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Water Supply and Distribution Networks (WSDNs) offer underexplored potential for energy recovery. While many studies confirm their technical feasibility, few assess the long-term operational compatibility and economic viability of such solutions. This study evaluates the energy recovery potential of the Brussels Capital Region’s WSDN using four years (2019–2022) of operational data. Rather than focusing on available technologies, the analysis examines whether the real behavior of the network supports sustainable energy extraction. The approach includes network topology identification, theoretical power modeling, and detailed flow and pressure analysis. The Brussels system, composed of a Water Supply Network (WSN) and a Water Distribution Network (WDN), reveals strong disparities: the WSN offers localized opportunities for energy recovery, while the WDN presents significant operational constraints that limit economic viability. Our findings suggest that day-ahead electricity markets provide more suitable valorization pathways than flexibility markets. Most importantly, the study highlights the necessity of long-term behavioral analysis to avoid misleading conclusions based on short-term data and to support informed investment decisions in the urban water–energy nexus.

Wind resource assessment is a key factor for the development and implementation of wind farms with the purpose of generating green, eco-friendly and clean electricity. The Bolivian Andes, as a large dry region, represents an important source of renewable energy. However, the altitude and high wind energy resources of the Bolivian Andes require further knowledge and understanding of the wind energy resources. In this study, the GWA have been used to determine the total area available to install wind farms considering the protected areas, roads, cities and transmission lines. In addition, the Weather Research and Forecasting (WRF v3.8.1) model is employed to complement the results of the GWA based on the validation of WRF simulations with measurements from Qollpana wind farm. The main purpose is to estimate the wind power potential along the Bolivian Andes and its variability in time. The wind power simulations have been compared with the power generated by the Qollpana wind farm to verify the WRF’s performance. The wind power potential in the highlands of the Bolivian Andes could reach between 225 (WRF) and 277 (GWA) GW, distributed mainly over the Western and Eastern Cordillera of the Altiplano.

The Wallonia region of Belgium aims to transition to a modern hydrogen infrastructure. Given the relatively low density of hydrogen gas, it is important to understand its nature and behavior during transport through pipelines. This study aims to observe the pressure loss in pipelines due to surface roughness with H2 and other singular losses to find a solution to minimize the amount of pressure loss that occurs during transportation. This study involves numerical methods and gas equation models to determine the pressure loss. This analysis includes the properties of hydrogen gas, the pipeline material used, the friction factor, pipeline efficiency, and other relevant properties of hydrogen and pipelines. To address this challenge, the study integrates numerical fluid dynamics methods with structural modelling of pipeline walls. It accounts for long-term friction effects, erosion over several years, radial pressure gradients (mixing pressure drop), acceleration effects, and gravity influences, considering the non-ideal behavior of gaseous hydrogen (GH2). This study provides a systematic comparison between AGA-based analytical models and CFD simulations using a scaled pipeline approach, enabling reliable estimation of pressure losses in long-distance hydrogen pipelines. The proposed methodology integrates scaling, numerical validation, and CFD simulation to compute pressure losses in a hydrogen pipeline.

To avoid the geographical and topographical prerequisites of the conventional pumped hydro energy storage, the use of underground cavities as water reservoirs allows countries without steep topography, such as Belgium, to increase the potential of the energy storage capacity. Belgium abounds in disused mines and quarries convertible into water basins. In this article, two Belgian case studies are presented and discussed for their singularity. A slate quarry in Martelange is discussed in technical aspects proposing three operating scenarios. Moreover, a preliminary economic analysis of the underground pumped storage system and a greenhouse gas emission evaluation for the storage system’s lifetime are presented. The analysis for a 100 MW power plant estimates a total initial investment of over 12 million euros and two million of CO2 avoided over its lifetime. This article also proposes the use of the coal mine 500 m deep of Pérronnes-lez-Binche. The mine representation discussed here offers a high energy capacity, but the substantial head drop (from about 500 to 200 m) challenges the selection of the hydraulic turbomachinery. A 1D simulation computed in SIMSEN draws out the behaviour of the unusual hydraulic configuration of turbines in series.

According to the objectives of the Paris Agreement on climate change, the European energy supply must be fully decarbonised by 2050. For the power sector, a massive deployment of decentralised renewable technologies will be required to provide carbon-free electricity. However, other energy-intensive sectors such as gas, heat, transport, and the industrial sectors are more challenging to decarbonise, since they rely mostly on liquid and gaseous fuels. Consequently, exploiting the synergies between energy vectors in an integrated, multi-energy system represents an opportunity for a cost-effective transition towards a carbon-free economy. The objective of this study is to provide insights on the coupling of power and residential heat supply systems in a centralised multi-energy system by developing a linear program that optimises the interactions between energy carriers such as electricity, heat, hydrogen, biomass, and methane to minimise the long-term investments in generation and storage assets. The tool was then applied to a case study for a carbon-neutral energy supply in the Brussels-Capital Region in 2050, and conclusions were drawn on the potential of sector coupling to determine the optimal supply system configuration. The conclusions were that the central planning and operation of a coupled system could induce an annual cost reduction of ownership and operation of more than 23% compared to the individual management of the power and residential heat sectors. The cost reduction reaches 30.9% if one further considers centralised, district-level storage and distribution of heat in district heating systems. Finally, it was concluded that the intermittent renewable energy infeed required along biomass to meet the total energy demand is significantly reduced in the optimal scenario. Indeed, the installed capacities of PV and wind onshore can be respectively reduced by 31.9% and 55.8%.

At Université Libre de Bruxelles (ULB), research was performed on a 1 kN lab-scale Hybrid Rocket Motor (the ULB-HRM). It has a single-port solid paraffin fuel grain and uses liquid N2O as an oxidizer. The first Computational Fluid Dynamics (CFD) model of the motor was developed in 2020 and improved in 2021, using ANSYS Fluent software. It is a 2D axisymmetric, two-phase steady-state Reynolds-Averaged Navier–Stokes (RANS) model, which uses the average fuel and oxidizer mass flow rates as inputs. It includes oxidizer spray droplets and entrained fuel droplets, therefore adding many additional parameters compared to a single-phase model. It must be investigated how they affect the predicted operating conditions. In this article, a sensitivity analysis is performed to determine the model’s robustness. It is demonstrated that the CFD model performs well within the boundaries of its purpose, with average deviations between predicted and experimental values of about 1% for the chamber pressure and 5% for the thrust. From the sensitivity analysis, multiple observations and conclusions are made. An important observation is that oxidizer related parameters have the highest potential impact, introducing deviations of the predicted operating chamber pressure of up to 18%, while this is only about 6% for fuel-related parameters. In general, the baseline CFD model of the ULB-HRM seems quite insensitive and it does not suffer from an excessive or abnormal sensitivity to any of the major parameters. Furthermore, the predicted operating conditions seem to respond in a logical and coherent way to changing input parameters. The model therefore seems sufficiently reliable to be used for future qualitative and quantitative predictions of the performance of the ULB-HRM.

The computational advances and many times the lack of meteorological measurements in some regions of the world impulse the employment of numerical methods for covering this deficiency of data, and the parameterization is a key factor for use and operation of numerical weather prediction models. The Weather Research & Forecasting (WRF) as one of the most important models has been scarcely parameterized in the Bolivian Altiplano and Titicaca Lake. This work evaluates different physics models and focus the parameterization in the planetary boundary layer (PBL) schemes. This study evaluates the performance of land surface, radiation, convective and microphysics models using WRFv3.8.1. The results showed well‐prediction with NOAH, THOMPSON, and RRTMG for land surface, microphysics and radiation schemes, respectively. For the PBL parameterization QNSE, YSU, MYJ, MYNN, and QNSE‐FDDA were evaluated for wind speed, temperature, and mixing ratio. The minimum root mean square error were 2.025 m s−1 (QNSE‐FDDA) for wind speed, 1.721 K (YSU) for temperature, and 0.786 g kg−1 (MJY) for mixing ratio. In summary, the results have shown that QNSE scheme well‐predicts wind speed and water mixing ratio. However, using FDDA only wind speed and water mixing ratio were improved, and the temperature prediction becomes worse. These results suggest an underprediction of incoming solar radiation due to temperature and water mixing ratio were underestimated near the Titicaca Lake. Key Points Weather Research & Forecasting model is parameterized at high altitude conditions over the Titicaca Lake and land surface, radiation, convective, microphysics and PBL physics are considered The PBL parameterization shown QNSE scheme predicts satisfactorily the wind speed, temperature and water mixing ratio Using four‐dimensional data assimiliation with QNSE scheme improved the predictions

Energy imports and the transition to renewable energy sources are of critical importance in the current geopolitical context, which necessitates concrete actions to tackle the energy crisis at the European Union level. This study aimed to explore the impact of imported non-renewable energy resources on the EU-27 economy. It examined the correlations and causal relationships between the GDP, the GVA, R&D investments, and energy imports from 2000 to 2021. Data normality was assessed using the Shapiro–Wilk test, while Pearson’s test identified correlations between variables. Linear and multiple regression analyses were conducted to determine the effects of changes in independent variables on dependent variables. The study found a strong association between natural gas imports and the GDP, with increases in GDP leading to a more-than-fourfold rise in imports. Furthermore, a multiple regression analysis indicated that a 1% increase in R&D investments results in a 2.21% decrease in fossil fuel imports in 91.7% of cases. This suggests that R&D investments contribute to improved efficiency and the use of renewable energy sources.

The current evolution of the energy context and progress in sustainable energy technologies are enabling the development of new energy supply systems for the residential sector. However, the techno-economic assessment of such energy systems is not straightforward and depends, among others, on the building type, its thermal insulation rate, and user patterns, as well as on the climatic conditions or energy and technology prices. This study therefore aims to develop an investment model for a typical UK household energy system that is applied to a diversity of scenarios to highlight the sensibility of the output results over stochastic input data such as electricity and heat demands, ambient temperature, and global solar irradiation. This dwelling diversity dataset is generated using a thermal–electrical demand model that uses stochastic techniques to model uncertainty. This contribution concludes with a discussion on how end-users can effectively take part in the energy transition while minimizing their energy bill and potentially generate long-term revenues. The main results show stable economic performance, with capital expenditure (CAPEX) ranging from GBP 15,400 to GBP 17,000 and NPV from GBP 21,000 to GBP 26,000 over 2000 individual scenarios. This study also confirms the leveraging effect of policy instruments, such as subsidies, in shifting the optimal system design towards higher shares of renewable and storage technologies, further reducing the reliance on fossil fuels and the impact on distribution systems.

Empirical correlations are still fundamental in the modern design paradigm of axial turbines. Among these, the prominent Ainley and Mathieson correlation (Ainley D. and Mathieson G., 1951, “A Method of Performance Estimation for Axial-Flow Turbines,” ARC Reports and Memoranda No. 2974) and its derivatives, plays a crucial role. In this paper, the underlying assumptions of the aforementioned models are discussed by means of a descriptive review, whilst an attempt is made to enhance their reliability and, potentially, accuracy in performance estimations. Closer investigation reveals an intriguing misuse of the lift coefficient in the secondary loss. In light of this, an enhanced model that, notably, builds upon the Zweifel criterion and the vortex penetration depth concept is developed and discussed. The obtained accuracy is subsequently assessed through CFD computations, employing a database comprising 109 cascades. The results indicate a 50% probability of achieving the ±15% error interval, which is twice as good as the most recent Aungier model (Aungier R., 2006, “Turbine Aerodynamics: Axial-Flow and Radial-Inflow Turbine Design and Analysis”, ASME Press, New York). Furthermore, the reliability of the proposed model is demonstrated by a reconstruction of the Smith chart, on the one hand, and a performance analysis, on the other. The reconstruction exhibits contours that conform to the original. The results of the performance study are compared with the CFD solutions of eight cascades working in off design conditions and confirm the need of the additionally included turbine design parameters, such as the axial velocity and the meanline radius ratios.