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“Reducing winter peaks in electricity consumption: A choice experiment to structure demand response programs”. Srivastava A, Van Passel S, Kessels R, Valkering P, Laes E, Energy Policy 137, 111183 (2020). http://doi.org/10.1016/j.enpol.2019.111183
Abstract: Winter peaks in Belgian electricity demand are significantly higher than the summer peaks, creating a greater potential for imbalances between demand and supply. This potential is exacerbated because of the risk of outages in its ageing nuclear power plants, which are being phased out in the medium term. This paper conducts a choice experiment to investigate the acceptability of a load control-based demand response program in the winter months. It surveys 186 respondents on their willingness to accept limits on the use of home appliances in return for a compensation. Results indicate that respondents are most affected by the days of the week that their appliance usage would be curtailed, and by the compensation they would receive. The willingness to enroll in a program increases with age, environmental consciousness, home ownership, and lower privacy concerns. The analysis predicts that 95% of the sample surveyed could enroll in a daily load control program for a compen- sation of €41 per household per year. Thus while an initial rollout among older and more pro-environment homeowners could be successful, a wider implementation would require an explanation of its environmental and financial benefits to the population, and a greater consideration of their data privacy concerns.
Keywords: A1 Journal Article; Engineering Management (ENM) ;
Impact Factor: 9
DOI: 10.1016/j.enpol.2019.111183
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“A review on learning effects in prospective technology assessment”. Thomassen G, Van Passel S, Dewulf J, Renewable &, Sustainable Energy Reviews 130, 109937 (2020). http://doi.org/10.1016/j.rser.2020.109937
Abstract: Global environmental problems have urged the need for developing sustainable technologies. However, new technologies that enter the market have often higher economic costs and potentially higher environmental impacts than conventional technologies. This can be explained by learning effects: a production process that is performed for the first time runs less smooth than a production process that has been in operation for years. To obtain a fair estimation of the potential of a new technology, learning effects need to be included. A review on the current literature on learning effects was conducted in order to provide guidelines on how to include learning effects in prospective technology assessment. Based on the results of this review, five recommendations have been formulated and an integration of learning effects in the structure of prospective technology assessment has been proposed. These five recommendations include the combined use of learning effects on the component level and on the end product level; the combined use of learning effects on the technical, economic and environmental level; the combined use of extrapolated values and expert estimates; the combined use of learning-by-doing and learning-by-searching effects and; a tier-based method, including quality criteria, to calculate the learning effect. These five complementary strategies could lead to a clearer perspective on the environmental impact and cost structure of the new technology and a fairer comparison base with conventional technologies, potentially resulting in a faster adoption and a shorter time-to-market for sustainable technologies.
Keywords: A1 journal article; Learning effects; Life cycle assessment; Techno-economic assessment; Prospective technology assessment; Learning-by-doing; Learning curve; Progress rate; Experience curve; Engineering Management (ENM) ;
Impact Factor: 15.9
DOI: 10.1016/j.rser.2020.109937
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Van Hoecke L, Laffineur L, Campe R, Perreault P, Verbruggen SW, Lenaerts S (2021) Challenges in the use of hydrogen for maritime applications
Abstract: Maritime shipping is a key factor that enables the global economy, however the pressure it exerts on the environment is increasing rapidly. In order to reduce the emissions of harmful greenhouse gasses, the search is on for alternative fuels for the maritime shipping industry. In this work the usefulness of hydrogen and hydrogen carriers is being investigated as a fuel for sea going ships. Due to the low volumetric energy density of hydrogen under standard conditions, the need for efficient storage of this fuel is high. Key processes in the use of hydrogen are discussed, starting with the production of hydrogen from fossil and renewable sources. The focus of this review is different storage methods, and in this work we discuss the storage of hydrogen at high pressure, in liquefied form at cryogenic temperatures and bound to liquid or solid-state carriers. In this work a theoretical introduction to different hydrogen storage methods precedes an analysis of the energy-efficiency and practical storage density of the carriers. In the final section the major challenges and hurdles for the development of hydrogen storage for the maritime industry are discussed. The most likely challenges will be the development of a new bunkering infrastructure and suitable monitoring of the safety to ensure safe operation of these hydrogen carriers on board the ship.
Keywords: A1 Journal Article;Review article, Hydrogen Production, Hydrogen Storage, Maritime Applications; Sustainable energy, air and water technology (DuEL)
Impact Factor: 29.518
DOI: 10.1039/D0EE01545H
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“The path to sustainable energy supply systems: Proposal of an integrative sustainability assessment framework”. Buchmayr A, Verhofstadt E, Van Ootegem L, Sanjuan Delmás D, Thomassen G, Dewulf J, Renewable &, Sustainable Energy Reviews 138, 110666 (2021). http://doi.org/10.1016/j.rser.2020.110666
Abstract: Energy supply is essential for the functioning and well-being of a society. Decision-makers are faced with the challenge to balance burdens and benefits of energy supply practices with the aim to achieve environmental, economic, and social sustainability. Literature exhibits a broad variety of sustainability assessment frameworks for energy supply technologies. However, there is no consensus on which aspects need to be covered for a comprehensive assessment of sustainability. While some aspects, such as environmental emission damage, receive predominant attention, there is a lack of coverage and adequate quantification for others. This led in the past to an unbalanced basis for decision-making.
Based on an analysis of literature, 12 impact categories were identified for the assessment of energy technologies. The analysis included the judgement of quantification approaches regarding their significance for describing the impact categories and their maturity resulting in the proposal of 12 concrete indicators. A framework is proposed to manage and integrate the assessment of single impact categories. The framework produces normalized and weighted output indicators to use in the form of a dashboard or alternatively a single sustainability index for informed decision-making.
Finally, the proposed sustainability assessment framework relies on life cycle, local impact, and supply chain risks assessment. It consists of both well-established assessment methods as well as suggestions for new indicators in order to allow a full assessment of all impact categories. It thereby goes beyond the isolated assessment of impacts and offers the basis for comparison of complete energy supply mixes.
Keywords: A1 Journal Article; Engineering Management (ENM) ;
Impact Factor: 8.05
DOI: 10.1016/j.rser.2020.110666
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“Correction: From the Birkeland–Eyde process towards energy-efficient plasma-based NOXsynthesis: a techno-economic analysis”. Rouwenhorst KHR, Jardali F, Bogaerts A, Lefferts L, Energy &, Environmental Science 16, 6170 (2023). http://doi.org/10.1039/D3EE90066E
Abstract: Correction for ‘From the Birkeland–Eyde process towards energy-efficient plasma-based NO<sub><italic>X</italic></sub>synthesis: a techno-economic analysis’ by Kevin H. R. Rouwenhorst<italic>et al.</italic>,<italic>Energy Environ. Sci.</italic>, 2021,<bold>14</bold>, 2520–2534, https://doi.org/10.1039/D0EE03763J.
Keywords: A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 32.5
DOI: 10.1039/D3EE90066E
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“Feasibility study of a small-scale fertilizer production facility based on plasma nitrogen fixation”. Manaigo F, Rouwenhorst K, Bogaerts A, Snyders R, Energy Conversion and Management 302, 118124 (2024). http://doi.org/10.1016/j.enconman.2024.118124
Keywords: A1 Journal Article; Plasma-based nitrogen fixation Haber-Bosch Feasibility study Fertilizer production; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 10.4
DOI: 10.1016/j.enconman.2024.118124
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“Is a catalyst always beneficial in plasma catalysis? Insights from the many physical and chemical interactions”. Loenders B, Michiels R, Bogaerts A, Journal of Energy Chemistry 85, 501 (2023). http://doi.org/10.1016/j.jechem.2023.06.016
Abstract: Plasma-catalytic dry reforming of CH4 (DRM) is promising to convert the greenhouse gasses CH4 and CO2 into value-added chemicals, thus simultaneously providing an alternative to fossil resources as feedstock for the chemical industry. However, while many experiments have been dedicated to plasma-catalytic DRM, there is no consensus yet in literature on the optimal choice of catalyst for targeted products, because the underlying mechanisms are far from understood. Indeed, plasma catalysis is very complex, as it encompasses various chemical and physical interactions between plasma and catalyst, which depend on many parameters. This complexity hampers the comparison of experimental results from different studies, which, in our opinion, is an important bottleneck in the further development of this promising research field. Hence, in this perspective paper, we describe the important physical and chemical effects that should be accounted for when designing plasma-catalytic experiments in general, highlighting the need for standardized experimental setups, as well as careful documentation of packing properties and reaction conditions, to further advance this research field. On the other hand, many parameters also create many windows of opportunity for further optimizing plasma-catalytic systems. Finally, various experiments also reveal the lack of improvement in plasma catalysis compared to plasma-only, specifically for DRM, but the underlying mechanisms are unclear. Therefore, we present our newly developed coupled plasma-surface kinetics model for DRM, to provide more insight in the underlying reasons. Our model illustrates that transition metal catalysts can adversely affect plasmacatalytic DRM, if radicals dominate the plasma-catalyst interactions. Thus, we demonstrate that a good understanding of the plasma-catalyst interactions is crucial to avoiding conditions at which these interactions negatively affect the results, and we provide some recommendations for improvement. For instance, we believe that plasma-catalytic DRM may benefit more from higher reaction temperatures, at which vibrational excitation can enhance the surface reactions.
Keywords: A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 13.1
DOI: 10.1016/j.jechem.2023.06.016
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“Plasma-based CO2 conversion: How to correctly analyze the performance?”.Wanten B, Vertongen R, De Meyer R, Bogaerts A, Journal of Energy Chemistry 86, 180 (2023). http://doi.org/10.1016/j.jechem.2023.07.005
Keywords: A1 journal article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 13.1
DOI: 10.1016/j.jechem.2023.07.005
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“Machine learning-driven optimization of plasma-catalytic dry reforming of methane”. Cai Y, Mei D, Chen Y, Bogaerts A, Tu X, Journal of Energy Chemistry 96, 153 (2024). http://doi.org/10.1016/j.jechem.2024.04.022
Abstract: This study investigates the dry reformation of methane (DRM) over Ni/Al2O3 catalysts in a dielectric barrier discharge (DBD) non-thermal plasma reactor. A novel hybrid machine learning (ML) model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data. To address the non-linear and complex nature of the plasma-catalytic DRM process, the hybrid ML model integrates three well-established algorithms: regression trees, support vector regression, and artificial neural networks. A genetic algorithm (GA) is then used to optimize the hyperparameters of each algorithm within the hybrid ML model. The ML model achieved excellent agreement with the experimental data, demonstrating its efficacy in accurately predicting and optimizing the DRM process. The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance. We found that the optimal discharge power (20 W), CO2/CH4 molar ratio (1.5), and Ni loading (7.8 wt%) resulted in the maximum energy yield at a total flow rate of 51 mL/min. Furthermore, we investigated the relative significance of each operating parameter on the performance of the plasmacatalytic DRM process. The results show that the total flow rate had the greatest influence on the conversion, with a significance exceeding 35% for each output, while the Ni loading had the least impact on the overall reaction performance. This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets, enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.
Keywords: A1 Journal Article; Plasma catalysis Machine learning Process optimization Dry reforming of methane Syngas production; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ;
Impact Factor: 13.1
DOI: 10.1016/j.jechem.2024.04.022
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“Single-layered imine-linked porphyrin-based two-dimensional covalent organic frameworks targeting CO₂, reduction”. Arisnabarreta N, Hao Y, Jin E, Salame A, Muellen K, Robert M, Lazzaroni R, Van Aert S, Mali KS, De Feyter S, Advanced energy materials (2024). http://doi.org/10.1002/AENM.202304371
Abstract: The reduction of carbon dioxide (CO2) using porphyrin-containing 2D covalent organic frameworks (2D-COFs) catalysts is widely explored nowadays. While these framework materials are normally fabricated as powders followed by their uncontrolled surface heterogenization or directly grown as thin films (thickness >200 nm), very little is known about the performance of substrate-supported single-layered (approximate to 0.5 nm thickness) 2D-COFs films (s2D-COFs) due to its highly challenging synthesis and characterization protocols. In this work, a fast and straightforward fabrication method of porphyrin-containing s2D-COFs is demonstrated, which allows their extensive high-resolution visualization via scanning tunneling microscopy (STM) in liquid conditions with the support of STM simulations. The as-prepared single-layered film is then employed as a cathode for the electrochemical reduction of CO2. Fe porphyrin-containing s2D-COF@graphite used as a single-layered heterogeneous catalyst provided moderate-to-high carbon monoxide selectivity (82%) and partial CO current density (5.1 mA cm(-2)). This work establishes the value of using single-layered films as heterogene ous catalysts and demonstrates the possibility of achieving high performance in CO2 reduction even with extremely low catalyst loadings.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
Impact Factor: 27.8
DOI: 10.1002/AENM.202304371
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