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Electricity is currently one of the most popular sources of energy. Considering such widespread use of electric energy, we may ask, what is the economic cost of producing and supplying it? The climate crisis and the social pressure associated with it have triggered the necessity to make further investments in renewable and low-emission energy sources, while the COVID-19 pandemic has abruptly limited electricity consumption in industry. All these factors can have an impact on disruptions or loss in the liquidity of companies responsible for supplying electricity to end users. Guaranteeing cash flow for energy sector entities is a prerequisite for energy supply continuity. In this context, the selection and application of reliable sources of information are vital for the management of the financial liquidity of energy sector entities. The aim of this article is to prove the value of the financial information of individual (IFR) and consolidated financial statements (CFR) essential for the indicative liquidity assessment of Polish energy groups in 2018–2021. The hypothesis of this study is that individual and consolidated statements do not offer coincident analytical data due to the diversified role of their parent undertakings. We have applied indicative liquidity assessment analysis from a static and dynamic perspective to 2018–2021, on the basis of individual and consolidated financial statements. The results clearly show high dysfunction in the application of indicative liquidity assessment in the case of the individual financial statement of the parent company. This is mainly due to the role parent companies play in Polish energy sector groups, as they are mainly responsible for support processes.

The article examines modern approaches to energy management in the context of the development of Industry 5.0 with a particular focus on cybersecurity. Key tenets of Industry 5.0 are discussed, including the integration of advanced technologies with intelligent energy management systems (IEMSs) and the growing need to protect data in the face of increasing cyber threats. The challenges faced by small and medium-sized enterprises (SMEs) using solutions based on renewable energy sources, such as photovoltaic farms, are also analyzed. The article presents examples of IEMS applications and discusses methods for securing these systems, offering an overview of cyber threat protection tools in the context of modern energy management. The analysis carried out provided information that will help businesses make rational decisions and contribute to shaping the state’s macroeconomic policy on cybersecurity and energy savings. The results of this research can also help develop more effective strategies for managing technology and IT infrastructure, which is crucial in the digital age of Industry 5.0.

Electricity is one of the most widely used energy sources. The climate crisis, public pressure to invest in renewable and low-carbon energy sources, and the reduction in industrial electricity consumption caused by the COVID-19 pandemic have a significant impact on the energy sector. In addition, military action in Europe is affecting energy generation capacity and availability, which raises the question of economic calculus, particularly regarding the cost of generation and supply. These factors affect the cost structure of those responsible for supplying energy and, in extreme cases, can lead to energy exclusion. The article aimed to identify differences in the presentation and interpretation of operating cost data from the individual and consolidated financial statements of Polish energy groups, which is of key importance for investors, analysts and decision-makers in the energy sector. The analysis uses data for 2018–2022 from the income statement. The research hypothesis is that the complexity of Polish energy groups in the Polish energy sector leads to ambiguity in the interpretation of cost data included in stand-alone and consolidated financial statements.

Employment and the competencies of employees in the energy sector are coming into particular prominence in economies around the world. It is one of the few sectors positively affected by the COVID-19 pandemic. As a result, a significant global change in the awareness of society occurred in favor of increasing pro-health and pro-environmental activities, which can be seen in the green transformation. Poland can also boast such changes in recent years, as evidenced by the dynamic development of renewable energy sources (boom for photovoltaics) and the increase in prosumption. Correlated with this is the increase in demand for employees with specific competencies, the so-called multi-competencies that are a compilation of technical, business, and soft and hard competencies, as well as interdisciplinary ones. The paper emphasizes the need to better adjust the education system to the real needs of the labor market in a turbulent environment with the use of the Sectoral Qualifications Framework in Energy, developed in cooperation with stakeholders from the industry. Therefore, the authors analyzed the employment structure in the energy sector in Poland, with particular emphasis on the factors and conditions of this structure and made an attempt to identify and create a competency profile of employees in this area. For the purposes of this article, two key research problems were formulated: What are the key competencies of employees in the energy sector? How is employment changing in this area? The following research hypothesis was also put forward: The transformation of the energy sector towards green energy affects the increase in employment in this area and the increase in the demand for soft competencies. The analysis was based on statistical data, reports, job advertisements, and a review of the results of empirical research to date.

The main aim of this paper is to assess sustainable transport development, particularly in Polish voivodeships, as well as to identify underdeveloped geographical areas. In order to deal with this research topic, both classical and multivariate order statistical measures were implemented into the research process. The source of information for the research was the data drawn from BDL (Bank of Local Data) Statistics Poland. The rankings of Polish voivodeships were obtained for sustainable transport development and its individual components in the form of three orders: environmental, social and economic. This allowed us to identify underdeveloped regions in the area of transport sustainability and its particular aspects. It should be noted that we applied both the original set of diagnostic variables and their classification into particular orders. However, the choice of variables was mostly conditioned by the availability of data. Furthermore, this was the first time that the taxonomic methods applied here, featuring the implementation of the multidimensional Weber median, have been used to assess aspects of transport sustainability. This kind of synthetic method design allowed us to consider the interactions between different areas of a sophisticated transportation system and made our analysis immune to skewing by diagnostic variables.

Convective drying is the most common drying method, and mathematical modelling of the dewatering process is an essential part of it, playing an important role in the development and optimization of drying devices. Modelling of the leek drying process can be difficult as the specific structure of this vegetable, in which the slices of leek are delaminated into uneven single rings at different times during drying and the material surface changes more than in other vegetables. This study aimed at proposing a theoretical model for leek convective drying, based on the theoretical laws of heat and mass exchange, which should take into account the observed random process disturbances in the form of random coefficients of this model. The paper presents a non-linear model of water content changes with a random coefficient n. Values of the coefficient n, which were considered to be a random variable, were obtained using the Monte Carlo method, using the inversed distribution function as a probabilistic method. The non-linear model of water content changes when a random n coefficient gives a good approximation of the measurements of water content changes to approximately 1–2 kg H2O/kg d.m.