flow rate model for coal flotation identification calculations, treated as a disturbance to the process. This is an innovative approach to modelling those quantitative parameters of the flotation feed that are measurably available and whose random changes have a significant impact on the enhancement process under industrial conditions. These include the volumetric flow rate of the feed and, in particular, concentration of solids in the feed. Therefore, it is suggested that random changes of these two parameters of the feed should be mapped using a model of one quantity—the flow rate of solids. This solution is advantageous because this quantity, as a quantitative parameter of the feed, has a significant impact on the course of the coal flotation process. The model is necessary in the process of designing an automatic control system through simulation tests. It allows us to generate a data string simulating random changes to this quantitative parameter of the feed. On this basis, in the simulation model, the correct functioning of the automatic control system is tested, the task of which is to compensate the influence of this disturbance. To determine the empirical model of the feed solids flow rate, measurement data obtained during the registration of the solids concentration and volumetric flow rate of the feed were used in four consecutive periods of operation of an industrial facility of one of the Polish coal processing plants. The time courses of the solids flow rate in the feed were described by ARMA (autoregressive–moving-average model) means, and the two-stage least squares method was used to estimate the model parameters. The results of the identification and verification of the designated model showed the correctness of adopting the third-order ARMA model, with parameters a1 = −1.0682, a2 = −0.2931, a3 = 0.3807, c1 = −0.1588, c2 = −0.2301, c3 = 0.1037, and variance σ2ε = 0.0891, white noise sequence εt, determined on the basis of a series of residuals described by the fifth-order model. It has been shown that the identified model of the flow rate of solids of the feed to flotation as disturbances can be used to develop a predictive model that allows forecasting the modelled quantity with a prediction horizon equal to the sampling period. One-step forecasting based on the determined predictor equation was found to give results consistent with the recorded values of the solid part flow rate of the feed and the extreme values of the prediction error are within the range from −1.08 to 2.90 kg/s.