• Energy Research
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Although the relationship between renewable energy and economic performance has attracted the interest of researchers in recent years, most of the analysis has focused on economic growth, which does not reflect the quality of standards of living. We employ a different approach measuring the impact of renewable energy consumption on the Human Development Index, which also considers qualitative characteristics. Using a simultaneous equation system approach that describes the interrelations between economic variables, renewable energy and pollution emissions with feedback effects, we provide robust evidence for a set of 28 OECD countries over the period 2004-2015, that renewable energy, human and physical capital are important factors for explaining the degree of sustainable development. Renewable energy consumption is mostly determined by higher levels of human capital, R&D, and the countries’ development stage. Furthermore, the development level, total energy consumption, and the education level are important for explaining environmental pollution.

Abstract This paper evaluates the impact of PCM-drywalls in the annual and monthly heating and cooling energy savings of an air-conditioned lightweight steel-framed (LSF) residential single-zone building, considering real-life conditions and several European climates. A multi-dimensional optimization study is carried out by combining EnergyPlus and GenOpt tools. The CondFD-algorithm is used in EnergyPlus to simulate phase-changes. For the optimization, the PSOCC-algorithm is used considering a set of predefined discrete construction solutions. These variables are related with the thermophysical properties of the PCM (enthalpy-temperature and thermal conductivity-temperature functions), solar absortance of the inner surfaces, thickness and location of the PCM-drywalls. Several parameters are included in the model mainly those related with the air-conditioned set-points, air-infiltration rates, solar gains, internal gains from occupancy, equipment and lighting. Indices of energy savings for heating, cooling and for both heating and cooling are defined to evaluate the energy performance of the PCM-enhanced rooms. Results show that an optimum solution can be found for each climate and that PCMs can contribute for the annual heating and cooling energy savings. PCM-drywalls are particularly suitable for Mediterranean climates, with a promising energy efficiency gain of about 62% for the Csb-Coimbra climate. As for the other climates considered, values of about 10% to 46% were obtained.

Photocatalytic oxidation is promising technology for removal of recalcitrant pollutants from water. Solar energy can be an interesting radiation source since the operating costs can be lower. However, the use of powder photocatalyst is a major drawback of the technology since suitable separation technologies are required and catalysts recovery is difficult. This work aims to test the suitability of using polymeric supports to immobilize TiO 2 in the reactor and apply it for parabens removal from water by solar photocatalytic oxidation. Polyurethanes (PU) and polydimethylsiloxane (PDMS) membranes were prepared and modified with TiO 2. While PU materials are only able to adsorb (35% in 1 h) parabens whichever the modification applied, modified PDMS was able to promote parabens photocatalytic oxidation removing 20% in 1 h under solar energy. Plasma/UV modification was able to active PDMS membranes (16% of methyl paraben (MP) removal) and further entrapment of TiO 2 in the polymeric matrix did not improve the process (18% of MP removal). Thus, only the superficial TiO 2 was active. Results show that PDMS is suitable material to support TiO 2 aiming photocatalytic wastewater treatment process using the Sun as a clean and renewable energy source.

This article presents an assessment of the most suitable compressed air energy storage (CAES) reservoirs and facilities to better integrate renewable energy into the electricity grid. The novelty of this study resides in selecting the best CAES reservoir sites through the application of a multi-criteria decision aid (MCDA) tool, specifically the simple additive weighting (SAW) method. Besides using geographic information systems (GIS) spatial representation of potential reservoir areas, for the MCDA method, several spatial criteria, environmental and social constraints, and positive incentives (e.g., the proximity to existing power generation facilities of renewable energy sources) were contemplated. As a result, sixty-two alternatives or potential reservoir sites were identified, and thirteen criteria (seven constraints and six incentives) were considered. The final stage of this study consisted of conducting a sensitivity analysis to determine the robustness of the solutions obtained and giving insights regarding each criterion’s influence on the reservoir sites selected. The three best suitable reservoir sites obtained were the Monte Real salt dome, Sines Massif, and the Campina de Cima—Loulé salt mine. The results show that this GIS-MCDA methodological framework, integrating spatial and non-spatial information, proved to provide a multidimensional view of the potential reservoir CAES systems incorporating both constraints and incentives.

Achieving nearly zero-energy buildings (nZEB) is one of the main objectives defined by the European Union for achieving carbon neutrality in buildings. nZEBs are heavily reliant on distributed renewable generation energy sources, which create new challenges associated with their inherent intermittency. To achieve nZEB levels, demand management plays an essential role to balance supply and demand. Since up to two-thirds of the total consumed energy in buildings is dispended for Heating, Ventilation and Air Conditioning (HVAC) operations, intelligent control of HVAC loads is of utmost importance. The present work aims to offer a solution to improve a building microgrids’ flexibility by shifting thermal loads and taking advantage of room thermal inertia. Innovation is present in using the internet of things to link several decentralized local microcontrollers with the microgrid and in the applicability of different control algorithms, such as the pre-emptive heating/cooling of a room. The developed solution relies on smart thermostats, which can be integrated into a building management system, or in a microgrid, and are capable of fulfilling the occupants’ need for comfort while complementing the building with needed power flexibility. The equipment is capable of controlling several HVAC systems to guarantee thermal and air quality comfort, as well as coordinate with a building/microgrid operator to reduce energy costs by shifting thermal loads and enacting demand control strategies. The smart thermostat uses an algorithm to calculate room inertia and to pre-emptively heat/cool a room to the desired temperature, avoiding peak hours, taking advantage of variable tariffs for electricity, or periods of solar generation surplus. The smart thermostat was integrated into a university campus microgrid and tested in live classrooms. Since the work was developed during the COVID-19 pandemic, special attention was given to the air quality features. Results show that smart HVAC control is a viable way to provide occupant comfort, as well as contribute to the integration of renewable generation and increase energy efficiency in buildings and microgrids.

Dissertação de Mestrado em Energia para a Sustentabilidade apresentada à Faculdade de Ciências e Tecnologia O setor de energia é fundamental para o desenvolvimento sustentável. Manter os níveis de atividade econômica enquanto reduz-se o consumo de eletricidade é um dos principais desafios a ser superado.Neste contexto, a intensidade elétrica é um indicador chave na avaliação da eficiência econômica por ser uma medida da produção da economia relacionada à eletricidade demandada. No entanto, a análise simplista do índice de intensidade elétrica não é muito reveladora, uma vez que os desvios neste índice são resultado de mudanças nos seus diferentes componentes. Desta forma, o objetivo desta dissertação é abordar detalhadamente a influência destes componentes, decompondo o indicador de intensidade elétrica na União Europeia.Complementando o método logarithmic mean Divisia index (LMDI) introduzido por Ang (2015), é proposta uma atualização que decompõe o componente de intensidade e adiciona um novo elemento à metodologia de decomposição. Consequentemente, os componentes da intensidade elétrica são três: estrutura, eficiência e eletrificação. Este aprimoramento, inovador de acordo com o nosso conhecimento, é fundamental para distinguir a real influência do componente de eficiência dos outros elementos, considerando que as metas de eficiência energética têm se tornado mais rigorosas e precisam ser perfeitamente mensuradas.Os resultados da decomposição atualizada demonstraram que o impacto causado pelo componente de eficiência foi, na verdade, maior do que aparentava. Se houvesse apenas melhorias de eficiência energética e, simultaneamente, nenhuma mudança na estrutura econômica e na taxa de eletrificação, o índice de intensidade elétrica teria diminuído 48,64% entre 1995 e 2017, valor 8,75% maior ao que realmente ocorreu.O fator estrutural apresentou menor influência na intensidade elétrica, embora o setor de serviços tenha aumentado a sua participação em 5,12% e a estrutura econômica da UE tenha mudado. Adicionalmente, o componente de eletrificação contribuiu para aumentar o indicador de intensidade, já que o consumo de eletricidade cresceu a taxa superior à produção econômica.Por fim, uma análise particionada demonstrou que a redução na intensidade elétrica foi causada exclusivamente por melhorias de eficiência no ciclo 2012-2017, sugerindo evidências positivas a respeito do sucesso das medidas de eficiência energética na UE. The energy sector is fundamental for sustainable development. Maintaining high levels of economic activity while reducing electricity consumption is still one of the main challenges to overcome.In this context, electricity intensity is a key indicator in assessing the economic efficiency because it is a measure of the economy output related to the electricity demanded. However, a simplistic analysis of the electricity intensity index does not reveal much, since the deviations in this indicator are the result of changes in its different components. Therefore, the objective of this dissertation is to address these components influence in detail, decomposing the electricity intensity indicator in European Union.Complementing the logarithmic mean Divisia index (LMDI) method introduced by Ang (2015), an upgrade is proposed, by breaking down the intensity component and adding a new element to the decomposition methodology. Consequently, the components of the electricity intensity are three: structure, efficiency and electrification. This enhancing feature, innovative to the best of our knowledge, is fundamental in distinguishing the real influence of the efficiency component from other elements, considering that energy efficiency goals are becoming more stringent and have to be perfectly measured.Results from the upgraded decomposition demonstrated that the impact caused by the efficiency component was, in fact, greater than it appeared. If there had been merely improvements in energy efficiency, and simultaneously no changes neither in the economic structure, nor in the electrification rate, the electricity intensity index would have decreased 48.64% from 1995 to 2017, a result 8.75% greater than what actually occurred.The structural factor displayed minor influence in electricity intensity, even though the service sector increased its shared by 5.12% and the economic activity profile of EU has changed. Additionally, the electrification component contributed to increase the intensity indicator, since the electricity consumption has grown at a higher rate than the economy output.Finally, a partitioned analysis demonstrated that the reduction in electricity intensity was solely caused by efficiency improvements in the 2012-2017 cycle, suggesting positive evidence regarding the success of energy efficiency measures in the EU.

Moving towards a global bioeconomy can mitigate climate change and the depletion of fossil fuels. Within this context, this work applies a set of multi-criteria decision analysis (MCDA) tools to prioritise the selection of five alternative bioenergy systems for residential heating based on the combination of three commercial technologies (pellet, wood stove and traditional fireplace) and two different feedstocks (eucalypt and maritime pine species). Several combinations of MCDA methods and weighting approaches were compared to assess how much results can differ. Eight indicators were used for a sustainability assessment of the alternatives while four MCDA methods were applied for the prioritisation: Weighted Sum Method (WSM), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Elimination and Choice Expressing Reality (ELECTRE), and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). Regarding the sustainability performance indicators, the highest environmental impacts were calculated for the fireplace alternatives, and there was not a best environmental option. Also, no clear trend was found for the economic and social dimensions. The application of MCDA tools shows that wood stove alternatives have the best sustainability performance, in particular wood stove with combustion of maritime pine logs (highest scores in the ranking). Regarding the worst alternative, fireplaces with combustion of eucalypt logs ranked last in all MCDA rankings. Finally, a sensitivity analysis for the weighting of the performance indicators confirmed wood stoves with combustion of maritime pine logs as the leading alternative and the key role of the analysts within this type of MCDA studies.

Abstract Given the importance of renewable energy in the discussion of a reliable and sustainable energy future, it is imperative to understand its main determinants and to draw result implications for energy policy. This study analyses these determinants for Sub-Saharan Africa. Using a panel data technique, namely the panel-ARDL model for a period covering 1990–2014, the results suggest that economic development (per capita GDP) and an increased use of energy aid renewable energy development while population growth impedes it. Furthermore, the study investigates the potentials and current status of renewable energy in Sub-Saharan Africa. This article shows that although the region has great potential for developing renewable energy such as wind, biomass, solar and hydropower, dispersed throughout the continent, this potential has not been fully explored, even though many resources are plentifully available, and evidence good economic potential.