• Energy Research
• other engineering and technologies close
• 7. Clean energy close
• 6. Clean water close
• Netherlands close

This study focuses on formulating the most sustainable concrete by incorporating recycled concrete aggregates and other products retrieved from construction and demolition (C&D) activities. Both recycled coarse aggregates (RCA) and recycled fine aggregates (RFA) are firstly used to fully replace the natural coarse and fine aggregates in the concrete mix design. Later, the cement rich ultrafine particles, recycled glass powder and mineral fibres recovered from construction and demolition wastes (CDW) are further incorporated at a smaller rate either as cement substituent or as supplementary additives. Remarkable properties are noticed when the RCA (4–12 mm) and RFA (0.25–4 mm) are fully used to replace the natural aggregates in a new concrete mix. The addition of recycled cement rich ultrafines (RCU), Recycled glass ultrafines (RGU) and recycled mineral fibres (RMF) into recycled concrete improves the modulus of elasticity. The final concrete, which comprises more than 75% (wt.) of recycled components/materials, is believed to be the most sustainable and green concrete mix. Mechanical properties and durability of this concrete have been studied and found to be within acceptable limits, indicating the potential of recycled aggregates and other CDW components in shaping sustainable and circular construction practices. The authors wish to acknowledge the financial support from EU Horizon 2020 Project VEEP ‘‘Cost-Effective Recycling of C&DW in High Added Value Energy Efficient Prefabricated Concrete Compo-nents for Massive Retrofitting of our Built Environment” (No.723582).

The present work focuses on the sampling procedure and quantification of the PAH yield from the fast pyrolysis of waste softwood. In particular, fast pyrolysis experiments were conducted using a CDS Pyroprobe 5200 at temperatures between 500 °C and 1000 °C, at a heating rate of 600 °C/s for a sample size of 30 mg. High performance liquid chromatography (HPLC) was used for the determination of the PAH compounds present in the liquid sample fraction, while a micro – GC was employed for the analysis of the main gaseous products (CO, CO2, CH4 and H2). An alternative tar sampling protocol was proposed, which employed the use of a cold trap (50 °C) and an isopropanol filled impinger bottle for the collection of the condensable products. The experiments were compared to heated foil reactor based pyrolysis tests within the same temperature range and heating rate, except for a slightly lower sample size (10 mg). The Pyroprobe and adapted sampling system proved to be more efficient regarding PAH capture and quantification compared to the heated foil reactor. Naphthalene, acenaphthylene and phenanthrene were the main PAH compounds detected. The PAH yields increased with pyrolysis temperature, up to values corresponding to roughly 0.2 wt% of the overall yield at 1000 °C. From the results it was derived that PAH evolution is mainly a product of secondary decomposition of primary tar, since the char yield stabilized for higher temperatures and the yields of CO, H2 and CH4 increased. Overall mass balance closure values were around 80 wt% on average. Char and gas yields were determined with high reproducibility, however gravimetric liquid analysis lacked due to the inability to gravimetrically measure the yield condensing in the impinger bottle. Future work is aimed on improving on this particular aspect. Overall, the alternative tar sampling system proposed was successful in the quantification of PAH from biomass fast pyrolysis experiments offering increased flexibility, accuracy and practicality of use.

The Flameless Combustion (FC) regime has been pointed out as a promising combustion technique to lower the emissions of nitrogen oxides (NOx) while maintaining low CO and soot emissions, as well as high efficiencies. However, its accurate modeling remains a challenge. The prediction of pollutant species, especially NOx, is affected by the usually low total values that require higher precision from computational tools, as well as the incorporation of relevant formation pathways within the overall reaction mechanism that are usually neglected. The present work explores a multiple step modeling approach to tackle these issues. Initially, a CFD solution with simplified chemistry is generated [both the Eddy Dissipation Model (EDM) as well as the Flamelet Generated Manifolds (FGM) approach are employed]. Subsequently, its computational cells are clustered to form ideal reactors by user-defined criteria, and the resulting Chemical Reactor Network (CRN) is subsequently solved with a detailed chemical reaction mechanism. The capabilities of the clustering and CRN solving computational tool (AGNES—Automatic Generation of Networks for Emission Simulation) are explored with a test case related to FC. The test case is non-premixed burner based on jet mixing and fueled with CH4 tested for various equivalence ratios. Results show that the prediction of CO emissions was improved significantly with respect to the CFD solution and are in good agreement with the experimental data. As for the NOx emissions, the CRN results were capable of reproducing the non-monotonic behavior with equivalence ratio, which the CFD simulations could not capture. However, the agreement between experimental values and those predicted by CRN for NOx is not fully satisfactory. The clustering criteria employed to generate the CRNs from the CFD solutions were shown to affect the results to a great extent, pointing to future opportunities in improving the multi-step procedure and its application.

Abstract Life Cycle Assessment (LCA) is a powerful tool for achieving sustainability. Traditional LCAs analyze well defined and developed industrial systems, but recent developments of LCA focus on analyzing emerging technologies which are not yet optimized with respect to energy and materials. Therefore, LCA results of ex-ante applications can be very different from ex-post applications for the same system. The purpose of this study is to show the different effects of data scales on LCA results regarding global warming, fine particulate matter formation, terrestrial acidification and freshwater eutrophication potentials. For this purpose torrefaction technology was selected as the case study and assessed based on bench scale data, lab scale data, data derived from process simulations, pilot scale data and commercial scale data. Considered environmental impacts were global warming, fine particulate matter formation, terrestrial acidification and freshwater eutrophication. Results showed that process efficiencies improved significantly between the bench scale system and systems with higher technology readiness levels (TRLs), such as pilot, process simulations and commercial scale systems. Furthermore, process simulations result in scores closer to commercial scale regarding all considered environmental impacts. However, if LCA practitioners focus only on global warming impact, then pilot scale is also a good alternative. Finally, due to torrefaction technology being relatively simple in terms of raw materials input, we suggest more complex chemical systems to be assessed with LCA in various TRLs.

Performing accurate numerical simulations of molten salt reactors is challenging, especially in case of fast-spectrum designs, due to the unique physics phenomena characterizing these systems. The limitations of codes traditionally used in the nuclear community often require the development of novel high-fidelity multi-physics tools to advance the design of these innovative reactors. In this work, we present the most recent code developed at Delft University of Technology for multi-physics simulations of liquid-fueled fast reactors. The coupling is realized between an incompressible RANS model and an SN neutron transport solver. The models are implemented in two in-house codes, based on the discontinuous Galerkin Finite Element discretization, which guarantees high-quality of the solution. We report and discuss the results of preliminary simulations of the Molten Salt Fast Reactor at steady-state and during a Total Loss of Power transient. Results prove our code has capabilities for steady-state and transient analysis of non-moderated liquid-fueled reactors.

The Energy Performance of Buildings Directive (EPBD) enhanced the sustainable improvement of dwellings in the European Union. Member states formulated measurable goals to improve the housing stock, and monitoring systems were developed to give insights into the improvements. In the Netherlands, non-profit housing associations agreed to improve the quality of their housing stock to an average Dutch energy label B (energy index (EI NV) = 1.40) by 2020. Research assessing this progress over time is presented using an annual monitoring system based on 2.0 million energy performance calculations of 264 Dutch non-profit housing associations between 2017 and 2020. The assessment includes: a detailed description of the development of the state of the stock over time; the effect of changes to the stock (construction and demolition) and changes within the stock (different types of retrofit measures); and the different characteristics of non-profit housing associations. Insights from this research show which specific retrofit and other measures are adopted and have substantial impact over time. This provides a useful frame of reference for building stock analysis and accelerating the improvement of the building stock. It also creates a baseline of information for the future sustainable development of this particular stock. 'Practice relevance' This research reveals which energy saving measures are most and least employed over time in Dutch non-profit housing associations sector. Large urban housing associations own a large share of the Dutch non-profit housing stock, and their dwellings have on average a lower energy rating. However, the improvement of their dwellings between 2017 and 2020 is higher than for smaller housing associations, which already have on average a higher energy rating. While the construction and demolition of dwellings contribute to 15.6% of the annual improvement, most of the improvement of the energy performance depends on retrofitting the existing stock. The trends are found to rely most on traditional measures ('e.g'. the installation of high-efficiency gas boilers and improved insulation). However, the rate of adding photovoltaic (PV) solar systems has increased rapidly in recent years, while futureproof systems ('e.g'. heat pumps and district heating) only have a steady adoption rate in this sector.

With increasing decarbonisation and accessibility to our energy systems and markets, there is a need to understand and optimise the value proposition for different stakeholders. Game-theoretic models represent a promising approach to study strategic interactions between self-interested private energy system investors. In this work, we design and evaluate a game-theoretic framework to study strategic interactions between profit-maximising players that invest in network, renewable generation and storage capacity. Specifically, we study the case where grid capacity is developed by a private renewable investor, but line access is shared with competing renewable and storage investors, thus enabling them to export energy and access electricity demand. We model the problem of deducing how much capacity each player should build as a non-cooperative Stackelberg-Cournot game between a dominant player (leader) who builds the power line and renewable generation capacity, and local renewable and storage investors (multiple followers), who react to the installation of the line by increasing their own capacity. Using data-driven analysis and simulations, we developed an empirical search method for estimating the game equilibrium, where the payoffs capture the realistic operation and control of the energy system under study. A practical demonstration of the underlying methodology is shown for a real-world grid reinforcement project in the UK. The methodology provides a realistic mechanism to analyse investor decision-making and investigate feasible tariffs that encourage distributed renewable investment, with sharing of grid access.

This paper introduces an innovative energy management system architecture for Smart Grids, designed in the European 7th framework program project e-balance. The architecture is hierarchical and fractal-like, which results in better scalability and reuse of algorithms and programming code for energy management. It supports both micro-grids and distributed energy resources. The system is structured into two main parts – the communication platform and the energy management platform. The former provides a common data exchange layer, while the latter provides the local energy management logic, currently supporting energy balancing and grid resilience services. The system is being deployed in two pilots: in Portugal and in the Netherlands, where use cases on energy balancing, grid monitoring and grid reliability will be demonstrated.

AbstractWind turbine design codes for calculating blade loads are usually based on a blade element momentum (BEM) approach. Since wind turbine rotors often operate in off‐design conditions, such as yawed flow, several engineering methods have been developed to take into account such conditions. An essential feature of a BEM code is the coupling of local blade element loads with an external (induced) velocity field determined with momentum theory through the angle of attack. Local blade loads follow directly from blade pressure measurements as performed in the National Renewable Energy Laboratory (NREL) phase IV campaign, but corresponding angles of attack cannot (on principle) be measured. By developing a free wake vortex method using measured local blade loads, time‐dependent angle of attack and induced velocity distributions are reconstructed. In a previous paper, a method was described for deriving such distributions in conjunction with blade pressure measurements for the NREL phase VI wind turbine in axial (non‐yawed) conditions. In this paper, the same method is applied to investigate yawed conditions on the same turbine. The study considered different operating conditions in yaw in both attached and separated flows over the blades. The derived free wake geometry solutions are used to determine induced velocity distributions at the rotor blade. These are then used to determine the local (azimuth time dependent) angle of attack, as well as the corresponding lift and drag for each blade section. The derived results are helpful to develop better engineering models for wind turbine design codes. Copyright © 2008 John Wiley & Sons, Ltd.