Search Results (2,238)

The growing penetration of renewable energy sources requires resilient microgrids capable of providing stable and continuous operation. Hybrid energy storage systems (HESS), which integrate hydrogen-based storage systems (HBSS), battery storage systems (BSS), and supercapacitor banks (SCB), are essential to ensuring the flexibility and robustness of these microgrids. Accurate modelling of these microgrids is crucial for analysis, controller design, and performance optimization, but the complexity of HESS poses a significant challenge: simplified linear models fail to capture the inherent nonlinear dynamics, while nonlinear approaches often require excessive computational effort for real-time control applications. To address this challenge, this study presents a novel state space model with linear variable parameters (LPV), which effectively balances accuracy in capturing the nonlinear dynamics of the microgrid and computational efficiency. The research focuses on a high-voltage DC bus microgrid architecture, in which the BSS and SCB are connected directly in parallel to provide passive DC bus stabilization, a configuration that improves system resilience but has received limited attention in the existing literature. The proposed LPV framework employs recursive linearisation around variable operating points, generating a time-varying linear representation that accurately captures the nonlinear behaviour of the system. By relying exclusively on directly measurable state variables, the model eliminates the need for observers, facilitating its practical implementation. The developed model has been compared with a reference model validated in the literature, and the results have been excellent, with average errors, MAE, RAE and RMSE values remaining below 1.2% for all critical variables, including state-of-charge, DC bus voltage, and hydrogen level. At the same time, the model maintains remarkable computational efficiency, completing a 24-h simulation in just 1.49 s, more than twice as fast as its benchmark counterpart. This optimal combination of precision and efficiency makes the developed LPV model particularly suitable for advanced model-based control strategies, including real-time energy management systems (EMS) that use model predictive control (MPC). The developed model represents a significant advance in microgrid modelling, as it provides a general control-oriented approach that enables the design and operation of more resilient, efficient, and scalable renewable energy microgrids. Full article

This study examines the alignment between the European Union’s climate policy rhetoric and the actual fossil fuel consumption behaviours of its Member States. By combining long-term and short-term time-series data with machine learning classification techniques, the analysis captures dynamic national energy trends and decarbonisation signals. Key innovations include the use of slope acceleration metrics and the identification of label reversals to detect volatility, acceleration, or stagnation in transition trajectories. The results show that, while some countries such as France and Denmark demonstrate consistent structural progress, others show deceleration or reversal, particularly in the use of gas and liquid fuels. This indicates that the relationship between EU-level policy ambition and national implementation is asymmetric and conditionally aligned. This study concludes that ongoing empirical monitoring and targeted diagnostics are essential to prevent conflating symbolic commitments with material change, and provides practical insights for improving climate policy accountability and adaptability across the EU. Full article

Background: Physical activity, sedentary behaviour, and sleep are interdependent components of the 24 h movement profile that may influence appetite control. While acute exercise can alter appetite perceptions and food reward, less is known about how reallocating time between daily behaviours affects appetite outcomes under free-living conditions. Methods: We applied isotemporal-substitution modelling in a cross-sectional study of 130 young, healthy, active adults. Accelerometer-derived estimates of sedentary time, light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and sleep were analysed in relation to energy intake (food diaries, laboratory meals), subjective appetite perceptions, appetite-related hormones (acylated ghrelin, PYY, leptin), and psychological traits, including food reward (Leeds Food Preference Questionnaire, LFPQ), food cravings (Control of Eating Questionnaire, CoEQ), and eating behaviour traits (Three-Factor Eating Questionnaire, TFEQ). Results: Reallocating 30 min/day of sedentary time to MVPA was associated with higher energy intake in free-living (+113 kcal/day, 95% CI: 34–192) and laboratory settings (+120 kcal/day, 95% CI: 55–185), along with greater postprandial hunger and prospective food consumption, reduced fullness, elevated fasting acylated ghrelin, and lower postprandial PYY. No associations were observed for reallocations to LPA or sleep. Furthermore, sedentary time reallocations were unrelated to leptin or psychological eating traits assessed by the LFPQ, CoEQ, or TFEQ. Conclusions: In this population, reallocating sedentary time to MVPA was linked to physiological and behavioural compensation consistent with elevated energy demands, whereas reallocating to LPA or sleep showed no associations. Trait-level eating behaviours were unaffected, suggesting MVPA influences appetite primarily through acute physiological rather than enduring cognitive or hedonic pathways. Full article

Global modern renewable energy based on geothermal, wind, solar, and marine resources has grown rapidly over the last decades despite low energy density, intermittent supply, and other qualities inferior to those of fossil fuels. What is the explanation for this growth? The main drivers of growth are assessed using economic theories and verified with statistical data. From the neo-classic viewpoint that focuses on price substitutions, the growth can be explained by the shift from energy-intensive agriculture and industry to labour-intensive services. However, the energy resources complemented rather than substituted for each other. In the evolutionary idea, investments supported by policies enabled cost-reducing technological change. Still, policies alone are insufficient to generate the growth of modern renewable energy as they are inconsistent across countries and in time. From the behavioural perspective that is preoccupied with innovative entrepreneurs, the value addition of electrification can explain the introduction of modern renewable energy in market niches, but not its fast growth. Instead of these mono-causalities, the growth of modern renewable energy is explained by technology diffusion during the pioneering, growth, and maturation phases. Possibilities that postpone the maturation are pinpointed. Full article

A personalized framework for smart home automation is introduced, utilizing machine learning to predict user activities and allow for the context-aware control of living spaces. Predicting user activities, such as ‘Watch_TV’, ‘Sleep’, ‘Work_On_Computer’, and ‘Cook_Dinner’, is essential for improving occupant comfort, optimizing energy consumption, and offering proactive support in smart home settings. The Edge Light Human Activity Recognition Predictor, or EL-HARP, is the main prediction model used in this framework to predict user behavior. The system combines open-source software for real-time sensing, facial recognition, and appliance control with affordable hardware, including the Raspberry Pi 5, ESP32-CAM, Tuya smart switches, NFC (Near Field Communication), and ultrasonic sensors. In order to predict daily user activities, three gradient-boosting models—XGBoost, CatBoost, and LightGBM (Gradient Boosting Models)—are trained for each household using engineered features and past behaviour patterns. Using extended temporal features, LightGBM in particular achieves strong predictive performance within EL-HARP. The framework is optimized for edge deployment with efficient training, regularization, and class imbalance handling. A fully functional prototype demonstrates real-time performance and adaptability to individual behavior patterns. This work contributes a scalable, privacy-preserving, and user-centric approach to intelligent home automation. Full article

Voltage supraharmonics present in the electrical grid can trigger chain reactions in grid-connected household and industrial power supplies equipped with Power Factor Correction (PFC). A single source of voltage supraharmonics may significantly increase the current in switching devices with PFC, leading to higher-amplitude disturbances throughout the electrical network. When addressing issues in a real low-voltage (LV) grid, it was observed that activation of a single device emitting supraharmonics caused oscillating currents across all feeders connected to the transformer’s busbars, matching the frequency of the supraharmonic source. To investigate this phenomenon further, the grid voltage containing supraharmonics was replicated in a controlled laboratory environment and used to supply various power electronic devices. The laboratory results closely mirrored those observed in the field. Supraharmonics present in the supply voltage caused current oscillations in the power electronic devices at the same frequency. Moreover, the amplitude of the observed current oscillations increased with the amplitude of the injected supply voltage supraharmonics. In some cases, the root mean square (RMS) value of the current drawn by the power electronic devices doubled, indicating a substantial impact on device behaviour and potential implications for grid stability and energy efficiency. Full article

This study evaluated the effects of including 0, 150, 300, 450, and 600 g/kg of dry matter (DM) of spineless cactus (SC; Nopalea cochenillifera Salm-Dyck) plus urea and ammonium sulphate (UAS) (9:1), replacing Tifton-85 hay (Cynodon spp. cv. Tifton 85), on nutrient intake and digestibility, feeding behaviour, water intake, and rumen dynamics. Five rumen-fistulated and cannulated crossbred wethers were randomly assigned in a 5 × 5 Latin square design. A roughage:concentrate ratio of 70:30 was supplied. Organic matter (OM) and metabolisable energy (ME) intakes showed quadratic responses (p < 0.05), with maximum values of 1157 g/day and 14.50 MJ/day estimated at SC+UAS levels of 364 and 410 g/kg DM, respectively. Apparent digestibilities of DM, OM, and non-fibre carbohydrates, as well as water excretion in faeces and degradation rate of DM, increased with SC+UAS inclusion (p < 0.05). Indigestible neutral detergent fibre (NDF) intake, feeding and rumination times, voluntary water intake, NDF degradation and passage rates, as well as the indigestible NDF passage rate, decreased with SC+UAS inclusion (p < 0.05). In wethers’ diets with a roughage:concentrate ratio of 70:30, a roughage combination of SC+UAS and Tifton-85 hay in a 41:29 ratio is recommended to maximise ME intake. Full article

Animal farming produces large volumes of underutilised by-products, such as poultry feathers (PF), often discarded in landfills or incinerated, causing environmental concerns. Transforming such residues into valuable energy carriers aligns with sustainable waste-to-energy (WtE) management. Pyrolysis represents a versatile thermochemical pathway for converting organic wastes into gaseous, liquid, and solid fuels. This study investigates slow pyrolysis of PF, lignite (LG), and their blends at pilot scale using a uniquely designed, patent-pending reactor bridging laboratory research with industrial practice. Experiments were conducted at 20 °C·min⁻¹, temperatures of 500–800 °C, and pressures from 0.1 to 1.0 MPa. PF pyrolysis produced mainly gas (70.1%), suitable for energy recovery, with smaller fractions of char (15.3%) and oil (14.6%). LG yielded predominantly char (59.9%), with lower gas (32.4%) and oil (7.7%) outputs. Co-pyrolysis revealed limited synergistic effects. Rising temperature promoted gas formation, reduced char, and improved its calorific value through carbon enrichment. Elevated pressure enhanced char yield and unexpectedly increased hydrogen content, suggesting complex thermochemical behaviour. The results confirm the scalability of laboratory findings and highlight pyrolysis as a practical WtE pathway for valorising protein-rich residues and low-rank coals, contributing to cleaner, more sustainable energy systems. Full article

Agricultural residues such as maize byproducts and discarded cocopeat substrates are abundant but underutilised biomass resources. Improving their fuel quality requires densification, such as pelletisation, combined with thermochemical upgrading. In this study, pellets were prepared by blending cocopeat and maize residues at weight ratios of 9:1, 7:3, and 5:5, followed by torrefaction at 220, 250, and 280 °C. Their fuel characteristics were evaluated through mass yield, elemental and proximate analyses, chemical composition, calorific value, combustion indices, and grindability. Results showed that increasing maize residue content reduced ash and fuel ratio but increased volatile matter, while cocopeat-rich pellets provided higher fixed carbon and lignin contents, improving thermal stability. Torrefaction significantly enhanced calorific value (up to 21.83 MJ/kg) and grindability, while increasing aromaticity. However, higher torrefaction severity decreased the combustibility index but improved volatile ignitability, indicating a trade-off between ignition behaviour and stable combustion. An optimal balance was observed at 250 °C, where energy yield and combustion performance were maximised. This study demonstrates the feasibility of valorising discarded cocopeat substrates, blended with maize residues, into renewable solid fuels, and provides practical guidance for optimising blending ratios and torrefaction conditions in waste-to-energy applications. Full article

The chemical and structural similarity of calcium orthophosphates to hard tissues in the human body makes them suitable as biomaterials for bone implants, cements, injection systems, etc., for bone regeneration and reconstruction. Tetracalcium phosphate (Ca₄(PO₄)₂O, TTCP) is a promising component for such biomaterials due to its high calcium content and alkaline nature. The former makes it suitable for promoting mineralization, while the latter supports neutralization of the acidic environment, helping to prevent inflammation and improve the biocompatibility of the materials. However, it is the least used calcium orthophosphate due to the difficulties in its synthesis. This study examines the effect of high-energy mechanochemical activation on the phase evolution, particle morphology, and thermal behaviour of equimolar mixtures of Ca(OH)₂ and CaHPO₄, with the aim of optimizing precursor conditions for the synthesis of (TTCP)-rich ceramic materials. The results demonstrate that mechanochemical activation effectively induces structural disorder, promotes the formation of amorphous and nanocrystalline phases, and facilitates subsequent phase transitions upon calcination. The combined use of solid-state NMR, XRD, TEM, and thermal analysis provides a comprehensive understanding of the transformation pathways. Ultimately, 24 h of activation under the experimental conditions was identified as optimal for producing a precursor with a favorable phase composition for obtaining TTCP-rich ceramic materials after calcination at 1350 °C. Full article

Scaffolds are temporary structures that workers usually use during building or repair work. These structures can be built in different shapes and types depending on the type of joints to which the beams and columns of the scaffolds are connected. Due to their temporary nature, they are very sensitive to vibration under dynamic or static actions, and this causes many accidents and unstable behaviours in them. This unstable behaviour has different reasons, including bracing conditions and slenderness of the columns, stiffness of joints and anchors, imperfections in the construction, damage and corrosion due to climate change, etc. This article aims to reanalyse the mechanical properties of scaffold joints and anchors and obtain some critical factors in the overall stability of the mentioned structures, including load-bearing capacity, initial stiffness, energy absorption, and ductility. To this aim, some recent research on scaffolds has been summarised and discussed, and then the failure mode and mechanical behaviour of the scaffolds in different types of scaffold joints and anchors have been estimated and considered from previous studies. Moreover, some mechanical properties, including ductility, initial stiffness, and energy absorption, have been estimated and developed based on the force-displacement curves of previous studies. The results highlight the crucial importance of the mechanical properties and behaviour of anchors and joints in estimating the behaviour and stability of scaffolds. The results also revealed that determining the mechanical characteristics of the mentioned elements can have a significant influence on the optimisation and design of scaffolds more accurately and predictably. Moreover, determining the mechanical properties of the anchors and joints can enhance our insights and understanding of how the mentioned parameters can improve the behaviour, stability, and safety of the scaffold structures. Full article

Compost barn systems are relevant alternatives to discussing production efficiency, welfare, and sustainability in dairy farming. However, studies evaluating these systems in different climates are still scarce, especially in subtropical climate zones. Here, we assess whether dairy cows’ behaviour, health and hygiene in compost barn systems are influenced by different climatic conditions and calving orders in Argentina’s central and extra-Pampean basins from the perspective of Bayesian inference. We evaluated dairy cows (n = 40) in a compost barn system simultaneously at two locations in Argentina: Rafaela and Salta. The following variables were evaluated: environmental factors, animal behaviour, respiratory rate, udder and hock hygiene, and locomotion degree of milking cows. There was a total of 10 primiparous cows and 10 multiparous cows at each location, randomly selected, which were in the first third of lactation (<90 DIM). Using Bayesian inference, we observed that Rafaela had a temperature-humidity index (THI) above 70, and Salta had a milder environment, with lower average temperature and higher relative humidity. Thus, climatic interference is evident in behaviour, triggering more behavioural and physiological mechanisms for heat abatement in primiparous females in Rafaela. At the same time, the mild conditions in Salta led to better thermal energy transfer by multiparous females compared to primiparous cows. This shows that the microclimate could interfere with the social hierarchy of cows when they are under heat stress. These findings highlight the importance of considering both calving orders and climate when designing management strategies for dairy systems. Full article

The use of light at night may contribute to the inappropriate or excessive use or presence of artificial light known as light pollution. Light pollution wastes huge amounts of electricity and money and contributes to global warming as well as having significant impacts on wildlife. There is a recognition that many of the issues that drive light pollution should be engaged by local, often pragmatic, governments. Lighting policies need to manage light pollution while also providing the intended services. To achieve this, local governments could develop policies and interventions in terms of three main considerations: functionality, technology, and the behaviours that comprise social usage. To determine to what extent this is being done, the lighting policies of the local governments of greater Melbourne are investigated, along with the related Australian Standards associated with lighting. Very few of the local governments in greater Melbourne had an explicit policy addressing light pollution and none of them considered the likelihood of behavioural issues such as rebounds in energy use. The results of this study suggest that policies that reduce light pollution, with controls to avoid behavioural complications such as rebound effects, should reduce costs for local governments and reduce greenhouse gas emissions. Full article

Water utilities are increasingly turning to digital solutions to promote conservation behaviours among households; however, traditional campaigns often suffer from limited personalisation, low interactivity, and modest long-term impact. Though computer-tailored and recommender systems (RSs) may offer personalisation, these systems lack a generalised framework that integrates behavioural theory with system design. This study addresses this research gap by introducing a novel framework that unites behavioural science, user experience (UX) design, and adaptive digital feedback to foster water-conscious practices at the residential level. The model draws on established behavioural theories, including the Theory of Planned Behaviour, the Transtheoretical Model, and Intervention Mapping, to ensure that tailored recommendations align with users’ psychological drivers, behavioural readiness, and daily routines. An industry-first prototype RS was developed and evaluated through an online survey (N = 300), assessing user perceptions of relevance, motivation, ease of use, and likelihood of action. The results reveal strong support for personalised suggestions, with 82% of respondents agreeing that personalised recommendations would help conserve water, and 76% indicating incentives would motivate adoption. This evidence indicates early acceptance and high potential impact. This study also addresses a critical research gap: no generic model previously existed to guide the integration of RSs with behaviour change interventions in water demand management. Broader implications are also discussed for applying the model to other sustainability domains such as energy use, waste reduction, and climate adaptation. Full article

Wind energy development is a key component in the transition to sustainable clean energy. Collision probability depends on turbine dimensions and species-specific behaviour, and understanding these relationships is essential for effective Environmental Impact Assessment (EIA). We applied a simulation approach based on flight-height distributions of a medium-sized diurnal raptor, the Common Buzzard (Buteo buteo). Long-term Global Positioning System (GPS) tracking data from an area with over 200 operating wind turbines in Northeastern Bulgaria were combined with Monte Carlo simulations of the Band collision risk model, and the predictions were validated against 18 years of systematic carcass searches under 114 turbines. Importantly, collision probability of the Common Buzzard was season-dependent, being greater during breeding and wintering, when flights occurred at lower altitudes, and lower during migration, when birds flew higher. Both the simulations and the field data supported an overall relatively low collision probability, indicating a high avoidance rate in this species. These findings suggest that wind energy planning should account for seasonal variation in flight behaviour and community composition, while long-term monitoring remains essential to ensure that cumulative impacts are adequately assessed. Full article