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Short-rotation coppice (SRC) Salix plantations have the potential to provide fast-growing biomass feedstock with significant soil and climate mitigation benefits. Salix varieties exhibit significant variation in their physiological traits, growth patterns and soil ecology—but the effects of these variations have rarely been studied from a systems perspective. This study analyses the influence of variety on soil organic carbon (SOC) dynamics and climate impacts from Salix cultivation for heat production for a Swedish site with specific conditions. Soil carbon modelling was combined with a life cycle assessment (LCA) approach to quantify SOC sequestration and climate impacts over a 50-year period. The analysis used data from a Swedish field trial of six Salix varieties grown under fertilized and unfertilized treatments on Vertic Cambisols during 2001–2018. The Salix systems were compared with a reference case where heat is produced from natural gas and green fallow was the land use alternative. Climate impacts were determined using time-dependent LCA methodology—on a land-use (per hectare) and delivered energy unit (per MJheat) basis. All Salix varieties and treatments increased SOC, but the magnitude depended on the variety. Fertilization led to lower carbon sequestration than the equivalent unfertilized case. There was no clear relationship between biomass yield and SOC increase. In comparison with reference cases, all Salix varieties had significant potential for climate change mitigation. From a land-use perspective, high yield was the most important determining factor, followed by SOC sequestration, therefore high-yielding fertilized varieties such as ‘Tordis’, ‘Tora’ and ‘Björn’ performed best. On an energy-delivered basis, SOC sequestration potential was the determining factor for the climate change mitigation effect, with unfertilized ‘Jorr’ and ‘Loden’ outperforming the other varieties. These results show that Salix variety has a strong influence on SOC sequestration potential, biomass yield, growth pattern, response to fertilization and, ultimately, climate impact.

Virtually developing of automotive power systems is currently experiencing increasing significance due to elevated vehicular electrification and automation of driving functions. The analysis of system-inherent disturbances requires accurate simulation models for both short-term transients or long-term driving cycles. The electrical behavior of electromechanical actuators such as brake or steering highly depends on the mechanical environmental interaction being dependent many variables. This contribution presents a methodology to extract abstracted models of machine driven actuators on the basis of an electric steering. The dynamics of a complex electromechanical model are investigated using pulse response analysis for differentiated operation points. The obtained model reduction is implemented in a frequency-dependent equivalent circuit.

Owing to the complexity of the sector, industrial activities are often represented with limited technological resolution in integrated energy system models. In this study, we enriched the technological description of industrial activities in the integrated energy system analysis optimisation (IESA-Opt) model, a peer-reviewed energy system optimisation model that can simultaneously provide optimal capacity planning for the hourly operation of all integrated sectors. We used this enriched model to analyse the industrial decarbonisation of the Netherlands for four key activities: high-value chemicals, hydrocarbons, ammonia, and steel production. The analyses performed comprised 1) exploring optimality in a reference scenario; 2) exploring the feasibility and implications of four extreme industrial cases with different technological archetypes, namely a bio-based industry, a hydrogen-based industry, a fully electrified industry, and retrofitting of current assets into carbon capture utilisation and storage; and 3) performing sensitivity analyses on key topics such as imported biomass, hydrogen, and natural gas prices, carbon storage potentials, technological learning, and the demand for olefins. The results of this study show that it is feasible for the energy system to have a fully bio-based, hydrogen-based, fully electrified, and retrofitted industry to achieve full decarbonisation while allowing for an optimal technological mix to yield at least a 10% cheaper transition. We also show that owing to the high predominance of the fuel component in the levelled cost of industrial products, substantial reductions in overnight investment costs of green technologies have a limited effect on their adoption. Finally, we reveal that based on the current (2022) energy prices, the energy transition is cost-effective, and fossil fuels can be fully displaced from industry and the national mix by 2050.

The iminoborane (HBNH) molecule selectively breaks a B═N bond of smaller diameter single-wall BN nanotubes (BNNTs) and expands a ring at their surface, either at the edges or at the middle of the tube. Density functional theory is used to test whether its organic counterpart HCCH can do the same with BNNTs. HCCH–BNNT complexes are identified and transition states located for these combination reactions. Also explored are possible reactions of HBNH with single-wall carbon nanotubes (SWNTs) and HCCH with SWNTs. Data suggest that B═N (C═C) bond breaking, followed by ring expansion at the surface, may be possible. Although [2 + 2]cycloaddition reaction seems possible for HBNH–BNNTs, a high energy barrier hinders the process for other combinations of reactants. Introduction of substituents to HBNH/HCCH may allow a facile process. In most cases of HCCH–BNNTs, HBNH–SWNTs, and HCCH–SWNTs, transition states are identified and suggest an electron-rich reactant might lower barrier heights to form stable complexes. R...

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed. The financial support from EPSRC for Liz Varga on project entitled "Transforming Utilities’ Conversion Points" (no. EP/J005649/1) is gratefully acknowledged.

The thermo-hydro-mechanical behaviour of a water-saturated cement-based heat store for domestic applications has been investigated. Numerical simulations have been employed to locate the critical regions during thermal loading, for which analytical solutions have been derived and validated by numerical simulations. The analytical solutions allow a fast screening of materials and design parameters in relation to the stresses induced by thermomechanical loading. Maximum stresses in the system have been quantified based on the thermomechanical properties of three heat exchanger materials selected by design engineers and of the filling material. Sensitivity analyses indicate that the stress distribution is very sensitive to the thermal expansion coefficients of the involved materials. The results of this study can serve as a guide line for the design of the present and similar heat storage systems. The analytical solution developed is a fast and robust method for the evaluation of stresses around heat exchangers embedded in a solid material and can serve as a tool for design optimisation.

The transition towards sustainable energy systems necessitates effective management of renewable energy sources alongside conventional grid infrastructure. This paper presents a comprehensive approach to optimizing grid management by integrating Photovoltaic (PV), wind, and grid energies to minimize costs and enhance sustainability. A key focus lies in developing an accurate scheduling algorithm utilizing Mixed Integer Programming (MIP), enabling dynamic allocation of energy resources to meet demand while minimizing reliance on cost-intensive grid energy. An ensemble learning technique, specifically a stacking algorithm, is employed to construct a robust forecasting pipeline for PV and wind energy generation. The forecasting model achieves remarkable accuracy with a Root Mean Squared Error (RMSE) of less than 0.1 for short-term (15 min and one day ahead) and long-term (one week and one month ahead) predictions. By combining optimization and forecasting methodologies, this research contributes to advancing grid management systems capable of harnessing renewable energy sources efficiently, thus facilitating cost savings and fostering sustainability in the energy sector.