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

Xiaozhen Chen, Kai Shi, Chaoqiang Jiang et al.

Data-driven approaches have emerged as a transformative force in accelerating the discovery and optimization of inorganic materials for all-solid-state batteries (ASSBs), leading to substantial progress in recent years. Earlier reviews often focus on isolated methodologies or specific material classes. Here, this study systematically highlights the pivotal role of machine learning in advancing solid electrolytes and cathode materials in ASSBs, targeting critical properties including high ionic conductivity, wide electrochemical stability windows, and interfacial compatibility. We chart the methodological evolution from conventional descriptor-based predictive models to advanced deep learning architectures that autonomously extract features from composition and crystal structure, and further to integrated active-learning platforms that close the loop between prediction and experimental validation. Beyond summarizing these technological strides, we critically assess current limitations, particularly the gap between idealized models and the complexity of real devices. Finally, a forward-looking research agenda is outlined, advancing physics-guided and multi-fidelity learning frameworks, developing generative models for inverse design under realistic constraints, extending modeling to interface and cell-level complexity, and establishing reliable closed-loop discovery systems. This work will consolidate current knowledge and chart a path toward more predictive, actionable, and integrative artificial intelligence tools that can accelerate the realization of high-performance, commercially viable solid-state batteries.

A. R. Byasharova, A. E. Zotov

The modern processes of globalization of the world economy are associated with the decarbonization of the energy market. This fact indicates that in the future, the economies of energy exporting countries will increasingly depend on this trend. This article discusses the general issues of the influence of energy exporting countries on the global economy. The process of divergence of the global economy, as well as the impact of sanctions on economic processes, is being investigated. Various scenarios for the development of the above-mentioned processes are analyzed, taking into account the direction of the transition of the world powers to a low-carbon economy. Such a transition is associated with various risks, especially relevant for developing countries. The hypothesis of the study is that in the context of decarbonization and energy transition, energy exporting countries will face technological and market challenges that can significantly affect economic growth and their development prospects. The economic, technological, and social blocks of economic activity of the countries that are the world's main energy suppliers are studied. The conclusions concerning the problems associated with risks for energy exporting countries during the transition of the world's economies to a low–carbon economy and their abandonment of fossil fuels are substantiated. The mechanisms of adaptation of the world market to the changing conditions of functioning of the global economic space are determined. Methods of theoretical modeling, comparative and system analysis were used as a universal means of scientific knowledge. The problems are systematized, the solution of which eliminates the main risks for the countries of the energy exporting group during the transition from fossil fuels to a low-carbon economy with further global decarbonization. As recommendations, the authors propose various scenarios that take into account the prospects for the development of the economies of the main energy exporting countries in the context of decarbonization of energy resources.

K Deenadayalan, B Rahul

This paper presents a comparative study on the residual stress formation in a Nickel-based matrix by the reinforcement of two types of WC particles having two different shape factors (angular and spherical) and density. Three types of coatings were prepared: pure Nickel-based super alloy (Spherical), Nickel-based super alloy with 30 % spherical WC particles, and Nickel-based super alloy with Angular WC particles. The prepared coatings (Ni, Ni-WCS & Ni-WCA) are characterised using the X-Ray Diffraction technique for the subsequent evaluation of residual stress. Namely three techniques Sin2ψ method, William Hall method and the Direct instrumentation method based on XRD were incorporated to determine and compare the residual stresses formed in the coatings. The results exhibited that the Ni and WC shape and form factor had a significant influence on the coating residual stress.

Francisco José Grandinetti, Marcelo Sampaio Martins, Wendell de Queiróz Lamas et al.

This research investigates the potential impact of adopting electric vehicles (EVs) on greenhouse gas (GHG) emissions within the Brazilian state of São Paulo. The aim is to evaluate the extent to which varying EV adoption rates can contribute to emissions reductions. A systematic literature review, conducted in accordance with the PRISMA framework, synthesised recent studies concerning the impacts of EVs. This qualitative analysis was complemented by quantitative modelling employing historical data pertaining to São Paulo’s vehicle fleet, fuel consumption, and emissions factors. Ridge regression models and optimisation algorithms, implemented in MATLAB® R2024b, were utilised to estimate emissions reductions across three distinct EV adoption scenarios: 25 %, 50 %, and 75 %. The analysis considered both the direct emissions from vehicle operation and the indirect emissions associated with electricity generation. Key findings highlight a significant potential for GHG emission reductions with increasing EV adoption rates. The novelty of this work lies in its specific focus on the context of São Paulo, Brazil, integrating a systematic review with robust statistical modelling to provide regionally relevant insights into the environmental implications of transport electrification.

Tao ZHOU, Haolei ZHANG, Yao YAO et al.

[Objective] The development of information technology leads the development trend of the new era. Information technology promotes the progress of nuclear power generation technology to intelligentization and even smartization, while also ensuring the safe development of nuclear power generation. [Method] The positioning association of information, nuclear power generation, and the intelligentization of nuclear power generation was provided. The application of information technology in future nuclear power generation was studied. The development trend of advanced nuclear power generation was analyzed. [Result] The future nuclear power generation should first be information-based nuclear power generation, followed by intelligent nuclear power generation, and then possibly smart nuclear power generation. The characteristics of 5G low delay can make the nuclear power generation system more accurate, and the nuclear system can be accurately adjusted to operate faster and respond in time. Cloud computing can also find problems in nuclear power generation's complex mass of data. Big data can analyze the root causes of problems in a timely manner. Quantum technology can enhance the core fuel function. Artificial intelligence machine data capture and neural networks learn to process and apply information more precisely. [Conclusion] Informationization is also a new quality productivity revolution, and information technology promotes the progress of nuclear power generation technology to intelligent development. The intelligence of nuclear power generation is the future trend of advanced nuclear power generation development. The upgrading of information technology is the leading driver of nuclear power generation. Ensuring nuclear power generation safety requires the assistance of information. Network information technology is the central link to build a comprehensive nuclear and solar energy system.

Junhong Liu, Qinfei Long, Rong-Peng Liu et al.

Distributed peer-to-peer (P2P) energy trading mandates an escalating coupling between the physical power network and communication network, necessitating high-frequency sharing of real-time data among prosumers. However, this data-sharing scheme renders the system vulnerable to various malicious behaviors, as Byzantine agents can initiate cyberattacks by injecting sophisticated false data. To better investigate the impacts of malicious Byzantine faults, this paper develops a fully distributed P2P energy trading model by accounting for the high-fidelity physical network constraints. To further detect Byzantine faults and mitigate their impacts on distributed P2P energy trading problem, we propose an online spatial-temporal anomaly detection approach by leveraging the tensor learning method, which is informed by the domain knowledge to enable awesome detection performance. Moreover, to enhance its computational efficiency, we further develop closed-form solutions for the proposed detection approach. Subsequently, we derive theoretical conditions for guaranteeing optimality and convergence of the distributed P2P energy trading problem with anomaly detection mechanisms. Results from numerical simulations validate the effectiveness, optimality, and scalability of the proposed approach.

Marcel van der Westhuizen, Amare Abebe, Eleonora Di Valentino

Interacting dark energy (IDE) models, in which dark matter (DM) and dark energy (DE) exchange energy through a non-gravitational interaction, have long been proposed as candidates to address key challenges in modern cosmology. These include the coincidence problem, the $H_0$ and $S_8$ tensions, and, more recently, the hints of dynamical dark energy reported by the DESI collaboration. Given the renewed interest in IDE models, it is crucial to fully understand their parameter space when constraining them observationally, especially with regard to the often-neglected issues of negative energy densities and future big rip singularities. In this work, we present a comparative study of the general linear interaction $Q=3H(δ_{\rm dm}ρ_{\rm dm} + δ_{\rm de}ρ_{\rm de})$ and four special cases: $Q=3Hδ(ρ_{\rm dm}+ρ_{\rm de})$, $Q=3Hδ(ρ_{\rm dm}-ρ_{\rm de})$, $Q=3Hδρ_{\rm dm}$, and $Q=3Hδρ_{\rm de}$. For these five models, we perform a dynamical system analysis and derive new conditions that ensure positive, real, and well-defined energy densities throughout cosmic evolution, as well as criteria to avoid future big rip singularities. We obtain exact analytical solutions for $ρ_{\rm{dm}}$, $ρ_{\rm{de}}$, the effective equations of state ($w_{\mathrm{eff}}^{\rm{dm}}$, $w_{\mathrm{eff}}^{\rm{de}}$, $w_{\mathrm{eff}}^{\rm{tot}}$), and a reconstructed dynamical DE equation of state $\tilde{w}$. Using these results, we examine phantom crossings, address the coincidence problem, and apply the statefinder diagnostic to distinguish between models. We show that energy transfer from DM to DE inevitably produces negative energy densities and make future singularities more likely, while transfer from DE to DM avoids these pathologies and is thus theoretically favored.

Jun-Shuo Zhang, Tian-Cong Wang, Pei Wang et al.

Fast radio bursts (FRBs) are widely considered to originate from magnetars that power the explosion through releasing magnetic energy. Active repeating FRBs have been seen to produce hundreds of bursts per hour and can stay active for months, thus may provide stringent constraints on the energy budget of FRBs' central engine. Within a time span of 214 days, we detected 11,553 bursts from the hyper-active FRB 20240114A that reached a peak burst rate of 729 hr$^{-1}$. This is the largest burst sample from any single FRB source, exceeding the cumulative total of all published bursts from all known FRBs to date. Assuming typical values of radio efficiency and beaming factor, the estimated total isotropic burst energy of this source exceeds 86% of the dipolar magnetic energy of a typical magnetar. The total released energy from this source exceeds that of other known repeaters by about one and a half orders of magnitude, yielding the most stringent lower limit of $4.7\times10^{32}$ G cm$^3$ for the magnetar's magnetic moment. The source remained active at the end of this observation campaign. Our findings thus require either the FRB's central magnetar engine's possessing exceptionally high emission efficiency or a more powerful compact object than a typical magnetar.

Prashant Giri, Tarun Sharma

Xiaoquan Lu, Kaijie Fang, Yuqi Zhou et al.

Abstract Based on the building thermodynamics model and the physical heat/cold conversion model of an air-conditioning system, this paper proposes a double-layer energy optimization model for a cement factory’s office building air-conditioning systems considering dynamic ambient temperature and the entire unit equipment. First, taking the envelope structure, outdoor air, and internal heat sources as the main subjects and considering the heat exchange between human skin and the envelope structure, a building thermal balance model and a refined calculation model of comfort were established. Secondly, the ground source heat pump is considered. A physical model of the operation of the air-conditioning system is set for the equipment, such as heat pumps, circulating water pumps, and variable frequency fans. Then, a two-layer comprehensive optimization model of the cement factory office building air-conditioning system was given based on system power consumption and comfort. The upper model dynamically adjusts the indoor set temperature to obtain the cooling load of the air-conditioning system; the lower model allocates the load rate based on the heat pump unit's performance to optimize the system's overall energy consumption. Finally, a typical case of a double-story model of a cement factory office building using the GA algorithm was compared and verified, showing the effectiveness of the proposed model.

Jian Ye, Qiang Dong, Gelin Yang et al.

Abstract In order to cope with the increasing energy demand and achieve the “double carbon “goal of China’s 14th Five-Year Plan,” combined with hydrogen energy storage technology, it has the characteristics of zero pollution, high efficiency and rich source. In the context of reducing energy consumption and the vigorous development of hydrogen energy storage technology, a multi-objective optimization configuration model with economy, energy consumption index and carbon emission index is proposed, which takes into account the working characteristics of the hydrogen energy storage system, and the exothermic heat release from the electrolysis tanks and fuel cells when they are working to provide the loads with an additional heat source of the Combined Cooling, Heating and Power (CCHP) system, to reduce energy consumption and carbon emission. Finally, taking a region as an example, a multi-objective optimization algorithm based on decomposition is used to solve the model, so as to obtain a series of alternatives with better optimization effect. At the same time, the two-way projection method based on interval intuitionistic fuzzy information is used to make decisions, and the scheme that optimizes the economy, energy consumption index and carbon emission index is obtained, which verifies the feasibility of the system proposed in this paper.

Zhang Dong, Zou Qing, Zheng Yu et al.

Abstract The focus of this study is to optimize the exploration of biomass-driven multi-energy systems, which include combined heat, power, and gas generation. The objective is to enhance the thermal, environmental, and economic performance indicators of the system. The optimization objectives encompass the quantities of internal combustion engines and air source heat pumps, as well as the dimensions of tanks utilized for anaerobic fermentation. A mathematical model was developed to optimize multiple objectives for combined heat, power, and gas generation systems by employing multi-objective intelligent optimization algorithms. The validation and analysis were conducted using rural residences in Lanzhou, Gansu Province, China, as a case study. The sensitivity analysis of biomass gasification combined heat and power systems was conducted from both technical and cost perspectives, examining the dynamic impact characteristics on the outcomes of multi-objective optimization. The findings indicate that the annual energy-saving rate of the optimized combined generation system decreased from 3.62% to -6.78%, while the growth in carbon emissions reduction rate increased from 76.05 to 81.38%, and the annual cost-saving rate grew from 0.97 to 14.96%. The power generation efficiency of the cogeneration station and hydraulic retention time were found to have a significant impact on the multi-objective optimization results of the combined generation system among the technical parameters. The unit cost of anaerobic fermentation tanks had a more significant impact on the multi-objective optimization results in terms of cost parameters, compared to the price of biogas residue.

Hans Christiansen, Bence Takács, Steen H. Hansen

The accelerated expansion of the Universe is impressively well described by a cosmological constant. However, the observed value of the cosmological constant is much smaller than expected based on quantum field theories. Recent efforts to achieve consistency in these theories have proposed a relationship between Dark Energy and the most compact objects, such as black holes (BH). However, experimental tests are very challenging to devise and perform. In this article, we present a testable model with no cosmological constant, in which the accelerated expansion can be driven by black holes. The model couples the expansion of the Universe (the Friedmann equation) with the mass-function of cosmological haloes (using the Press-Schechter formalism). Through the observed link between halo-masses and BH-masses one thus gets a coupling between the expansion rate of the Universe and the BHs. We compare the predictions of this simple BH model with SN1a data and find a poor agreement with observations. Our method is sufficiently general that it allows us to also test a fundamentally different model, also without a cosmological constant, where the accelerated expansion is driven by a new force proportional to the internal velocity dispersion of galaxies. Surprisingly enough this model cannot be excluded using the SN1a data.

Irene Monasterolo, Marco Raberto

Nguyen Huu Duc

The study of the current state of the renewable energy sources (RES) sector as an important area for reducing harmful emissions into the atmosphere makes it possible to identify a circle of subjects – participants in the RES electricity market. The financial risks they take largely determine the present and future of this innovative market in terms of investment, financing, lending, insurance, regulation, and incentives. The renewable energy market is of particular interest to investors, financial institutions, the state setting the rules of the game and stimulating its development. The financial risks of market participants as the probability of monetary losses and losses are manifested at all stages of the development and implementation of renewable energy projects, from the development of technologies to public procurement of generated electricity. The analysis made it possible to identify the features of financing renewable energy projects, in particular, high initial financial costs, long payback periods for projects requiring long-term lending, sensitivity to regulatory and legal changes on the part of the state in terms of purchase prices for electricity, subsidies and incentive benefits for its producers and financial institutions – participants. Based on specific examples of renewable energy projects, the risks of banks, insurers in Vietnam and a number of developing countries in South Asia that provide green loans and green insurance products to companies implementing renewable energy projects, as well as households producing electricity from solar systems, are considered. Recommendations were formulated for national financial regulators, banking institutions, insurance companies to ensure acceptable financial conditions for renewable energy projects and adequately assess their own financial risks.

Hemlal Bhattarai

René Kuchenbuch, Johann Schütz, Jürgen Sauer

Abstract The Smart Grid Architecture Model (SGAM) and the IEC 62559-2 Use Case Template are essential representatives of the Requirements Engineering of energy systems to promote interoperability. In particular, the quality of the use case descriptions and SGAM models is crucial for the system understanding. In order to measure and assess the quality of given use cases of the SGAM models, the aim of this research is to determine those requirements and quality characteristics. Based on a literature review, general best practices for deriving use cases and SGAM models are obtained. The results can be used to concept far-reaching supportive systems or to evaluate IEC 62559 use case descriptions and SGAM models.

Xiaolei Wang, Shuang Liang, Hui Wang et al.

Energy intensive industries (EIIs) in China are predominantly reliant on fossil fuels. Consequently, such high fossil fuel dependency has amplified carbon emission levels and blocked the low-carbon transition. It is inappropriate to discuss the solution of the dependency before investigating fossil-fuel price distortion and its impact on the industrial energy consumption. Therefore, this paper built a dynamic trans-log cost function model based on provincial panel data of China’s Ells between 2004 and 2016, to investigate inter-fuel substitution effects caused by own price elasticities and cross price elasticities, and analyzed the impact of fossil-fuel price distortions on low-carbon transition. The level of price distortions in coal, gasoline and diesel was evaluated, based on which the CO2 mitigation potentials in China’s EIIs were estimated. Results show that: 1) in each EII sector, the own price elasticities of all fuels were negative while the cross price elasticities among coal, oil and electricity were positive, suggesting substitution effect exists; 2) the average level of price distortions in coal, gasoline and diesel is 7.48, 11.1 and 32.19%, respectively, which means the prices of coal tend to be more market- oriented than the other two fuels; 3) removing coal price distortions can potentially reduce CO2 emissions in China’s EIIs by 905.78 million tons, while the effects of removing oil price distortions were uncertain, unless the substitution of coal for oil was restrained. Therefore, there is still much room for improvement in China’s fossil-fuel market reform. Possible policies are required to improve the production in EIIs and the low-carbon transition by adopting cleaner energy resources to substitute fossil-fuels.

Pascalin Tiam Kapen, Brigitte Astrid Medjo Nouadje, Victorin Chegnimonhan et al.

The electricity deficit in Cameroon is estimated today at 50 GWh. This deficit characterized by frequent and sometimes prolonged load shedding, disrupts economic and social life. To overcome this electricity deficit, Cameroon took the decision to produce 3000 MW of electrical energy from its renewable energies potential. Indeed, the annual solar radiation in Cameroon varies from 4.28 kWh/m2/year to 5.80 kWh/m2/year. It has 25 million hectares of forest covering three-quarters of its territory, amounting to the third-largest biomass potential in sub-Saharan Africa. In addition, there is an intense breeding activity for cattle, goats, sheeps and pigs in the Far North region amounting to several million heads and generating large quantities of dung. This paper therefore investigates for the very first time the techno-economic feasibility by using HOMER Pro of two scenarios of hybrid systems namely, PV/Fuel Cell/Electrolyzer/Biogas (scenario 1), and PV/Battery/Fuel Cell/Electrolyzer/Biogas (scenario 2) for energy and Hydrogen production in the city of Maroua, recognized as being part of the sunniest region (Far North) of Cameroon. The combination of electrolyzer, fuel cell and hydrogen tank was used in the present design to reduce battery storage requirement. Three types of household electricity demands communities (low, medium and high consumers) were considered in this work. The results showed that the optimal system architecture for scenario 1 included 144 kW PV module, 15 kW biogas generator, 11 kW converter, 15 kW electrolyzer, 15 kW fuel cell and 5000 kg Hydrogen tank with a dispatch strategy of cycle charging (CC) for low consumers community. For medium consumers community of scenario 1, 879 kW PV module, 15 kW biogas genetrator, 31.9 kW converter, 24 kW fuel cell, 24 kW electrolyzer and 5000 kg Hydrogen tank with a CC dispatch strategy was the best hybrid system. For high consumers community of scenario 1, 11,925 kW PV module, 15 kW biogas generator, 570 kW converter, 266 kW fuel cell, 266 kW electrolyzer and 25,000 kg Hydrogen tank with a CC dispatch strategy was the best hybrid system. Concerning scenario 2, the following architectures were the best hybrid systems: for low consumers, 138 kW PV modules, 15 kW biogas generator, 27.2 kW converter, 15 kW fuel cell, 15 kW electrolyzer, 5000 kg Hydrogen tank and 480 batteries storage bank with a CC dispatch strategy; for medium consumers, 234 kW PV modules, 15 kW biogas generator, 57.8 kW converter, 24 kW fuel cell, 24 kW electrolyzer, 5000 kg Hydrogen tank and 1023 batteries storage bank with a load following (LF) dispatch strategy; and for high consumers, 820 kW PV modules, 15 kW biogas generator, 405 kW converter, 266 kW fuel cell, 266 kW electrolyzer, 25,000 kg Hydrogen tank and 9519 batteries storage bank with a CC dispatch strategy. The levelized costs of energy (LCOE) for scenario 1 were US$ 0.871/kWh, US$ 0.898/kWh and US$ 1.524/kWh for low, medium and high consumers communities respectively. Concerning scenario 2, the LCOE were US$ 0.139/kWh, US$ 0.091/kWh and US$ 0.071/kWh. In addition, it was found a levelized costs of Hydrogen (LCOH) for scenario 1 of US$ 7.66/kg, US$ 4.95/kg, and US$ 0.45/kg for low, medium and high consumers communities respectively. For scenario 2, the LCOH were US$ 3.06/kg, US$ 1.34/kg and US$ 0.15/kg for low, medium and high consumers communities respectively. It was also concluded from the optimization results that the combination of water electrolyzer, fuel cell and hydrogen tank coupled to biogas generator and PV modules could be used as an alternative solution to make electricity available and accessible to the population of the Far North region of Cameroon.

Huiyan Zhang, Bingbing Luo, Kai Wu et al.

Catalytic fast pyrolysis of lignin is easy to cause agglomeration and coking, resulting in low-yield aromatic hydrocarbons. Catalytic pyrolysis of modified lignin combined with metal-modified HZSM-5 was proposed to enhance the aromatic yield. The experiment results showed that chemical modification with Ca(OH)2 not only inhibited the agglomeration behavior of lignin but also increased the yield of light phenolic compounds. Moreover, Ca2+-loaded lignin combined with metal-modified HZSM-5 was conducive to the formation of aromatics. The total yield of aromatics from the catalytic fast pyrolysis of Ca2+-loaded lignin over Zn/HZSM-5 was improved from 31.1 to 46.1 mg/g. The mechanism insight showed that Ca2+ modification realized the chemical combination between Ca2+ and the functional groups which are responsible for the agglomeration of lignin, and then the introduction of the Zn species suppressed the hydrogen transfer reaction and enhanced the dehydrogenation pathway, resulting in the increase of aromatic yield.