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[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.

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.

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.

This thesis explores Germany’s *Energiewende* (‘energy transition’) and the role of citizen/community energy democracy initiatives at municipal and state levels in shaping developments that underpin this society-wide transformation - examining how grassroots agitation, in particular, has prompted meaningful action and policy change on the part of government at multiple levels. Using Berlin and Hamburg - Germany’s largest urban centers and leading city-states in the country’s federal system - as case studies, the research examines how citizens’ initiatives in both cities have campaigned for the remunicipalization of local energy networks to expedite, democratize, and incorporate social justice goals into each region’s Energiewende. Finally, this study pivots to consider the progress of the transition nationally in recent years, investigating how major events like the Covid-19 pandemic, watershed federal elections in 2021, war in Ukraine, and the resultant energy crisis have affected the evolution and direction of the Energiewende, and the important contributions of citizen/community energy initiatives to the national response here. The analytical framework draws on over 100 interviews conducted with relevant stakeholders and experts involved in the transition, representing different perspectives (e.g. on remunicipalization and the Energiewende itself) and diverse levels of government (e.g. from the district to federal level). This extensive body of original research is complemented by a wide array of other relevant source material that has likewise been consulted to inform this work and further evaluate the impacts of bottom-up energy democracy initiatives on the broader transition in Germany’s regions - and, by extension, nationally - as they continue to affect the pace and trajectory of the now-famous Energiewende. Ultimately, this study contributes an in-depth, ground-level analysis to the literature of key elements that have driven energy system change in Germany, shining a fresh light on the complex and interrelated nexus of sustained grassroots action, policy responses, and shifting sociopolitical realities that form the context in which the Energiewende has been (re)launched, reformed, and reimagined over the decades.

Integrating environmental, social and governance (ESG) variables into the assessment of a mining project is essential to ensure the short and long term acceptance by the various stakeholders involved and the lack of doing so can put the sustainability of a project at risk. Thus, a holistic approach has been proposed which combines profitability and sustainability analysis with social and environmental considerations for any decisions made on processing operation selection or mine expansion. The potential economic implications of these factors would be used for determining the operational strategy. This study is based on an actual quarry case study and statistical data taken from Spain. Quantitative variables related to ESG aspects have been integrated into a block model, and optimisations were performed based on different plant types and waste disposal strategies. Results demonstrate a strong interdependence between profitability and sustainability. It is observed that strategies related to operating costs impact the environmental and social impacts. A green index is also incorporated to evaluate and compare the different scenarios, determining that the most relevant strategies in adding value to mining projects include investment in new technologies, environmental solutions, and economic and social benefits. Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura Objectius de Desenvolupament Sostenible::8 - Treball Decent i Creixement Econòmic Objectius de Desenvolupament Sostenible::12 - Producció i Consum Responsables Peer Reviewed