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The article presents an innovative method of analyzing energy companies’ strategies, which aims to identify the strategic orientation of the entities subject to the research and, thus, to initially define the directions of strategic changes in the analyzed sector. The aim of the research, the results of which were used in this publication, was to identify the features of energy sector companies’ strategies in the European Union in the period of sector transformation caused by the new climate policy. The analysis area is the energy sector, i.e., the sector whose fundamental strategic goal is energy production. The research used a critical analysis of the subject literature and desk research method with the use of the researchers’ own analytical equipment, developed for the needs of this analysis. It was assumed in the conducted research that the primary source of information in the empirical study, the information subject to subsequent analysis, was the analysis of official documents (strategies, financial reports, etc.) posted on the websites of the surveyed corporations. The research results indicate the dominance of the resource-based approach in implementing strategic postulates of the surveyed companies. Nevertheless, the operational activity focuses on the implementation of innovative solutions towards decarbonization and climate neutrality.

Fans as industrial devices are among the most significant single recipients of driving energy. Therefore, they represent an important area of energy savings to reduce CO2 emissions. The ubiquity of fans and their operation under conditions different from the optimum provides an opportunity for more significant global reductions in the energy used to drive them. The second important aspect, besides energy efficiency, related to the operation of fans is the noise they generate. This article studies fans in various operating configurations, emphasizing improving operating efficiency and reducing noise emissions. The subject matter undertaken is based on the current trends and needs of the industry, notably the ventilation and power industry. The article attempts a detailed literature review taking into account just these aspects. The paper is divided into three main sections, with an analysis of the literature in the areas of energy efficiency, considering the operation of fans with the necessary instrumentation, the incidence of vibration, and noise optimization. The final area of analysis is the parameters and components of the plant in which the fans operate. This article identifies possible sites for further research and scientific work to improve and optimize the areas identified earlier.

Hydrogen as a carbon-free fuel is commonly expected to play a major role in future energy supply, e.g., as an admixture gas in natural gas grids. Which impacts on residential and commercial gas appliances can be expected due to the significantly different physical and chemical properties of hydrogen-enriched natural gas? This paper analyses and discusses blends of hydrogen and natural gas from the perspective of combustion science. The admixture of hydrogen into natural gas changes the properties of the fuel gas. Depending on the combustion system, burner design and other boundary conditions, these changes may cause higher combustion temperatures and laminar combustion velocities, while changing flame positions and shapes are also to be expected. For appliances that are designed for natural gas, these effects may cause risk of flashback, reduced operational safety, material deterioration, higher nitrogen oxides emissions (NOx), and efficiency losses. Theoretical considerations and first measurements indicate that the effects of hydrogen admixture on combustion temperatures and the laminar combustion velocities are often largely mitigated by a shift towards higher air excess ratios in the absence of combustion control systems, but also that common combustion control technologies may be unable to react properly to the presence of hydrogen in the fuel.

Financial liquidity and profitability are two critical phenomena present in the financial economy of a company, whose relations depend on each other and may course in different directions. At the same time, they are an example of the complexity of the problem, which demands a proper approach, allowing one to reconcile two opposing objectives of any enterprise, i.e., maximizing the benefits for the owners and minimizing the risk of losing financial liquidity. Until now, the relationship between liquidity and profitability has not been examined explicitly, using multidimensional methods in particular. Nevertheless, the links between profitability and financial liquidity maintenance ensure the sustainable development of enterprises in different branches. This paper formulates two aims: scientific and practical. The scientific one concerns adopting the canonical variate analysis method to visualize the differences and relationships between food industry companies regarding financial liquidity and profitability. The practical one relates to indicating the relationship between financial liquidity and profitability in different groups of food industry companies. To study the relationships between the selected groups of enterprises and describe them, the liquidity and profitability ratios were utilized, involving canonical variate analysis based on transformation by linear combination and singular value decomposition. The analysis found that the most important feature highlighting the group of the examined entities regarding financial liquidity was the cash conversion cycle. The research results showed the existence of multidirectional relationships between liquidity and profitability. The research indicates that they depend on indicators describing financial dependencies and the industries in which they operate. This led to a much deeper and broader interpretation of the assessment of the financial situation of companies to support their sustainable development.

Le problème d'affectation des cellules est combinatoire, avec une complexité accrue lorsqu'il est abordé compte tenu de l'allocation des ressources. Ce document modélise l'affectation conjointe des cellules et l'affectation des ressources pour les réseaux hétérogènes cellulaires, et formalise l'affectation des cellules en tant que problème d'optimisation. Les algorithmes exacts peuvent trouver des solutions optimales au problème d'affectation des cellules, mais leur temps d'exécution augmente considérablement avec des déploiements de réseau réalistes. À leur tour, les heuristiques sont capables de trouver des solutions dans des délais d'exécution raisonnables, mais elles sont généralement bloquées dans des optima locaux, ne trouvant donc pas de solutions optimales. Les approches métaheuristiques ont réussi à trouver des solutions plus proches de l'optimum que les problèmes combinatoires pour les grands cas. Dans cet article, nous proposons une heuristique rapide et efficace qui donne des solutions d'affectation de cellules très compétitives par rapport à celles obtenues avec trois des métaheuristiques les plus largement utilisées, qui sont connues pour trouver des solutions proches de l'optimum en raison de la nature de leur exploration de l'espace de recherche. Notre approche heuristique ajoute une réduction des dépenses énergétiques dans sa conception algorithmique. Grâce à la simulation et à l'analyse statistique formelle, le système proposé s'est avéré produire des affectations efficaces en termes de nombre d'utilisateurs desservis, d'allocation de ressources et d'économies d'énergie, tout en étant un ordre de grandeur plus rapide que les approches métaheuritsiques. El problema de asignación de celdas es combinatorio, con una mayor complejidad cuando se aborda teniendo en cuenta la asignación de recursos. Este documento modela la asignación conjunta de celdas y la asignación de recursos para redes celulares heterogéneas, y formaliza la asignación de celdas como un problema de optimización. Los algoritmos exactos pueden encontrar soluciones óptimas al problema de asignación de celdas, pero su tiempo de ejecución aumenta drásticamente con implementaciones de red realistas. A su vez, las heurísticas son capaces de encontrar soluciones en tiempos de ejecución razonables, pero generalmente se quedan atascadas en los óptimos locales, por lo que no encuentran soluciones óptimas. Los enfoques metaheurísticos han tenido éxito en la búsqueda de soluciones más cercanas a la óptima para problemas combinatorios para grandes instancias. En este artículo proponemos una heurística rápida y eficiente que produce soluciones de asignación de celdas muy competitivas en comparación con las obtenidas con tres de las metaheurísticas más utilizadas, que se sabe que encuentran soluciones cercanas a las óptimas debido a la naturaleza de su exploración del espacio de búsqueda. Nuestro enfoque heurístico añade una reducción del gasto energético en su diseño algorítmico. A través de la simulación y el análisis estadístico formal, se ha demostrado que el esquema propuesto produce asignaciones eficientes en términos del número de usuarios atendidos, la asignación de recursos y el ahorro de energía, a la vez que es un orden de magnitud más rápido que los enfoques basados en metaheurística. The cell assignment problem is combinatorial, with increased complexity when it is tackled considering resource allocation. This paper models joint cell assignment and resource allocation for cellular heterogeneous networks, and formalizes cell assignment as an optimization problem. Exact algorithms can find optimal solutions to the cell assignment problem, but their execution time increases drastically with realistic network deployments. In turn, heuristics are able to find solutions in reasonable execution times, but they get usually stuck in local optima, thus failing to find optimal solutions. Metaheuristic approaches have been successful in finding solutions closer to the optimum one to combinatorial problems for large instances. In this paper we propose a fast and efficient heuristic that yields very competitive cell assignment solutions compared to those obtained with three of the most widely-used metaheuristics, which are known to find solutions close to the optimum due to the nature of their search space exploration. Our heuristic approach adds energy expenditure reduction in its algorithmic design. Through simulation and formal statistical analysis, the proposed scheme has been proved to produce efficient assignments in terms of the number of served users, resource allocation and energy savings, while being an order of magnitude faster than metaheuritsic-based approaches. مشكلة تخصيص الخلايا هي مشكلة اندماجية، مع زيادة التعقيد عند معالجتها مع مراعاة تخصيص الموارد. تقوم هذه الورقة بنمذجة تخصيص الخلايا المشتركة وتخصيص الموارد للشبكات الخلوية غير المتجانسة، وإضفاء الطابع الرسمي على تخصيص الخلايا كمشكلة تحسين. يمكن للخوارزميات الدقيقة العثور على الحلول المثلى لمشكلة تعيين الخلية، ولكن وقت تنفيذها يزداد بشكل كبير مع عمليات نشر الشبكة الواقعية. في المقابل، يستطيع الاستدلال إيجاد حلول في أوقات تنفيذ معقولة، لكنهم عادة ما يعلقون في الوضع الأمثل المحلي، وبالتالي يفشلون في إيجاد الحلول المثلى. نجحت الأساليب الماورائية في إيجاد حلول أقرب إلى الحل الأمثل للمشاكل التوافقية في الحالات الكبيرة. نقترح في هذه الورقة الاستكشافية السريعة والفعالة التي تسفر عن حلول تعيين خلية تنافسية للغاية مقارنة بتلك التي تم الحصول عليها مع ثلاثة من metaheuristics الأكثر استخدامًا، والتي من المعروف أنها تجد حلولًا قريبة من الأمثل نظرًا لطبيعة استكشافهم لفضاء البحث. يضيف نهجنا الاستكشافي تخفيضًا في إنفاق الطاقة في تصميمه الخوارزمي. من خلال المحاكاة والتحليل الإحصائي الرسمي، ثبت أن المخطط المقترح ينتج مهامًا فعالة من حيث عدد المستخدمين الذين يتم خدمتهم وتخصيص الموارد وتوفير الطاقة، بينما يكون ترتيبًا من حيث الحجم أسرع من النهج القائمة على metaheuritsic.

The purpose of the article is to define the risk factors in cogeneration projects and to demonstrate that a lack of sufficient identification of risks in different phases affects project implementation. A theoretical study is conducted, which aims to identify risk factors in cogeneration projects, based on case studies of such projects in Poland. The study offers a view at CHP (combined heat and power) projects as extremely dependent on the external environment of the organisation. These projects are subject to many external regulations due to their environmental impact and dynamically changing technical aspects. The biggest technical errors occur at the planning and construction stages. The biggest economic and financial risks occur at the execution stage after 2% and 3% of additional design costs occur, respectively. The authors estimated the risks at different stages of the project and concluded that the total cost of failure in correct identification of the risks at the planning stage exceeded PLN 1.5 billion, which amounted to almost 60% of the total additional costs of materialised project risk. Consequently, the biggest challenges in the area of CHP project management at the planning stage are a thorough identification of risks, and the pricing and planning reactions to risk.

According to data from the International Energy Agency (IEA), in order to achieve net-zero CO2 emissions by 2050, approximately 306 million tonnes of green hydrogen (H2) must be produced annually [...]