In order to prepare a coal company for the development of future events, it is important to predict how can evolve the key environmental factors. This article presents the most important factors influencing the hard coal demand in Poland. They have been used as explanatory variables during the creation of a mathematical model of coal sales. In order to build the coal sales forecast, the authors used the ARMAX model. Its validation was performed based on such accuracy measures as: RMSE, MAPE and Theil’s index. The conducted studies have allowed the statistically significant factors out of all factors taken into account to be identified. They also enabled the creation of the forecast of coal sales volume in Poland in the coming years. To maintain the predictability of the forecast, the mining company should continually control the macro environment. The proper demand forecast allows for the flexible and dynamic adjustment of production or stock levels to market changes. It also makes it possible to adapt the product range to the customer’s requirements and expectations, which, in turn, translates into increased sales, the release of funds, reduced operating costs and increased financial liquidity of the coal company. Creating a forecast is the first step in planning a hard coal mining strategy. Knowing the future needs, we are able to plan the necessary level of production factors in advance. The right strategy, tailored to the environment, will allow the company to eliminate unnecessary costs and to optimize employment. It will also help the company to fully use machines and equipment and production capacity. Thanks to these efforts, the company will be able to reduce production costs and increase operating profit, thus survive in a turbulent environment.

The level of sales of a given good depends largely on the distribution network. An analysis of the distribution network allows companies to optimize business activity, which improves the efficiency and profitability of a company’s sales with an immediate effect on profit growth. The so-called spatial analysis is highly useful in this regard. The paper presents an analysis of the network of authorized dealers of the Polish Mining Group for the Opolskie Province. The analysis was done using GIS (SIP) tools. The purpose of the analysis was to present tools that could be used to verify an existing distribution network, to optimize it, or to create a new sales outlet. The prresented tools belong to GIS operations used to process data stored in Spatial Information System resources. These are so-called geoprocessing tools. The article contains several spatial analyses, which results in choosing the optimum location of the distribution point in terms of the defined criteria. The used tools include a spatial intersection and sum. Geocoding and the so-called cartodiagram were also used. The presented analysis can be performed for both the network of authorized retailers within a region, a city or an entire country. The presented tools provide the opportunity to specify the target consumers, areas where they are located and areas of potential consumer concentration. This allows the points of sale in areas with a high probability of finding new customers to be located, which enables the optimal location to be chosen, for example, in terms of access to roads, rail transport, locations of the right area and neighborhood. Spatial analysis tools will also enable the coal company to verify its already existing distribution network.

Securing the certainty of supplies of the necessary minimum energy in each country is a basic condition for the energy security of the state and its citizens. The concept of energy security combines several aspects at the same time, as it can be considered in terms of the availability of own energy resources, it concerns technical aspects related to technical infrastructure, as well as political aspects related to the management and diversification of energy supplies. Another aspect of the issue of energy security is the environmental perspective, which is now becoming a priority in the light of the adopted objectives of the European Union’s energy policy. The restrictive requirements for reducing greenhouse gas emissions and increasing the required level of renewable energy sources in the energy balance of the Member States is becoming a challenge for economies that use fossil fuels to a large extent in the raw material structure, including Poland. Poland is the largest producer of hard coal in the European Union and hard coal is a strategic raw material as it satisfies about 50% of the country’s energy demand. In this context, the main goal of the article was to determine the future sale of hard coal by 2030 in relation to environmental regulations introduced in the energy sector. For this purpose, a mathematical model with a 95% confidence interval was developed using artificial LSTM neural networks, which belong to deep learning machine learning techniques, which reflects the key relationships between hard coal mining and the assumptions adopted in the National Energy and Climate Plan for the years 2021–2030 (NECP).