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This study delves into the dynamic evolution of solids content in a pilot-scale through air drying tissue machine, aiming to enhance comprehension and refine optimization strategies for tissue manufacturing. It focuses on development of solids content throughout the process. Analyzing the interaction between process parameters and solids content provides deeper insights into water removal dynamics. The research employs solid contents monitoring techniques in pilot scale, offering a detailed view of solids content evolution from the wet web's inception to the final tissue product. It significantly highlights the impact of key parameters, particularly pulp refining, on solids content across all positions of the pilot machine. Additionally, the study emphasizes the influence of vacuum system configurations, identifying the relationship between energy expended in the vacuum system and evaporation energy. Furthermore, the results indicate that compression and air displacement dewatering in vacuum boxes are less speed-sensitive compared to heat-driven evaporation in the TAD- and Yankee cylinders. Solid contents at all positions in the tissue machine correlates between various dewatering elements. Optimizing site-specific dewatering and evaporation strategies can potentially save drying energy in the Yankee drying phase which hold promise for enhanced energy and resource utilization, aligning with demands for sustainable manufacturing practices. [ABSTRACT FROM AUTHOR]

It is well-known that energy consumption is increasing around the world on a daily basis. In the construction sector, a highly effective solution for reducing energy consumption involves exploring both modern and traditional buildings designed to adapt to climate changes. One promising approach is to use paper waste and bio-sourced materials as the basis for insulation. The purpose of this study was to improve the sustainability of buildings by using recycled waste materials that have a positive impact on the environment, people, and the economy. A novel insulating material composed of recycled paper waste and Ampelodesmos mauritanicus leaves and fibers was developed and used in non-load-bearing elements. The paper waste was transformed into pulp and mixed with the bio-sourced materials to create a composite material that exhibits excellent insulation properties. The resulting material is lightweight, durable, and cost-effective. Furthermore, different mechanical and thermal analyses were performed on specimens with varying dosage ratios. The results showed that the developed material has good thermal insulation, with a value of 0.027 W/m.K. [ABSTRACT FROM AUTHOR]

A novel approach for paper drying using airborne ultrasound technology is presented. A unique experimental setup is developed, and a systematic study is conducted using 23 factorial design of experiments and Analysis of Variance. Three controlling factors are considered in the experiments including the initial moisture content, basis weight and refining condition. The outcome of the experiments is compared to a previous work on direct-contact ultrasonic drying of paper. The results confirm that similar to direct-contact, for airborne ultrasonic drying, the basis weight/thickness of the sample is the most important factor in ultrasonic drying and it is followed by the effect of initial moisture content. Using linear regression model, a correlation for predicting the total time of ultrasonic drying is provided. Quality of the dried samples is evaluated, and the permeability measurements confirmed the effect of pore characteristics on ultrasonic drying. The analysis for energy consumption reveals that airborne ultrasonic drying is more efficient at higher moisture contents. [ABSTRACT FROM AUTHOR]

Overwintering insects are facing energetic challenges because of food shortage, low temperature, and desiccation stress. Paper wasps of the genus Polistes overwinter as mated adults (gynes) in hibernacula protecting them from predation, snow, and rain but barely from low environmental temperature. In different climates, they face differing overwintering temperature regimes, and therefore they may differ in their energy use. We investigated how much of energy resources built up until autumn is used during diapause dormancy in natural hibernacula by measuring lipid, glycogen, and free carbohydrate content in autumn and early spring in Polistes dominula from temperate European (Austrian) and warm Mediterranean (Italian) climate and Polistes gallicus from Mediterranean climate. Winter energy consumption amounted to ~ 339 and ~ 310 J per wasp in the Austrian and Italian Polistes dominula populations. The smaller Italian Polistes gallicus consumed ~ 247 J. This amounts to 2.62, 2.35, and 1.79 J per day. Of this, the energy demand was mainly fuelled by lipids (84%, 93%, and 90%, respectively), but glycogen stores contributed also considerably (16%, 6%, and 9%). Free carbohydrates decreased only by 0.7%, 1%, and 0.8%. While fat stores seem still sufficient in spring, the wasps depleted most of their carbohydrates. The energy reserves of 396, 400, and 147 J per wasp remaining in spring in the three populations seem sufficient to fuel rest or simple brood care activities for a whole summer but restrict foraging flights to a few hours (~ 3.5–6 h). Results suggest that energy supply might become challenging in expected future climate scenarios. [ABSTRACT FROM AUTHOR]

In order to study the cutting performance of the straight edge hob and reduce the cutting power consumption model of the straight edge hob, this paper takes the cutting power of the straight edge hob as the minimum goal, and establishes the mathematical model of the optimization design of the straight edge hob based on the composite optimization method. The mathematical model is solved by MATLAB software. At the same time,the mowing characteristics of a roller blade were studied by investigating the relationship between the hob and the coordination of variables such as rotational speed and roller diameter with the mowing parameters. The parameter analysis of straight edge hob before and after structural parameter optimization is generated, and a design method is proposed based on this. After defining the objective function and constraint conditions, the influence of structural parameters on the power consumption and efficiency of the hob was determined by optimising the complex method; this could significantly adjust the hob parameters to lower its power consumption. The energy consumption of the optimized design is reduced by 11.1 % compared with the original scheme, and the optimization effect is remarkable. The results show that the best working parameters of the hob are cutting speed of 1000 r/min, sliding cutting angle and grinding edge angle of 25~30°. Moreover, practical tests demonstrated the feasibility of using the proposed method to design the straight edge hob to improve mowing performance and hob stability. This study can provide parameter foundation and an optimization method for lowering chopping power consumption of the roller mower blade. [ABSTRACT FROM AUTHOR]

In the field of intelligent transportation, the planning of traffic flows that meet energy-efficient driving requirements necessitates the acquisition of energy consumption data for each vehicle within the traffic flow. The current methods for calculating vehicle energy consumption generally rely on longitudinal dynamics models, which require comprehensive knowledge of all vehicle power system parameters. While this approach is feasible for individual vehicle models, it becomes impractical for a large number of vehicle types. This paper proposes a digital model for vehicle driving energy consumption using vehicle speed, acceleration, and battery state of charge (SOC) as inputs and energy consumption as output. The model is trained using an optimized CNN-BiLSTM-Attention (OCBA) network architecture. In comparison to other methods, the OCBA-trained model for predicting PHEV driving energy consumption is more accurate in simulating the time-dependency between SOC and instantaneous fuel and power consumption, as well as the power distribution relationship within PHEVs. This provides an excellent framework for the digital modeling of complex power systems with multiple power sources. The model requires only 54 vehicle tests for training, which is significantly fewer than over 2000 tests typically needed to obtain parameters for power system components. The model's prediction error for fuel consumption under unknown conditions is reduced to 5%, outperforming the standard error benchmark of 10%. Furthermore, the model demonstrates high generalization capability with an R2 value of 0.97 for unknown conditions. [ABSTRACT FROM AUTHOR]

There is an urgent need for energy sources with lower environmental impacts to dispose of waste generated by human activities. In this context, a holistic analysis of energy use of waste from agricultural and forestry activities, animal excreta, urban solid waste and sewage, waste from the pulp and paper industry and charcoal in Brazil is presented. Based on a bibliographic review, the current Brazilian panorama is presented in figures giving, a vision of national potential for harnessing bioenergy from this theoretical and technical potential. The QGIS3.24.2 Tisler geoprocessing tool was used to generate potentiality maps from census data of microregions and municipalities available in the IBGE database (2022) and in the Geocentric Reference System for the Americas (SIRGAS 2000). The results of map analysis by micro‐regions of the primary energy from agricultural residues highlight sugar cane, corn and soybeans crops, followed by wastewater and animal excreta. They stood out amont the studied sources of biomass with technical potentials of 53.17, 15.23 and 6.81 GW, respectively. With these results, it is concluded that Brazil could enable around 75 GW installed power, reusing all biomass, potentially 12.5 PJ, without considering the 16 GW already installed from sugarcane and paper black liquor plants. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ultrafine marble dust waste particles were obtained using the top–down approach. • Waste and by-products had positive effect on dry grinding of stone wastes. • It is economically feasible, also environmentally friendly. • These obtained ultrafine particles can be used effectively mineral filler in many areas. Waste management in marble processing plants is a considerable problem in countries with developed stone industries and trade. Research on the utilization of stone waste in different fields is still continuing. However, there are few studies on using this stone waste from processing plants as mineral fillers. Moreover, no study in the literature has investigated the influence of grinding aids on stone properties. The current research is the first to compare of the efficiency of different grinding aids on the waste calcitic and dolomitic marble in the production of mineral fillers. The objective of this work is to research the impacts of waste and by-products on the dry grinding of stone wastes as grinding aids in a vertical stirred media mill. The results were assessed in terms of various parameters: product particle size, powder flowability, material coating on the grinding media, and energy consumption. Remarkably, the study showed that the use of any of the grinding aids tested enhanced the grinding process in comparison with the no-aid condition. The best product fineness value was achieved with pomace oil followed by the by-product glycerin, among the grinding aids tested in both samples. Moreover, a higher media coating reduction and the highest energy saving were achieved with pomace oil. The most significant and lowest increase in the fluidity index was achieved with pomace oil and paper wastewater, respectively. Additionally, the Fourier transform infrared spectroscopy (FTIR) performed to reveal the interaction between particle surfaces and grinding aids demonstrated the activity of pomace oil and glycerin polar functional groups on particle surfaces. The analysis of the agglomeration phenomenon with SEM (scanning electron microscopy) micrographs showed that particle agglomeration could be eliminated with the pomace oil. Thermogravimetric analysis (TGA) was used to investigate changes in the mass of the samples' due to temperature changes. With this study, a significant contribution will be made to the ecosystem using waste marble powder whose storage problematic. [ABSTRACT FROM AUTHOR]

Aluminum powder particle size (D50) is quite important for how to improve the energy release level and formulation design of aluminized explosives. In this paper, four experimental samples of CL-20-based aluminized explosives with aluminum powder particle sizes including 2, 13, 24, and 43 μm were designed. The experiments were carried out through an underwater explosion tank and compared with explosives containing lithium fluoride of the same particle size. The results show that the burning of aluminum powder promoted the shock wave propagation and bubble expansion. Aluminized explosives have a lower and then higher decay rate than lithium fluoride-containing explosives. For the experimental range of aluminum powder particle sizes, with an increase in D50, the peak shock wave pressure first increased and then decreased, reaching the maximum at 24 μm; the shock wave and loss energy gradually increased, while the bubble energy, energy utilization, and underwater explosion total energy all gradually decreased. To a certain degree, the energy output structure can be regulated by adjusting the D50 under the premise of constant total energy of explosives. The experimental results improve our understanding of how D50 affects the underwater explosion parameters of aluminized explosives, which is of great significance for improving their energy utilization. [ABSTRACT FROM AUTHOR]

In this paper, a wideband metasurface-loaded (MTS-L) rectenna system is proposed to capture electromagnetic (EM) energy at arbitrary azimuth angles. The radiation patterns of different modes in the original MTS configuration are analyzed using the characteristic mode theory, and potential modes with omnidirectional radiation are screened out. By the arrangement of patches, the roundness performance of the radiation pattern can be ameliorated, and the omnidirectional characteristic is obtained over a wide frequency band. Subsequently, the surface current density of the selected mode is carefully and artificially designed to facilitate probe excitation as well as refrain from introducing complex power-combining networks. A wideband rectifier circuit is designed as the load of the proposed antenna. Eventually, measured results show that it operates from 4.6 to 9.6 GHz with a fractional bandwidth of 70.4%, and the peak system efficiency is 52.2%. The proposed system demonstrates excellent potential for wireless power transmission and EM energy harvesting in indoor environments. [ABSTRACT FROM AUTHOR]

The research assessed waste-based briquettes consumption compared to conventional fuels in the Andes. Laboratory tests were conducted together with on-field analysis in Colquencha (Bolivia). The laboratory study shows that the performances of briquettes are better in terms of PM2.5 (933.4 ± 50.8 mg kg−1) and CO emissions (22.89 ± 2.40 g kg−1) compared to animal dung (6265.7 ± 1273.5 mgPM2.5 kg−1 and 48.10 ± 12.50 gCO kg−1), although the boiling time increased due to the lower fuel consumption rate and firepower compared to shrubs. The social survey organized with 150 Bolivian citizens suggested that low-income households are not able to pay for an alternative fuel: about 40% would pay less than 4 USD per month, while methane use for cooking is positively correlated with the income level (r = 0.244, p < 0.05). On field analysis suggested that local cookstoves are not appropriate for briquettes combustion since indoor air pollution overcomes 30 ppm of CO and 10 mgPM2.5 m-3. On balance, local small manufactures can be the main target for selling waste-based briquettes to reduce shrubs and wood consumption. However, briquettes production costs seem not yet competitive to natural easy-to-obtain fuels (i.e., animal dung). The research encourages the use of cellulosic and biomass waste-based briquettes in the Andean area for cooking, heating, or manufacturing and strongly advises policy-makers to introduce economic incentives for the recovery of secondary raw materials. • Analysis of waste-based briquettes use in Andean areas were conducted. • Laboratory analysis, social surveys, and on field evaluations are the methods. • Briquettes can be employed for reducing about 30% of the conventional fuels. • The research encourages the employment of waste-based briquettes in the Andes. • Incentives to briquettes production and consumption should be introduced. [ABSTRACT FROM AUTHOR]

This paper examines the potential of solar and hydrogen (H 2) energy-based hybrid energy systems for residential applications. The growing need for energy and the demand for sustainable energy sources have led to the development of integrated energy systems that combine renewable energy resources to meet energy needs. This paper overviews recent studies on hybrid energy systems for on-grid and off-grid residential utilizations. It discusses the system configuration and components of hybrid energy systems, including solar panels, electrolyzers, fuel cells (FC), and batteries. It also covers the technical optimization of integrated energy systems, including sizing, control strategies, and economic analysis. The key findings of this review paper indicate that hybrid energy systems can offer dependable and sustainable energy for residential applications. Through numerical analyses, the optimal dimensioning of the system elements and control strategies can significantly enhance the system's performance and lower the cost of energy. This study also highlights the challenges and opportunities for integrating hybrid energy systems within residential applications. Overall, it provides in-depth perspectives on the possibilities inherent in solar and hydrogen energy-based hybrid energy systems for residential applications. The findings can guide future research and the advancement of hybrid energy systems for sustainable energy solutions. • Comprehensive review on solar and hydrogen-based residential applications. • Holistic approach to system configuration, optimization, and economics. • Detailed analysis of interconnected components enhancing system efficiency. • Unique focus on real-world residential applications and scenarios. • Broad applicability across diverse geographical regions. [ABSTRACT FROM AUTHOR]

In the context of 'energy shortage', developing a novel energy-based power system is essential for advancing the current power system towards low-carbon solutions. As the usage duration of lithium-ion batteries for energy storage increases, the nonlinear changes in their aging process pose challenges to accurately assess their performance. This paper focuses on the study LiFeO4(LFP), used for energy storage, and explores their performance degradation mechanisms. Furthermore, it introduces common battery models and data structures and algorithms, which used for predicting the correlation between electrode materials and physical parameters, applying to state of health assessment and thermal warning. This paper also discusses the establishment of digital management system. Compared to conventional battery networks, dynamically reconfigurable battery networks can realize real-time monitoring of lithium-ion batteries, and reduce the probability of fault occurrence to an acceptably low level. [ABSTRACT FROM AUTHOR]

This paper introduces a structural design which has superior energy harvesting ability. The proposed structure is based on the ability of most periodic structures to prohibit elastic waves from propagating in a specific frequency range of the phonon band gap. By leading into acoustic black hole (ABH) units and utilizing the energy concentration characteristics of the ABH structure, the filtering effect can be made more significant. These two characteristics can produce significant strain and energy localization, which is conducive to energy harvesting. In this paper, we obtained ABH unit capable of producing broadband gaps by adjusting the geometric parameters of the ABH structure, and chose a cantilever as the research object for energy harvesting, by applying a piezoelectric patch on the unit located near the fixed end to gain a broader application in the actual situation. The results show that the beam combining the energy concentration characteristics of band gap and ABH structure has a significant improvement in energy harvesting efficiency. Optimization on the parameters of ABH unit shows that the band gap characteristic of the periodic ABH structure can further optimize the energy harvesting efficiency of practical energy harvesters, and opens up a new possibility of energy harvesting of ABH structure. [ABSTRACT FROM AUTHOR]

This paper addresses the question whether energy consumption variables and the disaggregation of output matter in the context of efficiency analysis of container terminals. While it is obvious that the energy consumption of refrigerated cargo is higher than the energy consumption of non-refrigerated cargo, this work investigates whether those differences show in an overall efficiency analysis of terminals. This would point to a potentially important input for efficiency measures, to be considered in future productivity and efficiency analysis of terminals. Starting with a discussion on theoretical concepts and variable selection for measuring the energy dimension of terminal efficiency, this is the first paper that applies data envelopment analysis (DEA) comparing results with and without energy consumption, as well as differentiating productive outputs (dry and reefer container handling). The results reveal how the output disaggregation leads to substantially different efficiency scores and are a first step to show the relevance of output disaggregation and the inclusion of the energy variables as inputs in container terminal efficiency studies. [ABSTRACT FROM AUTHOR]

Energy saving has become a key concern of metro systems to reduce operating costs and meet the requirements of sustainable development. Energy-efficient timetabling, an effective way to reduce traction energy consumption, has gotten much attention in recent decades. However, limited research about energy-efficient timetabling simultaneously considered realistic speed profiles and the influence of train loads, which change greatly in different sections and significantly affect energy consumption. Therefore, this paper proposes an energy-efficient timetabling approach to improve regenerative energy utilization based on varying train loads and realistic speed profiles for bidirectional metro lines. First, based on the operational and safety constraints, this paper constructs an integer energy-efficient timetabling model where dwell times and nonuniform headways are taken as decision variables. Besides, the turnaround process is also considered to ensure rolling stock circulation efficiency. Sectional passenger volumes are employed to determine the varying train loads. Energy consumption is calculated based on realistic speed profiles. Owing to the complexity of the model, an improved adaptive large neighborhood search (ALNS) algorithm is designed to solve this model according to its characteristics. Finally, numerical examples are conducted based on the practical data from Shanghai Metro Line 17. The results indicate that the proposed approach effectively solves the energy-efficient timetabling problem with varying train loads and realistic speed profiles for bi-directional metro lines. The approach is suitable for off peak hours and can reduce energy consumption effectively, and the reduction is up to 11.9% for the presented cases. The improved ALNS algorithm can find good solutions within reasonable times in different cases. Moreover, compared with the widely used genetic algorithm in the literature, the improved ALNS algorithm is more efficient in solving the proposed energy-efficient timetabling problem in different cases. [ABSTRACT FROM AUTHOR]

This paper investigates the connection between climate change and energy security in Europe and provides empirical evidence that these issues are the two faces of the same coin. Using a panel of 39 European countries during the period 1980–2020, the empirical analysis presented in this paper indicates that increasing the share of nuclear, renewables, and other nonhydrocarbon energy and improving energy efficiency could lead to a significant reduction in carbon emissions and improve energy security throughout Europe. Accordingly, policies and reforms aimed at shifting away from hydrocarbons and increasing energy efficiency in distribution and consumption are key to mitigating climate change, reducing energy dependence, and minimizing exposure to energy price volatility. [ABSTRACT FROM AUTHOR]

New‐type professional farmers are new‐type rural talents with scientific and cultural literacy and professional knowledge of agriculture under the background of rural revitalization. The new type of professional farmers is of great significance for accelerating agricultural modernization and promoting the construction of a powerful modern socialist country. In the process of cultivating new types of professional farmers in rural areas, it is necessary to break through the previous informatization constraints of poor information flow, and give full play to the role of advanced information technology to promote the sustainable economic development. This paper proposes a new type of professional farmer cultivation platform based on edge computing architecture to improve the cultivation efficiency of new type of professional farmers, so as to better promote the development of rural informatization. Aiming at the challenges of energy consumption under the edge platform architecture, this paper proposes a dynamic scheduling method for semi‐online tasks for edge computing platforms. In order to evaluate the effectiveness of the algorithm, the method in this paper is compared with the classic scheduling algorithm, and simulated and verified on the CloudSim platform. Experimental results show that the proposed method outperforms other algorithms in the task completion time metric. With the expansion of task scale, more energy consumption can be saved by using the algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

Multi-intelligent vehicles forming and maintaining a specific formation during traveling can save energy consumption and road resources, and improve traffic efficiency and driving safety. Centered around the Cooperative Vehicle Infrastructure(CVI) framework of the Internet of Vehicles(IOV), this paper delves into the control objectives of forming multi-intelligent vehicle formation, explores the theory of formation shaping process, and investigates the optimization of energy consumption in the formation shaping process. First, the clustering design is used to take the kinematic process of vehicles as an optimization process from the bionics, taking the instantaneous consumption indexes as the optimization objectives. Then, optimize the acceleration inputs of the vehicle formation process using the improved Artificial Fish Swarm Algorithm(AFSA), and iterate with the clustering algorithm part, so as to realize the formation shaping process with energy consumption as the optimization objective. Finally, ajoint simulation platform built by Simulation of Urban Mobility (SUMO) and Python is used for simulation verification, and the results show that the formation shaping process can be realized and achieve the optimal energy consumption under the scenarios proposed in this paper, thus verifying the validity of the clustering model of vehicle formation shaping and the energy consumption optimization algorithm designed in this paper. [ABSTRACT FROM AUTHOR]

With the development of energy technology, hydrogen is gradually becoming widely used. China is also rapidly developing its own hydrogen energy industry in an effort to accomplish the "dual carbon target'. Hydrogen from methane is one of the mainstream sources, of which hydrogen from methane cracking is the decomposition of methane into hydrogen and solid carbon, with the solid carbon also having a high economic value. In particular, this technology does not emit carbon dioxide, which is very friendly to the environment, but it cannot avoid larger energy consumption. In contrast, hydrogen production from methane cracking driven by solar energy not only combines the characteristics of no CO 2 emission, but also greatly reduces the consumption of primary energy, which is the future development trend of hydrogen production from methane. This paper provides a brief overview of the various technological pathways for methane to hydrogen production in the context of China's actual development, focusing on the current status of the development and application of solar methane cracking to hydrogen production technologies at home and abroad. Among them, this paper mainly discusses the characteristics of solar reactors of different sizes and structures, and summarizes the results of related optimization studies. Meanwhile, the application of catalysts in solar reactors and the problem of carbon deposition are analyzed, and the practical application of solar methane cracking hydrogen production system is outlined. Finally, the future development of solar methane cracking hydrogen production technology is prospected from the national situation of China. [Display omitted] • Solar methane cracking for hydrogen can reduce emissions and energy consumption. • The current state of research on solar reactors is summarized. • Solar methane cracking requires higher performing catalysts. • Providing insights into the future development of solar methane cracking in China. [ABSTRACT FROM AUTHOR]

In this paper, a proper noun “Region” is used for nm‐scale n‐type dopant‐rich region in p‐type Si crystal. Using this Region, certain solar cells have been assumed. By resonance absorption between photon energy and potential barrier of the Region, the cell can absorb most photons for visible light frequency without passing loss or thermal loss. This light absorption mechanism is different from conventional band gap absorption. Despite this benefit, output voltage is anticipated to decline according to the principle of detail balance. To control the decline, two methods are proposed in this paper. Theoretical energy conversion efficiencies for several cases are calculated with an ideal condition. The calculation result is over 70% as a theoretical value. [ABSTRACT FROM AUTHOR]

Fuel cell electric buses (FCBs) have proven to be a technically viable solution for transportation, owing to various advantages, such as reliability, simplicity, better energy efficiency, and quietness of operation. However, large-scale adoption of FCBs is hindered by the lack of extensive and structured infrastructure and the high cost of clean hydrogen. Many studies agree that one of the significant contributors to the lack of competitiveness of green hydrogen is the cost of electricity for its production, followed by transportation costs. On the one hand, to reduce the investment cost of the electrolyzer, high operating hours should be achieved; on the other, as the number of operating hours decreases, the impact of the electricity costs declines. This paper presents an innovative algorithm for a scalable hydrogen refuelling station (HRS) capable of successfully matching and identifying the most cost-efficient levelized cost of hydrogen (LCOH) produced via electrolysis and connected to the grid, based on the HRS components' cost curves and the hourly average electricity price profile. The objective is to identify the least-cost range of LCOH by considering both the electric energy and the investment costs associated with a hydrogen demand given by different FCB sizes and electrolyzer rated powers. In addition, sensitivity analyses have been conducted to quantify the technology cost margins, and a cost comparison between the refuelling of an FCB fleet and the recharging infrastructure required for an equivalent fleet of Battery Electric Buse (BEB) has been performed. An LCOH of around 10.5 €/kg varying from 12 €/kg (2 FCB) to 10.2 €/kg (30 FCB) has been found for the best-optimized configurations. The final major conclusion of this paper is that FCB technology is currently not economically competitive. Still, a cost contraction of the electric energy price and the electrolyzer capital investment would lead to a 50% decrease in the LCOH. Furthermore, increasing renewable energies into the grid may shift the electricity cost curve, resulting in higher prices when the BEB recharging demand is more significant. This impact, in addition to the peak power load and longer recharging times, might contribute to bridging the gap with FCBs. • Techno-economic model for the sizing of an HRS with grid-connected electrolyzer. • The widespread diffusion of H2 technology in mobility needs both reliability and cost-effectiveness. • Investigation of various electrolysers rated powers and fuel cell buses fleet size. • An action on both CAPEX and OPEX would lead to potential cost margins improvement. • It is found that the best configuration that balances the CAPEX and OPEX coincides with an LCOH ranging from 12 to 10 €/kg. [ABSTRACT FROM AUTHOR]

The European Union, in pursuit of the goal of reducing emissions by at least 55% by 2030 and achieving climate neutrality by 2050, is deploying different actions, with industry decarbonization as a key strategy. However, increasing electricity demand requires an intensification of energy generation from clean technologies, and the energy system's expansion is hindered by renewable generation's climatic dependencies and the imperative for substantial electrical infrastructure investments. Although the transmission grid is expected to grow, flexibility mechanisms and innovative technologies need to be applied to avoid an overwhelming growth. In this context, this paper presents a thorough assessment, conducted within the FLEXINDUSTRIES project, of the flexibility potential across seven energy-intensive industries (automotive industry, biofuel production, polymer manufacturing, steel manufacturing, paper mills, pharmaceutical industry, and cement production). The methodology followed during the analysis entails reviewing the state-of-the-art existing flexibility mechanisms, industries' energy markets engagement, and technical/operational readiness. The results highlight the feasibility of the proposed actions for enabling energy market flexibility through demand-response programs, quantifying energy opportunities, and pinpointing regulatory and technical barriers. [ABSTRACT FROM AUTHOR]

With the increasing use of renewable energy sources and decentralized power systems, certain challenges have emerged in meeting consumers' electrical energy demands. The intermittent nature of renewable energy generation means that it cannot always align with consumers' needs, resulting in periods of excess energy production when it is not required. To bridge this gap between production and consumption, energy storage systems are necessary. This paper defines the work of an isolated microgrid, which consists of renewable sources (wind and PV) for energy production, households with electric vehicles as consumers, and a combined storage system. This storage system is made from batteries, hydrogen storage, and a control system that defines the best use of the storage. Stored energy is utilized through fuel cells to generate electricity for consumption when renewable sources cannot meet the demand. This paper presents the principles of electrolysis and models of individual elements within such a system, as well as the definition and principle of control of the system functionality based on rules and conditions. The proposed control system aims to increase the energy storage lifecycle by deciding when and how to utilize which type of storage and define a self-sufficient microgrid based on renewable sources of production. An economic analysis of the storage part of the system was carried out in which the levelized cost of energy stored and the NPC of the storage systems are calculated. A simulation of the system's operation is conducted using one-hour measurements of wind turbines, solar panels, and household consumption in Serbia. To analyze the system's behavior, a one-week time horizon is considered. [ABSTRACT FROM AUTHOR]

With the intensifying global energy crisis and environmental issues, the energy consumption and environmental impact of the construction sector have garnered significant attention. The development and application of green building materials have become crucial research areas. Traditional building materials cause substantial resource waste and environmental pollution during production, usage, and disposal. In contrast, green building materials based on thermodynamic principles, owing to their superior thermal performance and energy storage capabilities, have gradually gained attention. This paper aims to systematically optimize the thermal performance of green building materials through a research approach grounded in thermodynamic principles. The study consists of two main parts: first, constructing the control equations for the phase change thermal storage process of green building materials, and analyzing the thermodynamic characteristics during the phase change process in detail; second, conducting an in-depth analysis of the heat transfer process in phase change thermal storage green building materials to explore their thermal performance in practical applications. Despite extensive research on the thermal performance of green building materials, there are still shortcomings in the systematic analysis and optimization of material thermal performance, and existing research methods often fail to comprehensively and accurately reflect the actual thermal behavior of materials. This paper aims to provide a scientific basis for the optimized design of green building materials, further promoting their application and development in the construction field. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we study a UAV‐based fog or edge computing network in which UAVs and fog/edge nodes work together intelligently to provide numerous benefits in reduced latency, data offloading, storage, coverage, high throughput, fast computation, and rapid responses. In an existing UAV‐based computing network, the users send continuous requests to offload their data from the ground users to UAV–fog nodes and vice versa, which causes high congestion in the whole network. However, the UAV‐based networks for real‐time applications require low‐latency networks during the offloading of large volumes of data. Thus, the QoS is compromised in such networks when communicating in real‐time emergencies. To handle this problem, we aim to minimize the latency during offloading large amounts of data, take less computing time, and provide better throughput. First, this paper proposed the four‐tier architecture of the UAVs–fog collaborative network in which local UAVs and UAV–fog nodes do smart task offloading with low latency. In this network, the UAVs act as a fog server to compute data with the collaboration of local UAVs and offload their data efficiently to the ground devices. Next, we considered the Q‐learning Markov decision process (QLMDP) based on the optimal path to handle the massive data requests from ground devices and optimize the overall delay in the UAV‐based fog computing network. The simulation results show that this proposed collaborative network achieves high throughput, reduces average latency up to 0.2, and takes less computing time compared with UAV‐based networks and UAV‐based MEC networks; thus, it can achieve high QoS. [ABSTRACT FROM AUTHOR]

In this paper, the effects of different designs of pressure vessels on hydrodynamic parameters and the performance of seawater RO systems are investigated using computer simulations. Simulation results showed that designs using pressure vessels with four membranes in two-pass RO systems have a lower energy consumption, 5.29 and 0.33 kWh/m3 for the first and second passes, respectively, than those with two or three membranes. Also, designs No. 4 and No. 10 were the most efficient, 41 and 56% for the first and second passes, respectively, compared to other ones. The first and second passes required a lower permeate and feed pressure when using designs No. 3, No. 6, No. 9, and No. 12 where pressure vessels with two membranes were used. In addition, hybrid designs of two-pass RO systems were found to have the best efficiency and the lowest energy consumption among various other designs. Findings showed that in two-pass RO systems, the first pass consumes more energy than the second pass. Thus, the efficiency of the second pass in all designs of two-pass RO systems is more than the first pass. The results presented in this paper can be used to optimize the design of two-pass RO systems to ensure the optimum operation of such systems. [ABSTRACT FROM AUTHOR]

The software-defined network paradigm, ensembled with a wireless sensor network, has emerged as a promising phenomenon to enable multi-tasking, re-configuration, and scalability. Termed the software-defined wireless sensor network (SDWSN), it divides the network into two planes: data and control. The data plane consists of software-defined sensor nodes (SDSN) that sense monitoring activity and generate data. On the other hand, the control plane has controller/control Nodes (CN) which collect data from SDSN, perform data aggregation, and then transmit toward the sink node. These CNs consume more amount of energy as compared to SDSNs as they perform multiple tasks. Following this scenario, this paper proposes an energy-efficient multi-objective optimization approach to solve the CNs placement problem through a meta-heuristic algorithm by considering the nodes' location, energy, and load distribution. This paper presents a particle swarm optimization-based controller placement and re-placement (PSO-CPR) algorithm for SDWSN. The PSO-CPR elects SDSNs to become CN based on their distance, residual energy, and capacity in the network. Moreover, the placement of a CN rotates within the cluster to avoid its failure and balance energy consumption. The simulation results show improved CN placement with respect to the state-of-the-art algorithms in terms of average delay by 23.5–37.4%, energy consumption by 18.6–32.6%, and probabilistic load distribution by 17.7–54.1%. Moreover, the comparative study also indicates that PSO-CPR achieve promising result by reducing packet loss by 14.4–27.5% and network re-clustering period by 32.3–68.3% and enhance the network lifetime by 22.6–42.5%. [ABSTRACT FROM AUTHOR]

The three-dimensional (3D) path planning problem of an Unmanned Aerial Vehicle (UAV) considering the effect of environmental wind in a dense city is investigated in this paper. The mission of the UAV is to fly from its initial position to its destination while ensuring safe flight. The dense obstacle avoidance and the energy consumption in 3D space need to be considered during the mission, which are often ignored in common studies. To solve these problems, an improved Deep Reinforcement Learning (DRL) path planning algorithm based on Double Deep Q-Network (DDQN) is proposed in this paper. Among the algorithms, the random obstacle training method is first proposed to make the algorithm consider various flight scenarios more globally and comprehensively and improve the algorithm's robustness and adaptability. Then, the linear soft update strategy is employed to realize the smooth neural network parameter update, which enhances the stability and convergence of the training. In addition, the wind disturbances are integrated into the energy consumption model and reward function, which can effectively describe the wind disturbances during the UAV mission to achieve the minimum drag flight. To prevent the neural network from interfering with training failures, the meritocracy mechanism is proposed to enhance the algorithm's stability. The effectiveness and applicability of the proposed method are verified through simulation analysis and comparative studies. The UAV based on this algorithm has good autonomy and adaptability, which provides a new way to solve the UAV path planning problem in dense urban scenes. [ABSTRACT FROM AUTHOR]

The artificial potential field method has efficient obstacle avoidance ability, but this traditional method suffers from local minima, unreasonable paths, and sudden changes in heading angles during obstacle avoidance, leading to rough paths and increased energy consumption. To enable autonomous mobile robots (AMR) to escape from local minimum traps and move along reasonable, smooth paths while reducing travel time and energy consumption, in this paper, an artificial potential field method based on subareas is proposed. First, the optimal virtual subgoal was obtained around the obstacles based on the relationship between the AMR, obstacles, and goal points in the local environment. This was done according to the virtual subgoal benefit function to solve the local minima problem and select a reasonable path. Secondly, when AMR encountered an obstacle, the subarea-potential field model was utilized to solve problems such as path zigzagging and increased energy consumption due to excessive changes in the turning angle; this helped to smooth its planning path. Through simulations and actual testing, the algorithm in this paper demonstrated smoother heading angle changes, reduced energy consumption, and a 10.95% average reduction in movement time when facing a complex environment. This proves the feasibility of the algorithm. [ABSTRACT FROM AUTHOR]

High-pressure proton exchange membrane (PEM) water electrolysis for hydrogen production is a crucial method to achieve low energy consumption, high efficiency, minimal pollution, and seamless integration with storage systems. Despite its potential, the current application of high-pressure PEM water electrolysis faces several challenges. This paper provides a concise analysis of the research advancements in high-pressure PEM water electrolysis for hydrogen production, focusing on technical bottlenecks within high-pressure devices. It explores key issues such as gas cross-permeability, membrane degradation, membrane shedding, and hydrogen embrittlement encountered during high-pressure PEM water electrolysis for hydrogen production. Furthermore, this paper summarizes the latest research directions and proposed solutions based on existing findings, aiming to offer effective references for enhancing the safety, scalability, and industrial application of high-pressure PEM water electrolysis technology. [Display omitted] • State-of-art technology of high-pressure PEMWE for hydrogen production was discussed. • Gas cross-permeability, membrane degradation and hydrogen embrittlement of PEMWE were analyzed. • The latest research directions and proposed solutions for the PEMWE were presented. [ABSTRACT FROM AUTHOR]

The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry. [ABSTRACT FROM AUTHOR]

3D integration is one of the scalable multiprocessor design solutions. The main challenge in 3D design is temperature traps, especially in the upper layers and hot spots. The current studies present solutions for solving temperature and hotspot problems in topology, routing, and mapping levels. Accordingly, the characteristics of temperature-aware core mapping are beneficial for dealing with the challenges of 3D chips. In this paper, the core temperature is modeled based on processing, communication power, neighbor node temperature, distance from the heat sink, and hotspot node. To find the optimal solution, this paper proposes thermal-aware application mapping techniques using genetic algorithms and fuzzy logic to minimize peak temperatures in 3D network-on-chip (NoC) architectures. Fitness functions include the above parameters with the same weight (GSM) and the fitness function with fuzzy logic by considering the effect of distance from heat sink (GFM1) and heat sink distance and the number of neighbor's core (GFM2). Specifically, the fuzzy logic-based GFM1 algorithm demonstrates superior performance over the genetic algorithm-driven GSM approach in reducing power consumption and energy costs associated with inter-core communication traffic. Across the different traffic patterns tested, GFM1 consistently achieves lower energy expenditure, with reductions upward of 50% compared to GSM. This underlines the strengths of the fuzzy technique in enabling thermal-aware mapping to minimize chip temperatures in the presence of intensive workloads and communication. In essence, the key takeaway is that GFM1 outperforms GSM in the context of power and energy metrics linked to handling on-chip traffic between processing cores. [ABSTRACT FROM AUTHOR]

Research on resource management focuses on optimizing system performance and energy efficiency by distributing shared resources like processor cores, caches, and main memory among competing applications. This research spans a wide range of applications, including those from high-performance computing, machine learning, and mobile computing. Existing research frameworks often simplify research by concentrating on specific characteristics, such as the architecture of the computing nodes, resource monitoring, and representative workloads. For instance, this is typically the case with cloud systems, which introduce additional complexity regarding hardware and software requirements. To avoid this complexity during research, experimental frameworks are being developed. Nevertheless, proposed frameworks often fail regarding the types of nodes included, virtualization support, and management of critical shared resources. This paper presents Stratus, an experimental framework that overcomes these limitations. Stratus includes different types of nodes, a comprehensive virtualization stack, and the ability to partition the major shared resources of the system. Even though Stratus was originally conceived to perform cloud research, its modular design allows Stratus to be extended, broadening its research use on different computing domains and platforms, matching the complexity of modern cloud environments, as shown in the case studies presented in this paper. [ABSTRACT FROM AUTHOR]

With the rapid development of renewable energy and the increasing maturity of energy storage technology, microgrids are quickly becoming popular worldwide. The stochastic scheduling problem of microgrids can increase operational costs and resource wastage. In order to reduce operational costs and optimize resource utilization efficiency, the real-time scheduling of microgrids becomes particularly important. After collecting extensive data, reinforcement learning (RL) can provide good strategies. However, it cannot make quick and rational decisions in different environments. As a method with generalization ability, meta-learning can compensate for this deficiency. Therefore, this paper introduces a microgrid scheduling strategy based on RL and meta-learning. This method can quickly adapt to different environments with a small amount of training data, enabling rapid energy scheduling policy generation in the early stages of microgrid operation. This paper first establishes a microgrid model, including components such as energy storage, load, and distributed generation (DG). Then, we use a meta-reinforcement learning framework to train the initial scheduling strategy, considering the various operational constraints of the microgrid. The experimental results show that the MAML-based RL strategy has advantages in improving energy utilization and reducing operational costs in the early stages of microgrid operation. This research provides a new intelligent solution for microgrids' efficient, stable, and economical operation in their initial stages. [ABSTRACT FROM AUTHOR]

Low carbon operation of power systems is a key way to achieve the goal of energy power carbon peaking and carbon neutrality. In order to promote the low carbon transition of energy and power and the coordinated and optimized operation of distributed energy sources in virtual power plants (VPP), this paper proposes a framework for collaborative utilization of pumped storage–carbon capture–power-to-gas (P2G) technologies. It also constructs a multi-time scale low carbon economic dispatch model for VPP to minimize the internal resource operation cost of VPP in each time period. During the intraday scheduling stage, the day-ahead scheduling results as the planned output and the energy flow is then dynamically corrected at a short-term resolution in the framework. This allows for the exploration of the low-carbon potential of each aggregation unit within the virtual power plant. The results of the simulation indicate that the strategy and model proposed in this paper can effectively encourage the consumption of renewable energy sources, promote the low-carbon operation of power system power, and serve as a valuable reference for the low-carbon economic operation of the power system. [ABSTRACT FROM AUTHOR]

The introduction of fifth-generation (5G) mobile networks leads to an increase in energy consumption and higher operational costs for mobile network operators (MNOs). Consequently, the optimization of 5G networks' energy efficiency is crucial, both in terms of reducing MNO costs and in terms of the negative environmental impact. However, many aspects of the 5G mobile network technology itself have been standardized, including the 5G network slicing concept. This enables the creation of multiple independent logical 5G networks within the same physical infrastructure. Since the only necessary resources in 5G networks need to be used for the realization of a specific 5G network slice, the question of whether the implementation of 5G network slicing can contribute to the improvement of 5G and future sixth-generation networks' energy efficiency arises. To tackle this question, this review paper analyzes 5G network slicing and the energy demand of different network slicing use cases and mobile virtual network operator realizations based on network slicing. The paper also overviews standardized key performance indicators for the assessment of 5G network slices' energy efficiency and discusses energy efficiency in 5G network slicing lifecycle management. In particular, to show how efficient network slicing can optimize the energy consumption of 5G networks, versatile 5G network slicing use case scenarios, approaches, and resource allocation concepts in the space, time, and frequency domains have been discussed, including artificial intelligence-based implementations of network slicing. The results of the comprehensive discussion indicate that the different implementations and approaches to network slicing pave the way for possible further reductions in 5G MNO energy costs and carbon dioxide emissions in the future. [ABSTRACT FROM AUTHOR]

Underwater long-endurance platforms are crucial for continuous oceanic observation, allowing for sustained data collection from a multitude of sensors deployed across diverse underwater environments. They extend mission durations, reduce maintenance needs, and significantly improve the efficiency and cost-effectiveness of oceanographic research endeavors. This paper investigates the closed-loop depth control of actuation systems employed in underwater vehicles, focusing on the energy consumption of two different mechanisms: variable buoyancy and propeller actuated devices. Using a prototype previously developed by the authors, this paper presents a detailed model of the vehicle using both actuation solutions. The proposed model, although being a linear-based one, accounts for several nonlinearities that are present such as saturations, sensor quantization, and the actuator brake model. Also, it allows a simple estimation of the energy consumption of both actuation solutions. Based on the developed models, this study then explores the intricate interplay between energy consumption and control accuracy. To this end, several PID-based controllers are developed and tested in simulation. These controllers are used to evaluate the dynamic response and power requirements of variable buoyancy systems and propeller actuated devices under various operational conditions. Our findings contribute to the optimization of closed-loop depth control strategies, offering insights into the trade-offs between energy efficiency and system effectiveness in diverse underwater applications. [ABSTRACT FROM AUTHOR]

This paper reviews the integration of blockchain technology, smart microgrids, and the energy market, highlighting its potential to revolutionize the energy industry. The integration of blockchain technology into smart microgrids aims to address challenges related to energy efficiency, reliability, and sustainability. The paper provides an overview of blockchain technology, emphasizing its transparency, immutability, and decentralization characteristics. It explores the concept of smart microgrids, which enable efficient energy management and integration of renewable energy sources. The combination of blockchain and smart microgrids offers several benefits such as increased efficiency, reduced transaction costs, enhanced security, and improved grid reliability. One of the key advantages of this convergence is the ability to facilitate peer-to-peer energy trading. Blockchain technology allows for transparent and auditable energy transactions, enabling direct trading between energy producers and consumers. This empowers prosumers to actively participate in the energy market, promoting renewable energy adoption and democratizing energy access. However, some challenges need to be addressed, including scalability, interoperability, and regulatory frameworks. Ongoing initiatives, projects, and pilot studies are exploring the implementation of blockchain-enabled smart microgrids, and case studies provide real-world examples of successful deployments. In conclusion, the convergence of blockchain, smart microgrids, and the electrical energy market has the potential to transform the energy industry. Collaboration among stakeholders, including energy companies, technology providers, regulators, and consumers, is crucial to fully realize the benefits of this integration. By leveraging blockchain and smart microgrids, the energy industry can pave the way for a more efficient, sustainable, and decentralized energy future. [ABSTRACT FROM AUTHOR]

Vertical management auditing reforms achieve the centralization of audit institutions. The centralized structure of the auditing institutions affects their performance. This paper verifies the positive effect of vertical management auditing reform on carbon productivity through a difference-in-differences method. The conclusion still holds after robustness tests. Moreover, the policy effects only make sense when government officials face low promotion pressure or high public scrutiny pressure. The mechanism analysis shows that the vertical management auditing reform can improve carbon productivity by strengthening environmental regulation, promoting industrial structure rationalization, and improving regional green innovation and energy efficiency. This paper enriches the research on the relationship between auditing centralization and carbon productivity. [ABSTRACT FROM AUTHOR]

The behaviors of local governments can affect the enforcement of environmental regulations. Environmental regulation can influence the behaviour of energy-intensive enterprises. This paper examines the relationship between local government competition, environmental regulation and the investment efficiency of high energy consuming firms using a basic panel regression and moderating effects model based on data from 2011-2020 for high energy consuming firms in China. The paper found that local government competition and environmental regulation can promote increased investment efficiency in energy-intensive firms in the short term. However, environmental regulation is not beneficial to investment efficiency in the long run. Local government competition plays a positive moderating role in the impact of environmental regulation on the investment efficiency of high energy consuming firms. There is a threshold effect on the role of local government competition. When the level of government competition exceeds 2.097, it has a negative impact on the investment efficiency. We further test for heterogeneity and we find that this promotion effect is also more obvious in areas with high environmental taxes and low marketability. Finally, we provide constructive suggestions for the development of government and the improvement of the investment efficiency of high energyconsuming firms. [ABSTRACT FROM AUTHOR]

Coal and biomass are important feedstocks for carbon energy from thermochemical conversion process. Fully understanding the analytical technology that characterizes the changes in physicochemical properties and structural characteristics of coal and biomass during the thermochemical reactions is a key prerequisite for the realization of appropriate utilization of energy fuels. Modern in-situ process analysis technology can accomplish the in-situ detection of the experimental process, and therefore reflect the experimental process more accurately. Moreover, it is developing towards automation, intelligentization, and comprehensive detection. Based on the characteristics of each detection technology, this paper summarizes the basic principles, application scope and performance characteristics of the three advanced in-situ process analysis technologies: hyphenated technology, synchrotron radiation, and online analysis. The practicability and accuracy of each detection technology in coal and biomass research are compared and analyzed, and its latest application and development trend are elucidated. These tools not only make up for the shortcomings of traditional detection techniques in characterizing the in-situ reaction, but also provide complementary information on molecular microscopic changes during fuel thermal conversion. This review paper can provide insights for relevant researchers in the selection of analytical techniques, and promote in-depth study on microcosmic mechanism of fuel conversion. [ABSTRACT FROM AUTHOR]

Under the background of green and low‐carbon transformation of industrial high‐energy‐consuming parks, in order to realize the coordinated development planning of energy and transportation under different peaking capacity requirements, this paper proposes a collaborative optimization model of industrial high‐energy‐consuming parks under green and low‐carbon. Firstly, by studying the energy balance mechanism between industrial load and new energy, an energy topology prior model of energy interaction in the next generation of industrial new energy power grid is constructed. Then, based on the probability characteristics of the equilibrium state of different regions in the high‐energy‐consuming industrial zone, combined with the prior knowledge of industrial load and low‐carbon power system, a collaborative development planning model of high‐energy‐consuming industrial parks is constructed. Finally, the proposed model is simulated. From the simulation results the authors can see the dynamic division model and solution algorithm of energy balance region established in this paper can effectively improve the energy balance ability of power grid, reduce peak shaving demand and use more renewable energy. [ABSTRACT FROM AUTHOR]