The article aims to study the determinants of the energy policy implementation process from
risks and danger perspectives by building the risk management system model. The research methodology
is based on the application of the risk map to the energy policy. Our results confirmed
that the risk map could be applied in the energy industry to identify the risks and to implement the
energy policy risk management system model which will prevent critical uncertainties and risk
structure, identified from the risk map as well as bring the energy industry to the future state by
implementing scenarios and strategies, developed by the World Energy Council. The research limitations
are that the main limits are concerned with the lack of the evaluation results of the energy
policy risks aimed for the system management of the changes which these risks may introduce. No
empirical study has been conducted. The application of the risk map is related in a major part to
the enterprise level with financial and technical purposes of changes. In the research we made an
attempt to develop the managerial recommendations for the regulators on how to make a transitions
of risks to opportunities of introducing and managing changes in the framework of the energy
policy risk management system model. The originality/ value of the paper consists firstly, in the innovativeness
of applying the tool of matrix forecasting to the energy sector; secondly, in providing
a supporting tool to policy-makers and managers decisions.
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).