• Energy Research
• 2025-2025close
• Open Access close
• Closed Access close
• Open Source close
• Embargo close
• EU close
• ES close

| openaire: EC/H2020/963646/EU//HELIOS Lithium titanate oxide (LTO) batteries have been under intensive research due to their stability, safety, and rapid charging characteristics. Nevertheless, uncertainties as to LTO-batteries behavior when used as a raw material in battery recycling still exist. This study provides a grave-to-gate life cycle inventory for a hydrometallurgical battery recycling process in which Li-battery waste materials nickel manganese cobalt (NMC), LTO, and graphite were used as feed. The simulation showed that NMC cathode materials and lithium from both battery waste fractions could be recovered. In contrast, the titanium present within LTO cannot be recovered by the recycling process. Nevertheless, the life cycle assessment (LCA) of the process demonstrated clear benefits of recycling battery materials, highlighted by the decrease in global warming potential, acidification, eutrophication, and ozone depletion potential. Additionally, two routes for hazardous waste management were simulated to ascertain the environmental impacts of hazardous waste management within the recycling process. Peer reviewed

The required data was provided by Energex. The study received partial funding from the Ministry of Science and Innovation, Spain (Project ID: PID2020-115454GB-C21). Partial support of this work was through the LATENTIA project PID2022-140786NB-C31 of the Spanish Ministry of Science, Innovation and Universities (MICINNU) . This work presents a Temporal Convolution Network (TCN) model for half-hourly, three-hourly and daily-time step to predict electricity demand ( ) with associated uncertainties for sites in Southeast Queensland Australia. In addition to multi-step predictions, the TCN model is applied for probabilistic predictions of where the aleatoric and epistemic uncertainties are quantified using maximum likelihood and Monte Carlo Dropout methodologies. The benchmarks of TCN model include an attention-based, bi-directional, gated recurrent unit, seq2seq, encoder–decoder, recurrent neural networks and natural gradient boosting models. The testing results show that the proposed TCN model attains the lowest relative root mean square error of 5.336-7.547% compared with significantly larger errors for all benchmark models. In respect to the 95% confidence interval using the Diebold–Mariano test statistic and key performance metrics, the proposed TCN model is better than benchmark models, capturing a lower value of total uncertainty, as well as the aleatoric and epistemic uncertainty. The root mean square error and total uncertainty registered for all of the forecast horizons shows that the benchmark models registered relatively larger errors arising from the epistemic uncertainty in predicted electricity demand. The results obtained for TCN, measured by the quality of prediction intervals representing an interval with upper and lower bound errors, registered a greater reliability factor as this model was likely to produce prediction interval that were higher than benchmark models at all prediction intervals. These results demonstrate the effectiveness of TCN approach in electricity demand modelling, and therefore advocates its usefulness in now-casting and forecasting systems.

Decentralized multi-energy systems (MESs) are a key element of a future low-carbon energy supply. Here, we address the crucial role of grid-connected and off-grid MESs in achieving a low-carbon future, particularly relevant for regions like the Mediterranean with high renewable energy potential and carbon-intensive grid networks, using a mixed integer linear program for optimal economic and environmental MES design considering location-specific regulations. The results reveal that substantial cost (up to 30%, potentially saving 1.6 million) and greenhouse gas (GHG) emission reductions can be reached in Mediterranean regions with sufficient solar and wind energy resources currently relying on fossil fuel-based generators. However, our case study shows that the actual cost and emission reductions are most likely limited due to location-specific regulations (limiting cost savings to 0.8 million), especially those that constrain solar photovoltaic and onshore wind. Off-grid energy systems might be suitable decarbonization options in Mediterranean regions, to avoid absorbing current GHG-intensive power from the local power grid, under marginal cost increase (15%) compared to grid-connected cost optimization. However, off-grid MESs require substantial upfront investments and exhibit some environmental trade-offs, especially on material utilization, which could be overcome by balanced autonomy. Overall, truly sustainable and secure decentralized energy systems can only be reached by considering life cycle environmental impacts, social acceptance, and regulations during the design phase. Applied Energy, 377 ISSN:0306-2619 ISSN:1872-9118

A new energy-consistent discretization of the viscous dissipation function in incompressible flows is proposed. It is implied by choosing a discretization of the diffusive terms and a discretization of the local kinetic energy equation and by requiring that continuous identities like the product rule are mimicked discretely. The proposed viscous dissipation function has a quadratic, strictly dissipative form, for both simplified (constant viscosity) stress tensors and general stress tensors. The proposed expression is not only useful in evaluating energy budgets in turbulent flows, but also in natural convection flows, where it appears in the internal energy equation and is responsible for viscous heating. The viscous dissipation function is such that a consistent total energy balance is obtained: the 'implied' presence as sink in the kinetic energy equation is exactly balanced by explicitly adding it as source term in the internal energy equation. Numerical experiments of Rayleigh-Bénard convection (RBC) and Rayleigh-Taylor instabilities confirm that with the proposed dissipation function, the energy exchange between kinetic and internal energy is exactly preserved. The experiments show furthermore that viscous dissipation does not affect the critical Rayleigh number at which instabilities form, but it does significantly impact the development of instabilities once they occur. Consequently, the value of the Nusselt number on the cold plate becomes larger than on the hot plate, with the difference increasing with increasing Gebhart number. Finally, 3D simulations of turbulent RBC show that energy balances are exactly satisfied even for very coarse grids; therefore, we consider that the proposed discretization forms an excellent starting point for testing sub-grid scale models.