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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.

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.

In the mass customization environment, product platform development includes several aspects. One relates to the extent to which products are customized. Usually, a high level of product variety brings significant benefits to customers. On the other hand, a high degree of product customization may have a negative environmental impact during production, due to higher material usage. One possible way to reduce the impact is eliminating infeasible configuration options, caused by incompatibilities between optional component types, within a product platform. Such optional components are a source of negative complexity. However, a reduction of optional component types within a product platform can lead to decreasing the extent of the variety of a product to an undesirable level. An effective way of finding this optimal level of reduction is to quantify and analyze the rates between positive and negative complexities, which are related to the numbers of configuration options. The method for this purpose is presented in this paper.

Ground-source heat pumps are an efficient technology for heating and cooling in buildings. However, the main limitation of their widespread application is the borehole heat exchanger’s (BHE) high investment cost. Hybridizing GSHP systems may overcome this limitation. This research work analyzes the long-term energy performance of a dual-source heat pump (DSHP) system, which uses the air or the ground as external heat/sink sources, in three representative European climates. First, a BHE cost-effective design solution is proposed for each climatology; then, a complete energy analysis is carried out, and the optimal source control parameters that best enhance the system performance in each climate are determined with the use of a complete dynamic model of the DSHP system developed in TRNSYS. Simulations were carried out for a 25-year operation period. Results show that the DSHP maintains the efficiency during the simulated period, with deviations lower than 1.7% in all cases. Finally, the source control optimization method results in only slight efficiency gains (<0.35%) but with a stronger effect on the ground/air use ratio (up to 25% use of air in cold climates), reducing the thermal imbalance of the ground and leading to a consequent BHE size length and cost reduction.

As a result of growing interest in the thermal treatment of sewage sludge with methods such as combustion, gasification or pyrolysis, and also in processes that aim to recover precious components such as phosphorus from this waste, a growing demand has been observed for Computational Fluid Dynamics (CFD) models that provide solutions rapidly and accurately for efficient application in research and development. This study was carried out to develop a computationally inexpensive modelling approach for the combustion of pulverized sewage sludge in entrained flow furnaces. Sewage sludge is a very volatile-rich fuel. Therefore, the Steady Diffusion Flamelet model (SFM), in combination with a validated skeletal reaction mechanism, was applied to consider the pulverized firing of sewage sludge. It was possible to represent the complex composition of volatiles emitted from the sludge particles by releasing surrogate fuels. In addition, the influence of limestone additive (calcination reaction) and varying water content (water–gas shift reaction) was investigated experimentally and modelled via CFD. The simulation results confirm that the surrogate fuel approach is valid and can be used to describe pulverized sewage sludge effectively. The temperature and species concentration results, including the influence of the additive and different levels of water content, were confirmed by experimental data, which is usually hard to obtain due to the tendency of PSS to form agglomerates in entrained flow combustion furnaces. The model yields plausible and experimentally validated results for the combustion of sewage sludge powder across a wide range of operating conditions.

A number of measures to diversify its energy supply sources and reduce its dependence on imported energy sources has been taken by the EU. These include pursuing new energy sources, such as renewable energy and liquefied natural gas; increasing the storage capacities; and investing in interconnectors and other infrastructure. However, these actions require long-term adjustment, while there is a need to find an option to meet the energy needs at a moment. One possible option is to utilize seed production wastes for energy production. This research paper aims to investigate the potential of utilizing seed production wastes (SPWs) for energy production in continental Croatia, and assess its feasibility. Eight different SPWs were used in this research, where their energy characteristics were determined and the theoretical thermal potential was calculated if they are used as raw material in the production of thermal energy through biomass and cogeneration power plants, or in biogas power plants. By using the available feedstock, it is theoretically possible to produce a total of 38,051.10 GJ of thermal energy by direct combustion of SPWs and 34,727.91 GJ by combustion of the produced biomethane. The SPWs of oilseed rape and beans contain the highest specific heat potential per hectare.

Cooling demand in buildings is globally increasing, therefore developing more efficient cooling systems is important for the sustainability of European cities. Directive 2012/27/EU of the European Parliament and of the council on energy efficiency states: “Member States should carry out a comprehensive assessment of the potential for high-efficiency cogeneration and district heating and cooling”. The EU project INDIGO is investigating this issue considering also the economic efficiency and the use of renewable energy sources. In a district cooling system different kinds of cooling production can be combined. E.g., the use of absorption chillers with waste heat or through the solar cooling or the use of free cooling (generally the heat is rejected to seas, lakes, rivers or waterways) offer the possibility of a more sustainable way of cooling. Controlling those systems in an efficient way is a complex problem (consider that the cooling demand is much more difficult to predict than the heat demand, particularly the peaks, and sources such as the solar energy and the waste heat are not predetermined by the designers). The main results of INDIGO will be the development of: - predictive controllers (responsible for obtaining the HVAC systems set-points and based on component dynamic thermos-fluid models, some of them also including embedded self-learning algorithms); - system management algorithms (focused on energy efficiency maximization or energy cost minimization); - an open-source planning tool (based on design and performance parameters as well as simulation and optimisation results; LCA framework will be used as a method for both economic feasibility and climate impact assessment). To validate the results, the consortium is analysing case studies, both through energy modelling and through on-site observations and measurements. The present paper focuses mainly on the development of dynamic energy models and on their use in the context of the project.