• Energy Research
• 2016-2025close
• Embargo close
• GB close
• DE close
• CN close
• US close
• IT close
• CA close

[EN] The objective of this article is to compare the behaviour of the most representative domestic hot water systems (DHW) in single-family buildings. The study evaluates the energy consumption, equivalent CO2 emissions and cost for each system over a 15-year life period. This analysis is carried out in four cli- matic zones across Europe to observe the influence of climatic conditions on the results. The four climatic zones are located in the cities of Athens, Madrid, London and Berlin. The analysed systems are: a) natural gas-fired instantaneous water heaters, b) electric storage water heater, c) solar thermal system with gas- fired instantaneous, d) solar thermal system with electric storage water heater, e) air-source heat pump, f) photovoltaic system with electric storage water heater, and g) photovoltaic system with air-source heat pump. This range of technologies covers the most likely solutions to be implemented across domestic buildings in Europe.The heat pump system (HPWH) with PV considering self-consumption shows the lowest environmen- tal impact in all zones, but is not an attractive investment in the coldest zones due to lower natural gas prices. Thermal solar systems have a high purchase and maintenance costs which do not compensate their energy savings. The PV HPWH system has a greater reduction of emissions and a lower cost than HPWH across a 15-year life. The gas boiler system has the lowest cost in a 15-year period in the coldest areas, despite having a greater environmental impact than the heat pump.(c) 2023 Elsevier B.V. All rights reserved.

Thermoacoustic technology emerges as a sustainable and low-carbon method for energy conversion, leveraging environmentally friendly working mediums and independence from electricity. This study presents the development of a multimode heat-driven thermoacoustic system designed to utilize medium/low-grade heat sources for room-temperature cooling and heating. We constructed both a simulation model and an experimental prototype for a single-unit direct-coupled thermoacoustic system, exploring its performance in heating-only, cooling-only, and hybrid heating and cooling modes. Internal characteristic analysis including an examination of internal exergy loss and a distribution analysis of key parameters was first conducted in the hybrid cooling and heating mode. The results indicated a positive-focused traveling-wave-dominant acoustic field within the thermoacoustic core unit, enhancing energy conversion efficiency. The output system performance was subsequently tested under different working conditions in the heating-only and cooling-only modes. A maximum output heating power of 2.3 kW and a maximum COPh of 1.41 were observed in the heating-only mode. Meanwhile, a cooling power of 748 W and a COPc of 0.4 were obtained in the typical cooling condition at 7 °C when operating in cooling-only mode. These findings underscore the promising potential of thermoacoustic systems for efficiently utilizing medium/low-grade heat sources for cooling and/or heating applications in the future.

The lifetime and reliability of power transformers are primarily dependent on the hot-spot temperature in the windings, as temperature is the most important factor determining the insulation degradation rate. Key to removing the heat from the transformer is the radiator which must be carefully designed to keep the temperatures within limits under all operating conditions whilst minimizing the transformer size, weight and cost. This paper compares the analytical method used to predict the radiator performance with computational fluid dynamics (CFD) models in terms of heat dissipation. It is found that the analytical method and CFD models give similar results in the air natural (AN) cooling modes, whereas the analytical method overestimates the heat dissipation in the air forced (AF) cooling modes. Moreover, the thermal conduction effect in the radiator wall is investigated under different operating conditions and for different radiator sizes using the CFD models. The simulation results indicate that the radiator wall contributes to 6%-10% of the total heat dissipation under some circumstances and therefore should not be simply ignored in radiator models.

Selective removal of coatings by lasers can facilitate the reuse of coated tools in a circular economy. In order to optimise and control the process, it is essential to study the impact of process input variables on process performance. In this paper, coating removal from tooling was carried out using a picosecond a pulsed fibre laser, in order to investigate the effects of laser pulse energy, pulse frequency, galvo scanning speed and scanning track stepover. A fractional factorial design of experiments and analysis of variance was used to optimise the process; considering cleaning rate, specific energy consumption and surface integrity as assessed by changes in surface roughness and composition of the tooling after laser cleaning. The results shows synergy between cleaning rate and specific energy with the laser pulse frequency and galvo scanning speed as the two most significant factors, while the laser pulse energy had the greatest contribution to changes in surface composition. Based on extensive experiments, the relationship between processing rate and system specific energy consumption was mathematically modelled. The paper contributes a new specific energy model for laser cleaning and provides a benchmark of the process energy requirements compared to other manufacturing processes. Additionally, the generic scientific learning from this is that the rate of energy input is a key tool for maximising cleaning rate and minimising specific energy requirements, while the intensity of energy applied, is a key metric that influences surface integrity. More complex factors, influence the surface integrity.

Engineered cementitious composites (ECCs) are special types of fibre-reinforced cementitious composites (FRCC) with higher strain capacity which can be achieved with low fibre volume as low as 2% and total elimination of coarse aggregates. Due to the outstanding performance of ECCs, they are suitable for various construction and repair applications. However, in order for ECCs to achieve their properties; a high amount of binder which is primarily composed of Portland cement (PC) is used alongside a special type of ultrafine silica sand (USS) which is different from the conventional natural fine aggregates. The production of PC is known to be detrimental to the environment due to its high carbon dioxide emissions coupled with the high consumption of natural resources. Thus, the high use of PC content in ECCs posed a sustainability threat. Similarly, the USS used in ECCs are not readily available everywhere and are expensive. The processing of the USS coupled with its transportation over long distances would also increase the cost and embodied carbon of ECCs. Hence, in order to promote more development and applications of ECCs for various applications; this dissertation aims to provide innovative ways to improve the sustainability of ECCs and their performances. This dissertation offers four solutions to improve the sustainability of ECCs which are (i) use of unconventional industrial by-products as partial replacement of PC (ii) total replacement of PC in ECCs with alternative sustainable binders (iii) replacement of USS in ECCs with recycled materials and (iv) the use of supplementary cementitious materials to replace a high volume of PC. The findings from this study revealed sustainable ECCs with acceptable mechanical and durability performance can be achieved with the use of alternative binders or replacement of the conventional USS used in ECC mixtures. The sustainability and cost assessment of the ECCs indicated that the incorporation of industrial by-products such as blast furnace slag (BFS) especially at higher content is beneficial to reducing the negative environmental impact and economic burden associated with ECCs compared to the conventional ECC. The sustainability index and cost index of the ECCs further showed that the use of BFS is more beneficial when the sustainability and cost of the ECCs are compared with the corresponding performance. Similarly, the use of recycled materials as an alternative to USS was found to result in a significant reduction in the embodied carbon and cost of ECCs. The use of recycled materials such as expanded glass (EG) as aggregates in ECCs was also found to improve the thermal insulation properties of ECCs making such ECC suitable for the production of building envelope elements.

Environmental tax reform (ETR), a shift from labour to carbon taxes, has been mostly modelled using general equilibrium (GE) analysis. Since a low-carbon transition will require deep transformations, one will also have to address out-of-equilibrium dynamics and increased agent heterogeneity. Unlike GE models, agent-based models (ABMs) are well equipped to deal with this. We therefore replicate a recent GE model for ETR using an agent-based approach. This process, known as "agentization", allows assessing similarities as well as differences in policy impacts between the two modelling approaches, in turn providing a test of the robustness of the GE results. We find that the agent-based model is able to replicate many results of the general equilibrium analysis, while revealing strengths and weaknesses of both model types. We discuss concrete implementation steps and difficulties experienced in the GE-ABM translation process. We illustrate the potential of ABM by extending the model in several directions. We show that heterogeneous subsistence consumption can increase the space for combining a double dividend with an equity goal, and that overall macro-economic results can conceal important distributional impacts when green preferences and labour supply elasticities vary.

This paper proposes a novel online and self-learning algorithm to the identification of fuzzy neural networks, which not only learns the structure and parameters online but also learns the threshold parameters by itself and automatically. For structure learning, a self-constructing approach including adding neurons and merging highly similar fuzzy rules is proposed based on the criteria of the system error between actual and model output and the maximum firing strength of neurons. In order to achieve the efficient merging computing, a new calculation method of similarity degree between fuzzy rules is developed. Further and more importantly, the varying width of Gaussian membership functions can be learned by itself according to the underfitting and overfitting criteria. Similarly, different from the existing constant threshold of similarity degree for merging, the varying threshold of similarity degree can be self-learned according to the real-time accuracy of model. The proposed self-learning mechanism significantly improves the model accuracy and greatly enhances the easy usability. Several benchmark examples are implemented to illustrate the effectiveness and feasible of the proposed approach.