Hasil untuk "Energy industries. Energy policy. Fuel trade"

Sanya Carley, David M. Konisky

Z. Abdin, Ali Zafaranloo, A. Rafiee et al.

Abstract Hydrogen is known as a technically viable and benign energy vector for applications ranging from the small-scale power supply in off-grid modes to large-scale chemical energy exports. However, with hydrogen being naturally unavailable in its pure form, traditionally reliant industries such as oil refining and fertilisers have sourced it through emission-intensive gasification and reforming of fossil fuels. Although the deployment of hydrogen as an alternative energy vector has long been discussed, it has not been realised because of the lack of low-cost hydrogen generation and conversion technologies. The recent tipping point in the cost of some renewable energy technologies such as wind and photovoltaics (PV) has mobilised continuing sustained interest in renewable hydrogen through water splitting. This paper presents a critical review of the current state of the arts of hydrogen supply chain as a forwarding energy vector, comprising its resources, generation and storage technologies, demand market, and economics.

Jinfang Tian, Longguang Yu, Rui Xue et al.

The COVID-19 pandemic has created significant challenges for energy transition. Concerns about the overwhelming emphasis on economic recovery at the cost of energy transition progress have been raised worldwide. More voices are calling for “green” recovery scheme, which recovers the economy while not compromising on the environment. However, limited academic attention has been paid to comprehensively investigating the implications of COVID-19 for global energy transition. This study thus provides a comprehensive analysis of the dynamics between energy transition and COVID-19 around the world and proposes a low-carbon energy transition roadmap in the post-pandemic era. Using energy data from the International Energy Agency (IEA), we first summarized and reviewed the progress of energy transition prior to COVID-19. Building on prior progress, we identified the challenges for energy transition during the pandemic from the perspectives of government support, fossil fuel divestment, renewable energy production capacity, global supply chain, and energy poverty. However, the pandemic also generates opportunities for global energy transition. We hence also identified potential opportunities for energy transition presented by the pandemic from the perspectives of price competitiveness, policy implementation efficiency, and renewable energy strengths. We further provided an in-depth discussion on the impact of current worldwide economic recovery stimulus on energy transition. Based on the identified challenges and opportunities, we proposed the post-pandemic energy transition roadmap in terms of broadening green financing instruments, strengthening international cooperation, and enhancing green recovery plans. Our study sheds light on a global low-carbon energy transition framework and has practical implications for green recovery schemes in post-pandemic times.

Gunnar Luderer, S. Madeddu, Leon Merfort et al.

Yang Luo, Yinghong Wu, Bo Li et al.

The automotive industry consumes a large amount of fossil fuels consequently exacerbating the global environmental and energy crisis and fuel cell electric vehicles (FCEVs) are promising alternatives in the continuous transition to clean energy. This paper summarizes the recent development of fuel cell technologies from the perspectives of the automobile industry and discusses current bottlenecks hindering commercialization of FCEVs. Current status of the fuel cell technology, policies and market prospect of FCEVs, as well as recent progress of FCEVs are reviewed. Polymer electrolyte membrane fuel cells constitute the mainstream and most mature fuel cell technology for automobile applications. Hybridization with an auxiliary battery system will greatly boost the dynamic response of FCEVs. Hydrogen FCEVs have entered the preliminary commercialization stage since 2015 and the market share of FCEVs is expected to grow at a high rate. Challenges encountered by commercialization of FCEVs and future outlook are also discussed. Future efforts are expected to focus on solving problems such as the high cost of fuel cell stack production and maintenance, insufficient hydrogen supply facilities, insufficient reliability, slow cold start, safety concerns, and immature energy management systems of FCEVs. This review serves as a reference and guide for future technological development and commercialization of FCEVs.

Shivi Sharma, Neetha S.S., Pranav Arya et al.

The indicators of electric vehicle performance such as state of charge (SOC), remaining useful life (RUL), and charge demand need to be accurately forecasted to ensure maximum energy control and battery life. The models used are usually not able to capture the spatial and temporal correlation of battery data and be robust to the presence of noisy measurements. In this study, we model a sequential attention-based deep learning structure with convolutional neural networks, gated recurrent units, and an attention mechanism that can ultimately understand the local features, temporal relationships, and dynamic significance of various features in sequential battery data. The hybrid architecture of this model allows it to extract local spatial features, long-term sequential dependencies and dynamically find the importance of the critical time steps. We also develop a hybrid loss that is an accumulation of Huber loss and Mean Squared Error, which is much more resilient to outliers and at the same time has high prediction accuracy. It is experimentally proven that the proposed model has R2 values of 0.9575, 0.9558, and 0.9199 on SOC, RUL, and charge demand, respectively, which are better than the current single-architecture methods.

Mrugank Gandhi, Archana Y. Chaudhari, Rahesha Mulla

Abstract The increasing shift to sustainable transportation has fueled growing interest in electric vehicles, including the key issue of estimating the remaining driving range with high precision. The study develops a data-driven approach to predict the cargo electric vehicle’s remaining driving range that incorporates machine learning based estimation. Real-world operational data: a Musoshi Pop-Up Mini electric cargo vehicle was tested under various load and speed characteristics on a 2 km campus route, providing a possibility of high-resolution modeling of energy consumption patterns. After systematic preprocessing with feature engineering and segment-wise aggregation, seven regression algorithms: ElasticNet, Support Vector Regression, Random Forest, LightGBM, XGBoost, CatBoost, and ExtraTrees were optimized with Optuna-based Bayesian hyperparameter tuning and exhaustively compared in terms of RMSE, MAE, and R². Amongst these, the SVR model RMSE equal to 2.37, MAE equal to 1.75, and R² equal to 0.892 demonstrated the best performance and outperformed other ensemble and gradient boosting models. The obtained results prove that data-driven models, can reliably assess energy consumption and range for cargo EVs, which would ensure the safer and more reliable deployment of electric mobility systems.

Sanjeev Kumar, Ankita Gangotra, Michael Barnard

Lang Xu, Yalan Chen

With the continuous expansion of global trade, achieving sustainable maritime transport optimization and operations has become a key strategic direction for transforming maritime transport companies. To summarize the current state of research and identify emerging trends in sustainable maritime transport optimization and operations, this study systematically examines representative studies from the past decade, focusing on three dimensions, technology, management, and policy, using data sourced from the Web of Science (WOS) database. Building on this analysis, potential avenues for future research are suggested. Research indicates that the technological field centers on the integrated application of alternative fuels, improvements in energy efficiency, and low-carbon technologies in the shipping and port sectors. At the management level, green investment decisions, speed optimization, and berth scheduling are emphasized as core strategies for enhancing corporate sustainable performance. From a policy perspective, attention is placed on the synergistic effects between market-based measures (MBMs) and governmental incentive policies. Existing studies primarily rely on multi-objective optimization models to achieve a balance between emission reductions and economic benefits. Technological innovation is considered a key pathway to decarbonization, while support from governments and organizations is recognized as crucial for ensuring sustainable development. Future research trends involve leveraging blockchain, big data, and artificial intelligence to optimize and streamline sustainable maritime transport operations, as well as establishing a collaborative governance framework guided by environmental objectives. This study contributes to refining the existing theoretical framework and offers several promising research directions for both academia and industry practitioners.

Lanxin Li, Xianze Ao, Qiangyan Hao et al.

Accurately estimating atmospheric downward longwave radiation is critical for applications ranging from radiative cooling to building energy efficiency. The main challenge lies in its spectral variability, which depends strongly on sky conditions such as humidity and cloud cover. In this study, we propose a Black–Gray body atmospheric radiation model that divides the infrared spectrum into three regions, treating the atmosphere as a graybody in the 8–13 μm and a blackbody outside this band. The model integrates locally measured radiative power to dynamically capture temporal and spatial variations. Validation experiments were conducted using radiative cooling processes in three Chinese cities (Hefei, Lhasa, and Haikou) under different climates and weather conditions. The BG model consistently predicted radiative cooling power with high accuracy, with mean absolute percentage errors generally below 10 %, outperforming both the effective sky emissivity method and MODTRAN-based predictions. Furthermore, we introduce the concept of band-resolved atmospheric energy databases, analogous to solar radiation databases, and demonstrate it with a full-year case study in Hefei. This work provides a new modeling framework that enhances precision and enables broader applications in energy systems, climate studies, and environmental design.

Tianle He, Peixuan Xue, Zongtao Yu et al.

Fe-based oxygen carriers (OCs) exhibit significant potential for biomass chemical looping gasification (BCLG) to produce hydrogen. However, variations in OC composition and operating conditions strongly affect BCLG performance. In this study, Fe-based OCs were optimized by integrating experimental results with machine learning (ML) techniques, considering both material composition and operational parameters. Experimental evaluation identified Fe8Al2 as the most effective OC, achieving a hydrogen yield of 22.83 mmol/g biomass. These experimental data were combined with literature datasets to train an XGBoost model, yielding a robust predictive performance (R2 > 0.824). Interpretable ML analyses using Shapley Additive Explanations (SHAP) and partial dependence plots (PDP) revealed that the steam-to-biomass ratio and Fe content were the most influential factors for hydrogen production. This integrated approach demonstrates a viable pathway for OC optimization by supplementing limited datasets with targeted experimental data, thereby advancing hydrogen production from BCLG.

Xiaochao ZENG, Qinpeng SHI, Jianfeng HONG et al.

[Objective] With the proposal of the "carbon peak" and "carbon neutrality" goals, the global push for the transformation of the energy structure is accelerating the construction of new power systems dominated by renewable energy. The intermittency and instability of the new energy sources connected to the grid place higher demands on energy storage technologies. Gravity energy storage, as a novel physical energy storage technology, has broad prospects for development. However, its output power lacks stability, and the power curve urgently needs to be optimized. [Method] This paper analyzed the operation process of a shaft-based gravity energy storage system and established physical, efficiency, and power models. Based on these three fundamental models, an overall model for multi-objective optimization was developed with the goals of stabilizing power output and minimizing fluctuation rates. Constraints were set by combining the three models with real-world conditions to determine the optimal parameter configuration for the weight during operation. [Result] Simulation verification of the energy storage system shows that the established overall model effectively optimizes the output power curve at the grid demand power levels of 30 MW, 40 MW, and 50 MW. The optimized fluctuation rates are 3.9%, 4.6% and 8.7%, respectively. [Conclusion] Based on the proposed optimization model, under the condition of constant medium mass of the weight, the output power fluctuation increases as the grid demand power level rises. When the power level increases by 20 MW, the power fluctuation rate increases by 4.8%. Under the condition of constant grid demand power level, the output power fluctuation rate decreases as the medium mass of the weight increases. When the mass of the weight increases from 80 t to 150 t, the power fluctuation rate at 40 MW decreases by 4.2%. The model demonstrates good feasibility and provides valuable guidance for future vertical gravity energy storage projects.

V. Braguta, M. Chernodub, E. Eremeev et al.

We study the free energy and the angular momentum of rotating hot gluon matter using first-principle numerical simulations of the $\textrm{SU}(3)$ lattice Yang-Mills theory. We calculate the specific moment of inertia and the specific deformation of the gluon matter as, respectively, the leading and next-to-leading terms in a series in angular velocity over a broad range of temperatures and various spatial boundary conditions. We show that the specific deformation, similarly to the moment of inertia, takes negative values in a phenomenologically interesting region of temperatures above the phase transition and turns positive at higher temperatures.

O. Deligny

Various phenomena of physics beyond that of the Standard Model could occur at high scale. Ultra-high energy cosmic rays are the only particles available to explore scales above a few dozens of TeV. Although these explorations are much more limited than those carried out with colliders, they provide a series of constraints in several topics such as tests of Lorentz invariance, dark matter, phase transitions in the early universe or sterile neutrinos. Several of these constraints are reviewed in these proceedings of UHECR2024 based on searches for anomalous characteristics in extensive air showers or searches for ultra-high energy gamma rays and neutrinos.

Parth Bambhaniya, Elisabete M. de Gouveia Dal Pino

High-energy astrophysical sources such as active galactic nuclei, quasars, X-ray binaries, and gamma-ray bursts are powered by mechanisms that convert gravitational or rotational energy into radiation, jets, and relativistic outflows. Understanding the physics of these processes remains a major challenge. Black holes have traditionally served as the central engines behind such phenomena, with well established energy extraction mechanisms including the Penrose process, the Blandford-Znajek process, and the Banados-Silk-West mechanism. However, studies in general relativity indicate that, under certain conditions, gravitational collapse may lead to the formation of naked singularities or other horizonless compact objects, which could in principle allow more efficient energy extraction than classical black holes. This brief review summarizes recent progress on energy extraction mechanisms in naked singularity spacetimes. We examine the roles of rotation, electromagnetic fields, and particle interactions in shaping extraction efficiency and dynamics. Particular attention is given to negative energy orbits and ergoregion physics, which enable Penrose type and magnetic Penrose mechanisms without an event horizon. We also discuss collisional Penrose processes and particle acceleration near the singularity, emphasizing their potential astrophysical implications. By comparing extraction efficiencies and physical conditions in black holes and naked singularities, we highlight how the absence of a horizon fundamentally alters the dynamics of energy release. These results suggest that naked singularities may serve as natural laboratories for strong field gravity and as alternative engines for high-energy astrophysical phenomena in the era of multi-messenger observations.

Abdullah Emre Caglar, Muhammet Daştan, Emre Bulut et al.

With the efforts of the United Nations, environmental sustainability is becoming the subject of countries. Policymakers and researchers closely follow the environmental dimensions of Sustainable Development Goals. This study offers a new perspective for the European Union economies by directly targeting SDG 9 and considers environmental sustainability policies in selecting variables. To be more precise, this study probes the effects of economic growth, trade openness, renewable energy, human capital, and competitive industrial performance on the load capacity factor for EU countries over the period of 1995–2018. This study uses the CUP‐FM and CUP‐BC approaches due to cross‐sectional dependence and heterogeneity. In addition, the study does not ignore possible structural breaks. As a result of the empirical analysis, while economic growth, trade openness, and competitiveness worsen environmental quality, renewable energy and human capital contribute to environmental sustainability. Based on the panel data results, EU economies still rely on fossil fuels to maintain competitiveness in the industry. The EU, which has 2030 and 2050 targets, can eliminate the disadvantages of competitiveness by expanding the environmental quality‐enhancing feature of renewable energy and human capital. Moreover, this study provides SDG‐oriented policy recommendations for EU countries.

S. Yin, Zheng Zhao

In order to promote the construction of a clean, low-carbon, and diversified modern rural new energy system, this study examines the development, utilization, connection, and system construction of rural new energy in China. This is done through the classification, integration, and systematic analysis of official statistical data and materials from recent years. Utilizing descriptive statistical analysis, the study holds great theoretical and practical significance. The findings indicate the following: 1) overall, the development of new energy in China’s rural areas is progressing well. However, there is an increasing contradiction between supply and consumption. 2) The new energy industry is experiencing overall growth, accompanied by increasing policy support. Despite this, the industry’s driving effect is not substantial. 3) The development of new energy production equipment in rural areas is lagging, resulting in insufficient cleanliness of energy consumption. There is still a significant gap compared to the goal requirements of agricultural and rural modernization. 4) During the process of rural new energy connection and development, there exists a lack of strong connections between the various subjects of interest. The interest relationship is consequently unstable, necessitating the improvement of a closely-knit interest community. Taking the issue of rural new energy development as its starting point, this paper thoroughly explores the mechanisms driving rural new energy connection. It delves into the interest relationship between the different stakeholders and provides guidelines for optimizing rural new energy system construction. Ultimately, this research aims to contribute to rural revitalization, facilitate the realization of the “double carbon” goal, and establish a modern rural new energy system.

Dunja Grujić, Dušan Vućić, Miloš Kuzman

Usled potrebe za smanjenjem zagađenja životne sredine, usporavanja globalnog zagrevanja i sve manje količine raspoloživih fosilnih goriva, poslednjih godina svedočimo intenzivnom razvoju proizvodnje električne energije iz obnovljivih izvora, kao i razvoju tržišta električne energije. U okviru ovog rada biće izvršena uporedna analiza učesnika na tržištu električne energije u Crnoj Gori i Republici Srbiji, kao i njihovog uticaja na distributivni elektroenergetski sistem. Posebna pažnja biće posvećena kupcima-proizvođačima. Biće prikazani modeli obračuna električne energije kupaca-proizvođača i mogućnosti za njihove dodatne uštede kako energetske, tako i finansijske. Na kraju rada biće date preporuke za buduću lakšu integraciju kupaca-proizvođača i proizvođača električne energije iz obnovljivih izvora energije u distributivni elektroenergetski sistem kroz modele agregiranja, skladištenja i upravljanja proizvodnjom i potrošnjom

Hongtian Song, Yong Xiao, Shanshan Hu et al.

Abstract Super low frequency electric field measurements are crucial in analysing electromagnetic compatibility, assessing equipment status, and other related fields. Rydberg atom‐based super low frequency electric field measurements are performed by observing the Stark shift in the spectrum of the Rydberg state. In a specific range of field strength (E < Eavoid, where Eavoid is the threshold to avoid crossing electric fields), the Rydberg atomic spectrum experiences a quadratic frequency shift in relation to the field strength, with the coefficient being determined by the atomic polarisability α. The authors establish a dynamic equation for the interaction between the external electric field and the atomic system, and present the Stark structure diagram of the Caesium Rydberg atom. The mathematical formulae for α and Eavoid in different Rydberg states are also obtained: α = A × (n*)6 + B × (n*)7 and Eavoid = C/(n*)5 + D/(n*)7, where A(B) = 2.2503 × 10−9(7.49,948 × 10−11) and C(D) = 1.68,868 × 108(2.45,991 × 109). The error of α and Eavoid compared with the experimental values does not exceed 8% and is even lower in the low Rydberg states. Accurately calculating the values of α and Eavoid is crucial in incorporating the Rydberg atom quantum coherence effect into super low frequency electric field measurements in new power systems.

Yicang Guo, Yan Ding, Jinlong Li et al.

The energy efficiency of the single-effect absorption refrigeration systems (ARS) using ionic liquid (IL) [Emim]Br as an absorbent and water as a refrigerant is evaluated in this study. The thermodynamic properties of the mixture, such as vapor pressures and excess enthalpies, are calculated using the non-random two-liquid (NRTL) activity coefficient model. The coefficient of performance (COP) is estimated with fixed temperatures for the evaporator, absorber, condenser, and generator, set at 10, 30, 40, and 100 °C, respectively. It is found that the COP of the single-effect ARS using [Emim]Br-H2O as the working pair is about 0.8, which is slightly lower than that obtained with LiBr-H2O (0.83), but much higher than that of H2O-NH3 (0.65) systems. The effect of generator temperature on COP has the same trend as that of other IL working pairs. The influence of each component temperature on the system’s performance is investigated, and it is found that the single-effect ARS performs very well under different conditions with [Emim]Br - H2O as the working pair.