Search Results (26,993)

Considering the global objective of carbon emission reduction, this paper focuses on optimizing the operational efficiency of grid-connected electric vehicles (EVs) and promoting sustainable energy integration and thus proposes a novel dual-incentive mechanism combining real-time pricing (RTP) and carbon quotas. A core of this study is the development of a bilevel programming model that effectively captures the strategic interaction between power suppliers (PS) and microgrid (MG) users. At the upper level, the model enables the PS to optimize electricity prices, achieving both revenue maximization and grid balance maintenance; at the lower level, it supports MGs in rational scheduling of EV charging/discharging, photovoltaic and wind energy (PWE) utilization, and load consumption, ensuring the fulfillment of user demands while maximizing MG profits. To address the non-convex factors in the model that hinder an efficient solution, another key is the design of a bilevel distributed genetic algorithm, which realizes efficient decentralized decision making and provides technical support for the practical application of the model. Through comprehensive simulations, the study verifies significant quantitative outcomes. The proposed algorithm converges after only 61 iterations, ensuring efficient solution performance. The average purchase price of electricity from the PS for the MG is USD 1.1, while the selling price of PWE sources from MG for the PS is USD 0.6. This effectively promotes the MG to prioritize the consumption of PWE sources and encourages the PS to repurchase the electricity generated by PWE sources. On average, carbon emissions decreased by approximately 300 g each time slot, and the average amount of carbon trading was around USD 8. Ultimately, this research delivers a practical and impactful solution for the development of MGs and the advancement of carbon reduction goals. Full article

The increasing share of renewable energy sources (RES) in modern power systems necessitates the development of efficient, large-scale energy storage technologies capable of mitigating generation variability. Liquid Air Energy Storage (LAES), particularly in its adiabatic form, has emerged as a promising candidate by leveraging thermal energy storage and high-pressure air liquefaction and regasification processes. Although LAES has been widely studied, the impact of ambient temperature on its performance remains insufficiently explored. This study addresses that gap by examining the thermodynamic response of an adiabatic LAES system under varying ambient air temperatures, ranging from 0 °C to 35 °C. A detailed mathematical model was developed and implemented in Aspen Hysys to simulate the system, incorporating dual refrigeration loops (methanol and propane), thermal oil intercooling, and multi-stage compression/expansion. Simulations were conducted for a reference charging power of 42.4 MW at 15 °C. The influence of external temperature was evaluated on key parameters including mass flow rate, unit energy consumption during liquefaction, energy recovery during expansion, and round-trip efficiency. Results indicate that ambient temperature has a marginal effect on overall LAES performance. Round-trip efficiency varied by only ±0.1% across the temperature spectrum, remaining around 58.3%. Mass flow rates and power output varied slightly, with changes in discharging power attributed to temperature-driven improvements in expansion process efficiency. These findings suggest that LAES installations can operate reliably across diverse climate zones with negligible performance loss, reinforcing their suitability for global deployment in grid-scale energy storage applications. Full article

The main goal of this research is the preparation of mechanically and mechanochemically activated Ti/B₄C/(±Ni) composite powders, which will constitute the source of reinforcement formation in the titanium powder matrix. For this purpose, two composite powders of the Ti/B₄C/(±Ni) type were obtained in the molar ratio Ti:B₄C = 5:1 and Ti:B₄C:Ni = 6:1:1, respectively, by mechanical milling (MM) in a high-energy planetary ball mill for up to 7 h. The morphological and structural characteristics of composite powders were determined by laser particle size analysis, scanning electron microscopy with energy-dispersive X-ray spectrometry, X-ray diffraction, and differential thermal analysis. By milling for up to 7 h, a good homogenization of B₄C in the Ti matrix occurs. Also, the addition of Ni leads to new phases of formation: NiTi and TiB₂. Full article

The RADFET VT06 developed by Varadis (Cork, Ireland), which is aimed at high-dose applications, mainly for spacecraft missions, has been characterized by low- and high-energy proton beams at two different facilities, the Accelerator National Centre (Sevilla, Spain) and the Paul Scherrer Institute (PSI) located in Villigen (Switzerland), using a reader unit system developed by the University of Granada (Spain). The devices have been characterized with proton energies of 1, 2, 3, 150, and 230 MeV, with accumulated doses from 130 to 512 Gy, where the RADFET was unbiased during the irradiation while the source voltage was measured before and after irradiation to monitor the radiation dose. Excellent linearity has been obtained with a minimum correlation factor R² of 0.996, with a sensitivity that can vary from (0.691 ± 0.007) mV/Gy for 1 MeV to (1.143 ± 0.023) mV/Gy for 230 MeV without any build-up layer. An excellent stability was found in the studied cases, with dispersion being lower than 4% after a dose accumulation higher than 500 and 200 Gy for protons of 1 and 3 MeV, respectively. The detectors demonstrated linear responses, very low sensitivity dispersion per set of samples, and excellent stability after irradiation. This shows that, with an appropriate readout system, the RADFET can become an excellent system for high-dose proton beams. Full article

As the adoption of electric vehicles increases, hybrid energy storage systems (HESS) combining batteries and supercapacitors mitigate the conflict between high energy capacity and power demand, particularly during acceleration and transient loads. However, frequent current fluctuations accelerate battery degradation, reducing long-term performance. This study presents a multi-objective Whale–Particle Swarm Optimization Algorithm (MOWPSO) for tuning the control parameters of a HESS composed of a lithium-ion battery and a supercapacitor. The proposed full-active configuration with dual bidirectional DC converters enables precise current sharing and independent regulation of energy and power flow. The optimization framework minimizes four objectives: mean battery current amplitude, cumulative aging index, final state-of-charge deviation, and an auxiliary penalty term promoting consistent battery–supercapacitor cooperation. The algorithm operates offline to identify Pareto-optimal controller settings under the Federal Test Procedure 75 cycle, while the selected compromise solution governs real-time current distribution. Robustness is assessed through multi-seed hypervolume analysis, and results demonstrate over 20% reduction in battery aging and approximately 25% increase in effective cycle life compared to battery-only, rule-based and metaheuristic algorithm strategies control. Cross-cycle validation under highway and worldwide driving profiles confirms the controller’s adaptability and stable current-sharing performance without re-tuning. Full article

Background/Objectives: The Fourth Italian National Food Consumption Survey (IV SCAI 2017–2020) provides updated and comprehensive data on the dietary habits of the Italian population. The study aimed to assess nutrient intakes and their main food sources among individuals aged 3 months to 74 years and to evaluate the adequacy of intakes against the Italian dietary reference values (DRVs). Methods: A nationally representative sample of 1969 participants were surveyed using two non-consecutive food diaries (ages 3 months–9 years) and 24 h recalls (ages 10–74 years) in accordance with the European Food Safety Authority’s EU Menu guideline. The multiple source method was used to estimate the usual intakes accounted for intra-individual variability. Nutrient adequacy was assessed against age- and sex-specific DRVs, and the main food sources of macro- and micronutrients were identified. Results: Energy intake was below DRVs for adults, particularly women, while protein intake exceeded recommendations across all ages, mainly from animal sources (67% of total). Total fat (38%En) and saturated fat (12%En) exceeded the recommendations, whereas carbohydrates (45%En) and dietary fibre were suboptimal. Vitamin D and calcium intake were markedly below DRVs for all age groups; iron inadequacy was prevalent among females. The main energy sources were cereals (39%), milk and dairy (15%), oils and fats (13%), and meat (10%). Vegetables and fruits were leading contributors to vitamins A and C, while meat, fish, and dairy provided vitamin B12 and D. Conclusions: The Italian diet remains cereal-based but shows nutritional imbalances: notably, excessive protein and fat intake and widespread deficiencies in vitamin D, calcium, iron, and fibre. These findings underline the need for targeted nutrition policies to realign dietary patterns with the national recommendations. Full article

This study is dedicated to analysing Ukraine’s transition to utilising renewable energy sources within the broader context of European integration, the decarbonization process, and the challenges significantly intensified by the full-scale Russia-Ukraine war in 2022. The objective of this study is to assess the effectiveness of managing Ukraine’s energy transition compared with selected European Union countries and to identify governance-related determinants of transition performance. The energy transition process is viewed as a cornerstone for ensuring national resilience, food security, and strategic post-war recovery planning. Despite significant growth rates in installed capacity, stimulated primarily by the implementation of green tariffs and foreign investments, Ukraine faces a range of systemic barriers. These include regulatory uncertainty, war-related infrastructure damage, and institutional fragility. To comprehensively assess managerial effectiveness, a comparative approach is employed, integrating data from the Energy Transition Index, the Worldwide Governance Indicators, and the Bertelsmann Transformation Index for the period 2015–2023. Within the scope of this research, a comparative analysis is conducted of Ukraine with Poland, Romania, and Slovakia, countries that share a post-socialist legacy and experience in European integration. The obtained results demonstrate that, although Ukraine exhibits a relatively high growth index for renewable energy development, at 54.56%, it significantly lags behind its regional partners in the parameters of quality of state governance, policy implementation consistency, and strategic coordination. It is concluded that managerial effectiveness, defined as the complex interplay between institutional capacity, policy stability, and implementation efficiency, is a decisive factor for the success of the energy transition. The research recommendations encompass enhancing regulatory transparency, strengthening strategic planning, and intensifying the attraction of international investments. Full article

Rapid integration of renewable energy sources poses a serious problem to the functionality of microgrids since they are characterized by underlying uncertainties and variability. This paper proposes a multi-stage approach to energy management to overcome these issues in a virtual power plant that combines heterogeneous microgrids. The solution is based on multi-agent deep reinforcement learning to coordinate internal energy pricing, microgrid scheduling, and virtual power plant-level energy storage system management. The proposed model autonomously learns the optimal dynamic pricing strategies based on load and generation dynamics, which is efficient in dealing with operational uncertainties and maintaining microgrid privacy due to its decentralized structure. The efficiency of the proposed solution is tested on comparative simulations based on real-world data, which prove the superiority of the framework to the traditional operation modes, which are isolated microgrids and the energy sharing scenarios. The findings prove that the suggested solution has a dual beneficial impact on both virtual power plant operators and involved microgrids, as it leads to profit enhancement and, at the same time, system stability. This process facilitates the successful balancing of conflicting interests among the stakeholders at a time when the operation is low-carbon. The study offers an overall solution to dealing with complicated multi-microgrids and brings substantial changes in the integration of renewable energy, as well as the distributed management of energy resources. The framework is a scalable model that can be used in the future perspective of power systems with high-renewable penetration to address both economic and operational issues of the contemporary energy grids. Full article

Against the backdrop of China’s transition from the eradication of absolute poverty toward the pursuit of common prosperity, equitable access to energy has become an increasingly important policy concern. This study develops a multidimensional framework to assess energy poverty from three interrelated dimensions: energy use level, energy structure, and energy capability. Using panel data for 30 provincial-level regions from 2005 to 2020, a provincial energy poverty index (EPI) is constructed based on the entropy-weighting approach. The spatial and temporal dynamics of energy poverty are examined using Moran’s I, the Dagum Gini decomposition, kernel density estimation, and spatial Markov chain analysis. The results reveal several key patterns. (1) Although energy poverty has declined nationwide, it remains pronounced in parts of western, central, and northeastern China. (2) Energy poverty exhibits significant spatial clustering, with high-poverty clusters concentrated in resource-dependent regions such as Shanxi and Inner Mongolia, while low-poverty clusters are mainly located along the eastern coast. (3) Regional disparities follow an inverted U-shaped trajectory over time, with east–west differences constituting the primary source of overall inequality. (4) Moreover, the evolution of energy poverty displays strong path dependence and club convergence. These findings highlight the need to strengthen dynamic monitoring and governance mechanisms, promote region-specific clean energy development, and enhance cross-regional coordination to support energy security and green transformation under China’s “dual-carbon” objectives. Full article

Brake particulate matter (PM) represents a significant portion of the non-exhaust related soot emissions from all forms of transport, posing significant environmental and health concerns. Euro 7 standards only regulate road automotive emissions, while no regulation covers train transportation. This study compares two brake PM samples from rail and automotive applications. Rail brake PM was generated from composite brake pads subjected to real-world urban rapid transit braking conditions, while automotive brake PM was generated using ECE brake pads and discs under World Harmonized Light-Duty Test Cycle (WLTC) conditions. Transmission electron microscopy (TEM) and energy-dispersive X-ray (EDX) analyses were performed to assess PM morphology and composition. Both samples showed PM in coarse (10–2.5 µm), fine (2.5–0.1 µm), and ultrafine (<0.1 µm) size ranges, with angular flakes in automotive PM and rounded particles in rail PM. The rail PM exhibited a uniform size distribution, with a mean Feret diameter of 1 µm. In contrast, the automotive PM shifted toward larger particles, with ultrafine PM representing only 4% of the population. Excluding carbon and oxygen, automotive PM was dominated by iron (6 at.%) and magnesium (1 at.%). Rail PM showed lower iron (0.6 at.%) and higher aluminium (0.7 at.%) and calcium (0.8 at.%), with a broader non-C/O composition. This study tackles source-specific PM features, thereby supporting safer and more efficient non-exhaust emissions regulations. Full article

To further enhance economic efficiency and optimize energy conservation and emission reduction performance, an optimized energy management strategy (EMS) tailored for the hybrid power system of rubber-tyred gantry cranes is proposed. Wavelet packet decomposition (WPD) was employed as the signal processing approach, and this method was further integrated with EMS for hybrid power systems. Through a three-layer progressive architecture comprising WPD frequency–domain decoupling, fuzzy logic real-time adjustment, and PSO offline global optimization, a cooperative optimization mechanism has been established in this study between the frequency-domain characteristics of signals, the physical properties of energy storage components, and the real-time and long-term states of the system. Firstly, the modeling and simulation of the power system were conducted. Subsequently, an EMS based on WPD and limit protection was developed: the load power curve was decomposed into different frequency bands, and power allocation was implemented via the WPD algorithm. Meanwhile, the operating states of lithium batteries and supercapacitors were adjusted in combination with state of charge limits. Simulation results show that this strategy can achieved reasonable allocation of load power, effectively suppressed power fluctuations of the auxiliary power unit system, and enhanced the stability and economy of the hybrid power system. Afterward, a fuzzy controller was designed to re-allocate the power of the hybrid energy storage system (HESS), with energy efficiency and battery durability set as optimization indicators. Furthermore, particle swarm optimization algorithms were adopted to optimize the EMS. The simulation results indicate that the optimized EMS enabled more reasonable power allocation of the HESS, accompanied by better economic performance and control effects. The proposed EMS demonstrated unique system-level advantages in enhancing energy efficiency, extending battery lifespan, and reducing the whole-life cycle cost. Full article

The electricity–hydrogen–electricity conversion chain offers an effective solution for integrating clean energy into the grid while addressing multiple grid control requirements. Moreover, multiregional, interconnected, and integrated energy systems (IESs) can significantly increase overall energy utilization efficiency and operational flexibility through spatiotemporal coordination among diverse energy sources. However, few researchers have considered these two aspects in a unified framework. To address this gap, a low-carbon economic dispatch model and control strategy for a multiregional hydrogen-blended IES are proposed in this work. The model is constructed based on a system architecture that incorporates electricity–hydrogen–electricity conversion links while accounting for source–load uncertainties and peak shaving requirements. We solve the resulting distributed nonconvex nonlinear optimization problem using the alternating direction method of multipliers (ADMM). Furthermore, we analyze how uncertainty factors and peak shaving needs affect the maximum allowable hydrogen blending ratio in the gas grid, as well as the corresponding dynamic blending strategy. Our findings demonstrate that the proposed multiregional hydrogen-blended integrated energy system, with dynamic hydrogen blending control, significantly enhances the capacity for clean energy integration and reduces carbon emissions by approximately 12.3%. The peak-shaving demand is addressed through a coordinated mechanism involving electrolyzers (ELs), gas turbines (GTs), and hydrogen fuel cells (HFCs). This coordinated mechanism enables hydrogen fuel cells to double their output during peak hours, while electrolyzers increase their power consumption by approximately 730 MW during off-peak hours. The proposed dispatch model employs conditional risk measures to quantify the impacts of uncertainty and uses economic coefficients to balance various cost components. This approach enables effective coordination among economic objectives, risk management, and system performance (including peak shaving capability), thereby improving the practical applicability of the model. Full article

Wave energy is gaining momentum as a viable and environmentally sustainable source of renewable power, with the potential to contribute significantly to the global energy mix. Central to wave energy conversion is the power take-off system, where electromagnetic generators play a crucial role in determining overall system performance, reliability, and efficiency. This paper provides a review of wave energy conversion devices and classifies the main power take-off mechanisms. It evaluates and compares key generator types based on their performance under wave energy conditions. Among these, Permanent Magnet Synchronous Generators have demonstrated strong potential due to their high efficiency, power density, and suitability for low-speed direct drive configurations typical of wave environments. The review presents a detailed analysis of advanced permanent magnet generator topologies, focusing on structural designs, control methods, and wave-specific trade-offs. It also investigates hierarchical control strategies, where high-level decisions are based on wave conditions and low-level control ensures accurate generator operation. The paper aims to provide a broad perspective on the design and control of electromagnetic generators for wave energy systems. Full article

Background: In silico diet design may represent a flexible approach in diet planning and adaptation to a variety of conditions, and it may take advantage from standard diet(s) as reference template(s). The concept of standard diet(s) is, however, quite vague and poorly defined. Objective: The aim of this work was to develop templates of omnivorous (OMN), lacto-ovo-vegetarian (LOV), and vegan (VEG) standard diets, based on data produced in European countries and the USA in 1998–2024, and adapted to an adult subject requiring ≈2200 kcal/day. Design: Online databases were used to identify papers containing experimentally determined (EXP) data of daily food frequencies, or reporting dietary recommendations (REC) from (inter)national agencies or specific studies. Only sources reporting quantitative food data (as g/day) in OMN, LOV, and VEG diets were accepted. Results: Out of >200 publications initially identified, 24 EXP and 20 REC sources complied with the selection criteria. By combining the EXP and REC data within each diet type, total meat intake in OMN diet was 99 ± 36 g/day. Total dairy food in LOV diets (247 ± 107 g/day) tended to be lower (by ≈15%, NS) than in OMN diets (272 ± 100). In VEG diets, total vegetal foods were ≈33% greater than in LOV (p < 0.01), and ≈1-fold greater than in OMN ones (p < 0.00001). Total cereal foods were similar in OMN (272 ± 122) and LOV (264 ± 122) diets, but tended to be ≈20–25% greater in VEG diets (to 326 ± 103, NS). Potato and other starchy foods were not different among the three diets. Legumes and pulses were modestly but insignificantly greater in LOV (55 ± 25) and VEG diets (112 ± 137) than in OMN ones (31 ± 24). Soy products were greater in VEG than in LOV diets. The “nuts, seeds, and spreads” food group in VEG diets was ≈3-fold greater than in OMN (p < 0.0005), and ≈90% greater than in LOV diets (p < 0.002). Fruit intake in VEG diets was ≈14% (p = NS) and ≈ 60% (p < 0.005) greater than in LOV and OMN diets, respectively. Finally, the “protein and energy-rich vegetal alternatives” food group in LOV and VEG diets was ≈5- to ≈6-fold greater than in the OMN diet (p ≤ 0.001). Conclusions: The exclusion of meat, fish, and egg in LOV diets is not compensated by increased dairy foods, rather by more total vegetal foods and protein-rich vegetal alternatives. VEG diets replace animal-derived proteins mainly with nuts, seeds, and spreads, soy products and protein-rich vegetal alternatives. On the basis of these data, templates to design “standard” OMN, LOV, and VEG diets are proposed. Full article

The article presents an extended methodology for calculating the LENI energy efficiency index for building lighting, taking into account an additional reactive power component—LENI_Q. The proposed methodology takes into account the influence of the power factor (cos φ), the nature of the receivers, and the presence of constant lighting intensity (CTE) systems. Based on the analysis of two public buildings (schools)—one without a photovoltaic installation and the other equipped with a PV system—it was shown that reactive power can be a significant component of the energy balance. For the facility without PV, a value of LENI_Q = 58.4 kvarh/m²·year was obtained, while for the facility with PV—4.75 kvarh/m²·year, which indicates a more than tenfold reduction in reactive energy thanks to the use of automation and renewable energy sources. A comparison with model values for different cos φ enabled an additional assessment of the efficiency of lighting installations. The aim of this study is to develop an extended methodology of the LENI indicator by introducing a reactive power component LENI_Q, enabling a comprehensive assessment of lighting energy efficiency. Full article