[Objective] The purpose is to reveal the ways, extents and differences in how electricity consumption across various regions in China is influenced by temperature changes. [Method] Data on monthly total social electricity consumption and corresponding average temperatures for 29 provinces municipalities and autonomous regions from 2008 to 2020 were collected. Monthly meteorological electricity consumption and relative meteorological electricity consumption were calculated for each province, along with trend coefficients and correlation coefficients with concurrent temperatures. National distribution maps of these parameters were drawn, and their spatial differences and possible causes were analyzed. [Result] The results show that: (1) With rising summer temperatures, meteorological electricity consumption shows an increasing trend, especially significant in the eastern regions, Chongqing, and Shaanxi, while it is not significant in western and northern regions (such as Xinjiang, Qinghai, Gansu and Heilongjiang). The trend coefficients of relative meteorological electricity consumption also vary significantly among regions with a significant relationship, with an average trend coefficient of 1.5%/℃ in the three northeastern provinces, reaching 5%/℃ in Central China and Eastern China (excluding Fujian), and about 3%/℃ in Guangxi, Chongqing and Shaanxi. (2) Winter temperature changes also have a certain relationship with electricity consumption in various regions of China. When winter temperatures decrease, electricity consumption shows an increasing trend, and a significant relationship is observed in most areas of China, except for the southern coastal regions and Guizhou, with an extremely significant relationship extending from the northeast and north China to the southwest region. The trend coefficients of relative meteorological electricity consumption range from −2.0%/℃ to −7.5%/℃. (3) Spatial correlation analysis shows that summer meteorological electricity consumption and the trend coefficients of relative meteorological electricity consumption are significantly positively correlated with temperature. For each 1℃ increase in temperature, both meteorological electricity consumption and relative meteorological electricity consumption show a significant increase, while in winter, the correlation is weakly negative. [Conclusion] These results have important reference value for energy demand forecasting, energy supply assurance, addressing climate change, achieving the carbon peaking and carbon neutrality goals.
Muhammad Wasim Tahir, Muhammad Yousaf Arshad, Huma Hussain
et al.
The development of advanced electrode materials and their complex formulations has made it increasingly difficult to obtain accurate thermophysical parameters of the active zone in lithium-ion cells. These parameters, such as thermal conductivity and specific heat capacity, are crucial for optimizing the performance and safety of the battery. Conventional methods for obtaining these measurements often require expensive and sophisticated laboratory equipment, which limits accessibility and ease of use. An innovative hybrid approach is presented for measuring the thermophysical parameters of the active zone in lithium-ion batteries. This method combines experimental measurements with numerical simulations to determine anisotropic thermal conductivity, specific heat capacity, and the density of the electrode stack. A key aspect of this approach is the use of low-viscosity liquid paraffin to simulate the effects of the electrolyte. The through-plane and in-plane thermal conductivities of both wetted and dry specimens are measured, while the specific heat capacity is approximated numerically. This simple, cost-effective technique eliminates the need for specialized and expensive lab equipment. The through-plane thermal conductivity of the wetted specimen was found to be 2 orders of magnitude greater than that of the dry specimen, while the difference between the in-plane thermal conductivities of the wetted and dry specimens was negligible. The errors in the measured values of through-plane and in-plane thermal conductivities were approximately 4% and 2%, respectively, while the numerically approximated specific heat capacity showed an error of around 2.5%. All measured parameters were found to be within reported ranges. A 3D lumped thermal model incorporating the measured thermophysical parameters was simulated using the commercial software ANSYS Fluent to examine the effects of thermal anisotropy. The simulation results were validated against experimental data and were found to be in good agreement.
Energy industries. Energy policy. Fuel trade, Renewable energy sources
Zisis Lampropoulos, Spyridon Spyridopoulos, Traianos Karageorgiou
et al.
The gradual electrification of the road transport sector has raised a lot of concerns about the reliability of battery electric vehicles (BEVs). Many potential customers not only lack awareness about the benefits of electrification, total costs and charging infrastructure, but are especially worried about battery lifetime and vehicle performance, information which manufacturers often struggle to provide accurately. This work proposes a methodology to predict BEV lifetime based on complete vehicle simulation employing a physics-based, electrochemical-thermal-aging battery model. In addition, the model calculates the performance degradation over time in terms of energy consumption, range, battery charging efficiency and vehicle acceleration. Physics-based models are harder to develop and computationally costlier than data-driven models. However, once developed, they can be used in a much broader range of conditions and, more importantly, be applied also when no adequate on-road data are yet available. The proposed methodology is applied in a case study of BEV taxis in the city of Thessaloniki, Greece. In particular, the impact of battery preheating prior to charging is evaluated by simulation, showing that preheating could increase lifetime and mileage of BEV taxis by 14% in South European climates. In another application, it is calculated that mid-shift fast-charging could even double the life of the battery compared to fast-charging only before shift change, leading simultaneously to improved performance when compared within the same operational period. Such results could support battery and vehicle manufacturers as well as fleet managers to guide BEV taxi owners towards optimal charging behavior. The modeling approach presented in this paper can be further extended to other vehicle groups, environmental, driving and charging conditions, making it a powerful tool not only for manufacturers, but also for policymakers and charging infrastructure companies.
Energy industries. Energy policy. Fuel trade, Renewable energy sources
Recent progress in microgrids (MGs) has resulted in increased acceptance and utilization of green energy sources, energy storage technologies, and MGs. This has facilitated a more effective and practical administration of distributed energy resources (DERs). The progress in MGs, along with the implementation of hierarchical supervision and monitoring, has facilitated the transmission of information within contemporary communication systems. The incorporation of cyber physical systems (CPS) within MGs has heightened their susceptibility to cyber-attacks, thereby converting them into cyber–physical systems. Thus, emphasizing the importance of preventing, detecting, and isolating cyber-attacks is essential for the effective management of MG. This study offers an in-depth examination of cyber security within the energy sector, exploring the historical backdrop of cyber-attacks and classifying different forms of MG breaches, encompassing both cyber and physical security strategies. This study explore into the intricate communication networking infrastructure susceptible to attacks, particularly emphasizing data centers, and underscores the critical role of MG management in alleviating cyber risks. The study presents a framework that strategically improves cyber security defenses through a classification of countermeasures. The work offers significant perspectives on present and forthcoming advancements, promoting a forward-thinking strategy for safeguarding essential infrastructure in a world that is becoming more digitized.
In this work, we constrain the phenomenological interacting dark energy (IDE) model using \emph{Fermi} gamma-ray burst (GRB) dataset and the latest baryon acoustic oscillation (BAO) data from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2). Through a joint Bayesian analysis, we perform a cosmological comparative assessment of the $Λ$CDM, $w$CDM, and CPL models with the phenomenological IDE model. For the phenomenological IDE model in a flat universe with \emph{Fermi} samples and DESI DR2, we obtain: $ξ=2.63^{+0.63}_{-0.52}$, $ξ+ 3w_X = -0.98^{+1.90}_{-2.07}$ with the GOLD sample ($1.4\le z \le5.6$) and $ξ=2.83^{+0.63}_{-0.58}$, $ξ+ 3w_X = 0.03^{+1.35}_{-1.33}$ with the FULL sample ($1.4\le z \le8.2$), respectively. Our analysis shows that the $Λ$CDM model without interaction ($ξ=3$, $ξ+ 3w_X = 0$) is consistent with the latest \emph{Fermi} sample and DESI DR2 at $1σ$ confidence level. We find no significant deviations from the standard model using AIC and BIC criterias.
Jakub Vícha, Alena Bakalová, Olena Tkachenko
et al.
We assume an extreme scenario, in which the arriving cosmic rays are composed of only iron nuclei at energies above $10^{19.6}\,\text{eV}\simeq40\,\text{EeV}$, while allowing a freedom in the scale of the depth of shower maximum ($X_{\rm{max}}$) and preserving the elongation rate and fluctuations of $X_{\rm{max}}$ predicted by models of hadronic interactions. We derive the shift of the $X_{\rm{max}}$ scale for QGSJet II-04 and Sibyll 2.3d models using the public data from the Pierre Auger Observatory. We then propose a new mass-composition model for the energy evolution of four primary species at the ultra-high energies by fitting the publicly-available $X_{\rm{max}}$ distributions. We discuss the consequences of this Heavy-metal scenario on the energy spectrum of individual primary species, hadronic interaction studies, and the effect of the Galactic magnetic field on the arrival directions.
Energy-efficient ventilation control plays a vital role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate representation of indoor airflow, their high computational cost limits their use in real-time building control. In this work, we present a neural operator learning framework that combines the physical accuracy of CFD with the computational efficiency of machine learning to enable building ventilation control with the high-fidelity fluid dynamics models. Our method jointly optimizes the airflow supply rates and vent angles to reduce energy use and adhere to air quality constraints. We train an ensemble of neural operator transformer models to learn the mapping from building control actions to airflow fields using high-resolution CFD data. This learned neural operator is then embedded in an optimization-based control framework for building ventilation control. Experimental results show that our approach achieves significant energy savings compared to maximum airflow rate control, rule-based control, as well as data-driven control methods using spatially averaged CO2 prediction and deep learning based reduced order model, while consistently maintaining safe indoor air quality. These results highlight the practicality and scalability of our method in maintaining energy efficiency and indoor air quality in real-world buildings.
Hamed Kargaran, Hassan Alipour, Maryam Amirhoseiny
et al.
Optimization problems can be classified as discrete or continuous, depending on the nature of the decision variables. Using continuous algorithms for problems that are inher-ently discrete can pose challenges in achieving optimal efficiency. This study aims to reduce the number of simulations required to determine the most suitable layer thick-nesses for a solar cell. The focus is on the grey wolf optimization method, a continuous algorithm known for its effectiveness in handling complex problems. The objective function of the algorithm is to maximize the short-circuit current density. The research is conducted in two primary stages: single-layer optimization and multi-layer optimization. In the single-layer optimization phase, the ZnO optical spacer layer and the MoOx layer are optimized individually using the grey wolf method. The results indicate that the grey wolf algorithm requires significantly fewer simulations compared to both the genetic algorithm and the brute-force method, which are discrete optimization strategies. In the multi-layer optimization phase, the simultaneous optimization of two layers using the grey wolf method requires approximately 307.03 ± 169.46 simulations, with 100% accuracy. Although there is a minor difference in outcomes, as evidenced by the highest standard deviation, this continuous optimization method still requires considerably fewer simulations compared to the brute-force method (2511 simulations) and the genetic algorithm (1758.77 ± 39.75 simulations) reported in previous studies.
The generation of plastic waste and waste cooking oil is a serious environmental concern because of worldwide waste disposal issues. At the same time, increasing demand and contemporary geopolitics make fossil fuels a significant worldwide problem. As a result, there has been an increase in demand for alternate fuel for CI engines. To overcome these twin problems can be addressed by converting waste into liquid fuels. This research explores an intriguing area by mixing waste cooking oil biodiesel and waste plastic oil to create a mixture that remarkably seems like the physico-chemical properties of diesel fuel in a society that is looking for sustainable alternatives. So, in this investigation, a ternary fuel blend of Petro-diesel, waste cooking oil biodiesel (WCOB), and waste plastic oil (WPO) was used in the diesel engine. To enhance the properties of fuel, combustion, emission, and performance parameters of diesel engines, a ternary blend of B20P20D60 was employed in the CI engine as an alternative fuel. In the ternary fuel blends, WCOB, WPO, and diesel content were 20%, 20%, and 60%, respectively. The results were compared with conventional diesel fuel, showing that the ternary fuel blend B20P20D60 has an improved brake thermal efficiency of up to 1.71% at 80% loading and reduced emissions (HC, CO, NOx) compared to conventional diesel. Because of this, the ternary blends have significant potential for use in diesel engines.
Energy industries. Energy policy. Fuel trade, Renewable energy sources
Data from multiple experiments suggest that the current interaction models used in Monte Carlo simulations do not correctly reproduce the hadronic interactions in air showers produced by ultra-high-energy cosmic rays (UHECR), in particular - but not limited to - the production of muons during the showers. We have created a large library of UHECR simulations where the interactions at the highest energies are slightly modified in various ways - but always within the constraints of the accelerator data, without any abrupt changes with energy and without assuming any specific mechanism or dramatically new physics at the ultra-high energies. We find that even when very different properties - cross-section, elasticity and multiplicity - of the interactions are modified, the resulting changes in some air-shower observables are still mutually correlated. Thus not all possible combinations of changes of observables are easily reproduced by some combination of the modifications. Most prominently, the recent results of the Pierre Auger Observatory, which call for a change in the prediction of both the muon content at ground and the depth of the maximum of longitudinal development of the showers, are rather difficult to reproduce with such modifications, in particular when taking into account other cosmic-ray data. While some of these results are related to the assumptions we place on the modifications, the overall lessons are general and provide valuable insight into how the UHECR data can be interpreted from the point of view of hadronic physics.
[Introduction] In recent years, China has put into operation a large number of offshore booster stations and accumulated rich experience in the construction and operation of offshore booster stations. Based on these experiences, it is found that the current design of offshore booster stations has certain problems, such as relatively simple analysis of operation mode, general load of air conditioning power supply in important equipment rooms, the "unattended" design concept of offshore booster stations does not conform to reality, and inadequate consideration of environmental protection requirements. The design of offshore booster station still has new optimization space. [Method] The experience feedback of several offshore wind farms in the construction and operation stage in recent years were analyzed and the relevant of standards at home and abroad was studied. [Result] Design optimization suggestions are put forward for the operation mode, HVAC load classification of important equipment rooms, personnel duty form of offshore booster station. [Conclusion] The design optimization suggestions of offshore booster station summarized in this paper can be used as a reference for subsequent design of new offshore booster station.
Philipp Wiesner, Ramin Khalili, Dennis Grinwald
et al.
Federated Learning (FL) is an emerging machine learning technique that enables distributed model training across data silos or edge devices without data sharing. Yet, FL inevitably introduces inefficiencies compared to centralized model training, which will further increase the already high energy usage and associated carbon emissions of machine learning in the future. One idea to reduce FL's carbon footprint is to schedule training jobs based on the availability of renewable excess energy that can occur at certain times and places in the grid. However, in the presence of such volatile and unreliable resources, existing FL schedulers cannot always ensure fast, efficient, and fair training. We propose FedZero, an FL system that operates exclusively on renewable excess energy and spare capacity of compute infrastructure to effectively reduce a training's operational carbon emissions to zero. Using energy and load forecasts, FedZero leverages the spatio-temporal availability of excess resources by selecting clients for fast convergence and fair participation. Our evaluation, based on real solar and load traces, shows that FedZero converges significantly faster than existing approaches under the mentioned constraints while consuming less energy. Furthermore, it is robust to forecasting errors and scalable to tens of thousands of clients.
Chun Shen, Abel Noble, Jean-François Paquet
et al.
Heavy-ion collisions at $\sqrt{s_\mathrm{NN}} \sim 10$ GeV probe the QCD phase diagram at large baryon densities. Because the longitudinal Lorentz contraction is small at these collision energies, understanding the dynamics during the early phase of the collision is essential for the subsequent modeling of the system evolution and for constraining the QGP transport properties at finite baryon densities. Direct photons provide undistorted information on early-stage dynamics. We model relativistic heavy-ion collisions at RHIC Beam Energy Scan energies with a hybrid dynamical approach consisting of a 3D-Glauber initial state followed by viscous hydrodynamics and hadronic transport (MUSIC + UrQMD). The implemented thermal photon emission takes into account the enhancement from finite baryon chemical potentials. We show that direct photon spectra and their anisotropic flow coefficients have a strong sensitivity to the early stage of heavy-ion collisions. Thus, they provide constraints on QGP dynamics complementary to those obtained from hadronic observables.
Ashani Wickramasinghe, Saman Muthukumarana, Dan Loewen
et al.
Abstract An efficient building should be able to control its internal temperature in a manner that considers both the building’s energy efficiency and the comfort level of its occupants. Thermostats help to control the temperature within a building by providing real-time data on the temperature inside that space to determine whether it is within the acceptable range of that building’s control system, and proper thermostat placement helps to better control a building’s temperature. More thermostats can provide better control of a building, as well as a better understanding of the building’s temperature distribution. In order to determine the minimum number of thermostats required to accurately measure and control the internal temperature distribution of a building, it is necessary to find the locations that show similar environmental conditions. In this paper, we analyzed high resolution temperature measurements from a commercial building using wireless sensors to assess the performance and health of the building’s HVAC zoning and controls system. Then we conducted two cluster analyses to evaluate the efficiency of the existing zoning structure and to find the optimal number of clusters. K-means and time series clustering were used to identify the temperature clusters per building floor. Based on statistical assessments, we observed that time series clustering showed better results than k-means clustering.
Delia D'Agostino, Sofia Tsemekidi Tzeiranaki, Paolo Zangheri
et al.
Decarbonising the energy sector is crucial to reach future climate and energy goals. As established by the Energy Performance of Building Directive recast, Nearly Zero Energy Buildings (NZEBs) are the mandatory building target in Europe for all new buildings from 2021 onwards. In the light of the approaching deadline, this paper assesses the development of NZEBs in Europe based on the most recent collected data and information.This paper provides an overview of the implementation of national definitions and energy performance values for new, existing, residential, and non-residential buildings in Member States. It evaluates the differences with the established European benchmark and cost-optimal levels. An overview of the most commonly implemented technologies in NZEBs is given together with costs and the relative projections over next decades. Finally, quantitative data on the NZEBs diffusion in Member States are given as recently assessed. The evolution of the NZEB concept and the future NZEBs role is also forecasted.The results assume a strategic value in the light of future targets for the building sector, showing the progress made by Member States in relation to different NZEBs aspects. They provide a comprehensive analysis of the European NZEBs implementation depicting a positive overall progress improvement for NZEBs definitions, uptake, technology development, and energy performance levels. Next challenges and barriers are outlined and appear mainly related to NZEBs retrofit.
Renewable energy provides twenty percent of electricity generation worldwide. Hydroelectric power is the cheapest way to generate electricity today. It is a renewable source of energy and provides almost one-fifth of electricity in the world. Also, it generates electricity using a renewable natural resource and accounting for six percent of worldwide energy supply or about fifteen percent of the world’s electricity. Hydropower is produced in more than 150 countries. Hydropower plant producers provide energy due to moving or falling water. This paper presents and discusses studies on hydroelectric power plant fields, which have been carried out by different investigators. This work aims to study and provide an overview of hydroelectric power plants such as applications, control, operation, modeling and environmental impacts. Also, the hybrid power and efficiency of the hydroelectric power plants has been investigated. The applications of a flexible AC transmission system (FACTS) controller in the power system with the hydroelectric power plants are presented.
Fabbri Clement, de-Loubens Romain, Skauge Arne
et al.
In the domain of heavy to extra heavy oil production, viscous polymer may be injected after water injection (tertiary mode), or as an alternative (secondary mode) to improve the sweep efficiency and increase oil recovery. To prepare field implementation, nine polymer injection experiments in heavy oil have been performed at core scale, to assess key modelling parameters in both situations. Among this consistent set of experiments, two have been performed on reconstituted cylindrical sandpacks in field-like conditions, and seven on consolidated Bentheimer sandstone in laboratory conditions. All experiments target the same oil viscosity, between 2000 cP and 7000 cP, and the viscosity of Partially Hydrolyzed Polyacrylamide solutions (HPAM 3630) ranges from 60 cP to 80 cP. Water and polymer front propagation are studied using X-ray and tracer measurements. The new experimental results presented here for water flood and polymer flood experiments are compared with experiments described in previous papers. The effects of geometry, viscosity ratio, injection sequence on recoveries, and history match parameters are investigated. Relative permeabilities of the water flood experiment are in line with previous experiments in linear geometry. Initial water floods led to recoveries of 15–30% after one Pore Volume Injected (PVI), a variation influenced by boundary conditions, viscosity, and velocities. The secondary polymer flood in consolidated sandstone confirms less stable displacement than tertiary floods in same conditions. Comparison of secondary and tertiary polymer floods history matching parameters suggests two mechanisms. First, hysteresis effect during oil bank mobilization stabilizes the tertiary polymer front; secondly, the propagation of polymer at higher oil saturation leads to lower adsorption during secondary experiment, generating a lower Residual Resistance Factor (RRF), close to unity. Finally, this paper discusses the use of the relative permeabilities and polymer properties estimated using Darcy equation for field simulation, depending on water distribution at polymer injection start-up.
Chemical technology, Energy industries. Energy policy. Fuel trade