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

A. Demirbaş

Zhien Zhang, S. Pan, Hao Li et al.

Abstract Carbon dioxide (CO2) is the major contributor to greenhouse gas (GHG) emissions and the main driver of climate change. Currently, CO2 utilization is increasingly attracting interest in processes like enhanced oil recovery and coal bed methane and it has the potential to be used in hydraulic fracturing processes, among others. In this review, the latest developments in CO2 capture, utilization, conversion, and sequestration are examined through a multi-scale perspective. The diverse range of CO2 utilization applications, including mineralization, biological utilization, food and beverages, energy storage media, and chemicals, is comprehensively presented. We also discuss the worldwide research and development of CO2 utilization projects. Lastly, we examine the key challenges and issues that must be faced for pilot-scale and industrial applications in the future. This study demonstrates that CO2 utilization can be a driver for the future development of carbon capture and utilization technologies. However, considering the amount of CO2 produced globally, even if it can be reduced in the near-to mid-term future, carbon capture and storage will remain the primary strategy and, so, complementary strategies are desirable. Currently, the main CO2 utilization industry is enhanced oil and gas recovery, but considering the carbon life cycle, these processes still add CO2 to the atmosphere. In order to implement other CO2 utilization technologies at a large scale, in addition to their current technical feasibility, their economic and societal viability is critical. Therefore, future efforts should be directed toward reduction of energy penalties and costs, and the introduction of policies and regulation encouraging carbon capture, utilization and storage, and increasing the public acceptance of the strategies in a complementary manner.

Hanna Brauers, P. oei

Abstract Poland is the largest hard coal and second largest lignite producer in the EU, generating around 80 percent of its electricity from coal. Resistance to a reduction in coal production and consumption comes from various actors, namely, coal corporations, unions, parts of civil society and the government – as well as their coalitions. Their opposition centres around the prospect of losing their business, past negative experiences with structural change, fears of rising energy prices and energy security concerns, as well as potential unemployment in regions almost entirely dependent on coal. This paper identifies key political and economic drivers and barriers of a reduction in coal production and consumption in Poland using the Triple Embeddedness Framework. Uneconomic coal mining, unavoidable energy infrastructure investments, rising air pollution levels and pressure from the European Union might provide new political momentum for a shift away from coal in line with international climate targets. However, results show that to achieve political feasibility, policies targeting a reduction in coal production and use need to be implemented jointly with social and structural policy measures, addressing a just transition for the affected regions in line with the vision of a ‘European Green Deal’.

Edinson Benavides, Germán Obando, Andrés Pantoja

Abstract Peer-to-peer (P2P) energy trading represents a viable solution for the transition toward carbon-free energy systems, as they enable prosumers to exchange electricity at lower costs without the need for intermediaries. However, P2P networks require an infrastructure that supports the secure exchange and storage of information. In addition, a key challenge in P2P markets is ensuring economic balance among all network participants. This paper develops an integrated methodology for P2P energy trading by combining distributed optimization with Blockchain technology. To mitigate the challenges of economic balancing and data privacy, we implement an asynchronous distributed algorithm based on Replicator Dynamics within the Ethereum ecosystem. The proposed two-layer architecture utilizes smart contracts to facilitate optimal dispatch among prosumers while maintaining information immutability and security. Experimental implementation shows that the system achieves fast convergence in the optimization process without compromising agent privacy. The study concludes with an automated P2P market framework, demonstrating the potential of Blockchain as a robust infrastructure for decentralized energy management and distributed optimization.

J. Larsson, Anna Elofsson, T. Sterner et al.

ABSTRACT Aviation constitutes about 2.5% of all energy-related CO2 emissions and in addition there are non-CO2 effects. In 2016, the ICAO decided to implement a Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) and in 2017 the EU decided on faster emission reductions in its Emissions Trading System (EU ETS), which since 2012 includes the aviation sector. The effects of these policies on the expected development of air travel emissions from 2017 to 2030 have been analyzed. For the sample country Sweden, the analysis shows that when emissions reductions in other sectors are attributed to the aviation sector as a result of the EU ETS and CORSIA, carbon emissions are expected to reduce by −0.8% per year (however if non-CO2 emissions are included in the analysis, then emissions will increase). This is much less than what is needed to achieve the 2°C target. Our analysis of potential national aviation policy instruments shows that there are legally feasible options that could mitigate emissions in addition to the EU ETS and CORSIA. Distance-based air passenger taxes are common among EU Member States and through increased ticket prices these taxes can reduce demand for air travel and thus reduce emissions. Tax on jet fuel is an option for domestic aviation and for international aviation if bilateral agreements are concluded. A quota obligation for biofuels is a third option. Key policy insights Existing international climate policies for aviation will not deliver any major emission reductions. Policymakers who want to significantly push the aviation sector to contribute to meeting the 2°C target need to work towards putting in place tougher international policy instruments in the long term, and simultaneously implement temporary national policy instruments in the near-term. Distance-based air passenger taxes, carbon taxes on jet fuel and quota obligations for biofuels are available national policy options; if they are gradually increased, and harmonized with other countries, they can help to significantly reduce emissions.

Cecil Felix, Iosif Vazirgiantzikis, Mphoma Matseke et al.

Slot-die coating is a promising method for mass-producing membrane electrode assemblies for polymer electrolyte membrane fuel cells. Precise control of slot-die coating parameters and catalyst ink variables is essential for achieving defect-free catalyst layers. This study investigated catalyst ink rheology and coating windows of typical ink formulations and extremes. The influence of the dispersing solvent ratio, ionomer-to-carbon ratio, and Pt weight percentage on catalyst ink rheology and coating behaviour was examined. Inks with a 75%-water/25%-n-propanol dispersing solvent ratio exhibited shear-thinning and good coatability, while those with high water content (90%-water/10%-n-propanol) displayed Newtonian flow, leading to poor substrate wetting and coating. Increasing the ionomer-to-carbon ratio reduced the ink's viscosity, while increasing the Pt weight percentage increased the ink’s viscosity. While appearing defect-free, x-ray fluorescence and optical microscopy analyses revealed that the coated catalyst layers often displayed nonuniform Pt loadings and cracks, especially with increasing catalyst layer thickness. The nonuniform Pt loadings were attributed to variations in gas diffusion layer roughness, catalyst layer cracks, and limitations of the slot-die coater. Initial membrane electrode assembly performance tests underscored the importance of material selection, the ionomer overlayer, and hot-pressing to enhance performance.

Maxim Idriss Meli Tametang, Pavell Leandry Lekeufack Tameze, Guy Bertrand Tchaya et al.

This study investigates a novel hybrid electric vehicle architecture integrating a wind energy conversion system to transform part of kinetic energy of the vehicle into electrical energy to ensure real-time recharging of battery. Application of Pontryagin’s Minimum Principle yields the optimal control law, revealing that this supplementary energy source extends engine operation in pure electric driving mode, thereby reducing fuel consumption. Furthermore, this new architecture enables a substantial reduction in pollutant emissions, particularly CO2, nitrogen oxides (NOx), carbon monoxide (CO), and hydrocarbons (HC), thereby enhancing its environmental benefits. More interestingly, a threshold turbine blade radius is derived above which the vehicle can operate in pure electric mode throughout the trip. Numerical simulations and experimental validation, using a small wind turbine mounted behind a Pick-up truck, confirm the analytical findings, demonstrating the potential for wind energy harvesting to generate approximately 1000W of power at speeds of up to 95km∕h, thus paving the way for a more sustainable transportation future.

Shu-Xu Yi, Chen-Wei Wang, Shao-Lin Xiong et al.

To understand the physical mechanisms underlying the prompt emission of gamma-ray bursts (GRB), single FRED (Fast-Rise-Exponential-Decay) profile GRBs serve as an ideal sample, as they origin from single epoch central engine activity. These GRBs have been found to exhibit a peculiar morphology-including the elegant cross-energy-similarity across energy bands and the recently discovered composite nature-challenging nearly all existing radiation mechanisms, sparking widespread curiosity about their origins. Here we propose a physical model which includes radiation locations sequentially triggered by propagating magnetic perturbations. It naturally explains all observed properties of these GRBs, including the self-similar FRED profile, multi-band aligned subpulses, hard-to-soft spectral evolution, local intensity tracking, and increasing subpulse durations. Furthermore, our results demonstrate that the duration of these GRBs is not reflecting the activity timescale of the central engine, reconciling recent challenges to the traditional merger-short/collapsar-long dichotomy of GRBs.

Jun Wen Law, Bryan K. Mignone, Dharik S. Mallapragada

Low-carbon liquid fuels play a key role in energy system decarbonization scenarios. This study uses a multi-sector capacity expansion model of the contiguous United States to examine fuels production in deeply decarbonized energy systems. Our analysis evaluates how the shares of biofuels, synthetic fuels, and fossil liquid fuels change under varying assumptions about resource constraints (biomass and CO2 sequestration availability), fuel demand distributions, and supply flexibility to produce different fuel products. Across all scenarios examined, biofuels provide a substantial share of liquid fuel supply, while synthetic fuels deploy only when biomass or CO2 sequestration is assumed to be more limited. Fossil liquid fuels remain in all scenarios examined, primarily driven by the extent to which their emissions can be offset with removals. Limiting biomass increases biogenic CO2 capture within biofuel pathways, while limiting sequestration availability increases the share of captured atmospheric (including biogenic) carbon directed toward utilization for synthetic fuel production. While varying assumptions about liquid fuel demand distributions and fuel product supply flexibility alter competition among individual fuel production technologies, broader energy system outcomes are robust to these assumptions. Biomass and CO2 sequestration availability are key drivers of energy system outcomes in deeply decarbonized energy systems.

Rahul Kumar Padhy, Krishnan Suresh, Aaditya Chandrasekhar

Latent heat thermal energy storage (LHTES) systems are compelling candidates for energy storage, primarily owing to their high storage density. Improving their performance is crucial for developing the next-generation efficient and cost effective devices. Topology optimization (TO) has emerged as a powerful computational tool to design LHTES systems by optimally distributing a high-conductivity material (HCM) and a phase change material (PCM). However, conventional TO typically limits to optimizing the geometry for a fixed, pre-selected materials. This approach does not leverage the large and expanding databases of novel materials. Consequently, the co-design of material and geometry for LHTES remains a challenge and unexplored. To address this limitation, we present an automated design framework for the concurrent optimization of material choice and topology. A key challenge is the discrete nature of material selection, which is incompatible with the gradient-based methods used for TO. We overcome this by using a data-driven variational autoencoder (VAE) to project discrete material databases for both the HCM and PCM onto continuous and differentiable latent spaces. These continuous material representations are integrated into an end-to-end differentiable, transient nonlinear finite-element solver that accounts for phase change. We demonstrate this framework on a problem aimed at maximizing the discharged energy within a specified time, subject to cost constraints. The effectiveness of the proposed method is validated through several illustrative examples.

Qingqing Weng, He Xu

Abstract One of the greatest constraints currently affecting China's economic development is climate change, with its associated restrictive conditions. Consequently, the application of appropriate actions to conserve energy and reduce emissions features centrally in China's core national development goals and development policies. These goals not only pose significant challenges and opportunities, but they also entail an important innovation. Under the framework of the Kyoto Protocol, the carbon trading market has emerged at a historic moment as an important measure for conserving energy and reducing emissions. Given the continuous development of the international carbon trading market over the last decade, China is also attempting to develop its own carbon trading market to further contribute to energy conservation and emissions reduction. Based on an analysis of the current situation of China's carbon trading market, relevant policy suggestions are offered here for its improvement, with the aim of providing guidelines for reducing carbon emissions, which are of mounting concern.

Wenwen Li, Zhengliang Hu

The shipping industry is featured by high carbon emissions. The 2023 IMO Strategy on Reduction of GHG Emissions from Ships sets forth the global goals of shipping decarbonization. Shipping decarbonization involves complicated issues of economy, technology, policy and law etc., and implies the conflicts between economic interests and environmental interests, between individual interests and public interests, between individual States’ interests and international common interests and between current interests and long-term interests. This research suggests that balancing such conflicting interests need to follow the principle of prioritizing the international public environmental interests while taking into account the other interests because protection of environmental interests should be taken as the basic value orientation in shipping decarbonization governance and the principle of collaborating governmental intervention and market mechanisms by reference to the theory on the relationship between government and market in economics. Under the guidance of these principle, by reference to the equilibrium analysis method in economics and following the progressive decision theory in management, this research demonstrates that the main pathways in achieving such balance may include: making strategic plan and basic policy for reducing GHG emissions from ships by the government, implementing economic incentive policies such as tax incentives and fiscal subsidies, implementing ship energy efficiency measures, prudently implementing shipping carbon emissions trading mechanism, accelerating the establishment of alternative marine fuel supply chain, innovating alternative marine fuel technology and ship propulsion technology, and actively engaging in international cooperation.

Maryam Doroodi, B. Ostadi, A. H. Kashan et al.

Electricity plays a pivotal role in the socio-economic development of nations. However, heavy reliance on fossil fuels for electricity generation, as observed in Iran, poses significant environmental challenges. This study proposes a novel hybrid methodology that combines system dynamics modeling and Design of Experiments (DOE) to examine economic and environmental indicators within Iran's electricity sector. The system dynamics model delineates four key subsystems: consumption, production, CO2 emissions, and power trade. By integrating DOE into this framework, various economic and environmental metrics are assessed for the year 2040. Through a comprehensive analysis of variable impacts on these indicators, optimal levels are identified to achieve favorable outcomes. Notably, variables such as the allocation coefficient of export income to capacity development and electricity export price emerge as critical determinants. Due to economic, environmental, and economic-environmental indicators, the most appropriate level of allocation of export income towards capacity development is estimated at 30, 10, and 20 percent, respectively. The study recommends allocating 80 % of the capacity development budget to renewable energy sources and 20 % to thermal power plants to optimize future conditions. In business as usual, the Export CO2 emission damage to export income index will be 0.19. In implementing the proposed scenario, according to the economic-environmental index, this value will decrease and reach 1.73E-06, which indicates the improvement of electricity export from the economic-environmental dimension. This research underscores the importance of balancing economic prosperity with environmental sustainability in electricity industry planning and policy formulation.

E. M. Hodgson, J. McCalmont, R. Rowe et al.

Abstract The UK sixth carbon budget has recommended domestic biomass supply should increase to meet growing demand, planting a minimum of 30,000 hectares of perennial energy crops a year by 2035, with a view to establishing 700,000 hectares by 2050 to meet the requirements of the balanced net zero pathway. Miscanthus is a key biomass crop to scale up domestic biomass production in the United Kingdom. A cohesive land management strategy, based on robust evidence, will be required to ensure upscaling of miscanthus cultivation maximizes the environmental and economic benefits and minimizes undesirable consequences. This review examines research into available land areas, environmental impacts, barriers to uptake, and the challenges, benefits, and trade‐offs required to upscale miscanthus production on arable land and grassland in the United Kingdom. Expansion of perennial biomass crops has been considered best restricted to marginal land, less suited to food production. The review identifies a trade‐off between avoiding competition with food production and a risk of encroaching on areas containing high‐biodiversity or high‐carbon stocks, such as semi‐natural grasslands. If areas of land suitable for food production are needed to produce the biomass required for emission reduction, the review indicates there are multiple strategies for miscanthus to complement long‐term food security rather than compete with it. On arable land, a miscanthus rotation with a cycle length of 10–20 years can be employed as fallow period for fields experiencing yield decline, soil fatigue, or persistent weed problems. On improved grassland areas, miscanthus presents an option for diversification, flood mitigation, and water quality improvement. Strategies need to be developed to integrate miscanthus into farming systems in a way that is profitable, sensitive to local demand, climate, and geography, and complements rather than competes with food production by increasing overall farm profitability and resilience.

Ege Kandemir, Agus Hasan, Trond Kvamsdal et al.

Abstract In recent years, there has been growing interest in digital twin technology in both industry and academia. This versatile technology has found applications across various industries. Wind energy systems are particularly suitable for digital twin platforms due to the integration of multiple subsystems. This study aims to explore the current state of predictive digital twin platforms for wind energy systems by surveying literature from the past five years, identifying challenges and limitations, and addressing future research opportunities. This review is structured around four main research questions. It examines commonly employed methodologies, including physics-based modeling, data-driven approaches, and hybrid modeling. Additionally, it explores the integration of data from various sources such as IoT sensors, historical databases, and external application programming interfaces. The review also delves into key features and technologies behind real-time systems, including communication networks, edge computing, and cloud computing. Finally, it addresses current challenges in predictive digital twin platforms. Addressing these research questions enables the development of hybrid modeling strategies with data fusion algorithms, which allow for interpretable predictive digital twin platforms in real time. Filter methods with dimensionality reduction algorithms minimize the computational resource demand in real-time operating algorithms. Moreover, advancements in high-bandwidth communication networks facilitate efficient data transmission between physical assets and digital twins with reduced latency.

Xi Yang, Kai Jia, Zirui Peng

Abstract This study presents a major advance in grid management: the development and deployment of an integrated network command system for the main distribution network. The system integrates cutting-edge information technology, including modules such as command issuance, intelligent routing, security assurance and in-depth data analysis, opening a new era of refined and intelligent power grid management. The research focuses on the application of core technologies such as information communication technology, distributed control system, artificial intelligence and big data analysis, and strengthens the system operation foundation. The chapter on system architecture details the innovative integration of DDQN algorithm and attention mechanism, and carefully constructs intelligent scheduling engine and status monitoring and early warning system, which significantly improves real-time response, decision optimization and active security defense capabilities. Simulation experiments and actual case analysis verify the effectiveness of the system, specifically, the response time is reduced by 75.7%(from 2.1 s to 0.51 s in the traditional system), the data processing speed is still maintained at a high level under high load (100,000 data processing rate is 300/s), and the system stability is as high as 99.97%. The new system also achieved a high degree of automation, reducing annual operation and maintenance costs by 20%, and increasing user satisfaction to 90%, an increase of 28.6% over the previous period. These improvements not only optimize power quality and grid efficiency, but also further confirm that the fault response time is reduced by 30% and the user outage time is reduced by 25%. Therefore, this study not only highlights the innovation of the proposed system, but also demonstrates its significant contribution to accelerating the modernization of power grid management and ensuring safe operation with empirical data.

Fabrizio Canfora, David Dudal, Thomas Oosthuyse et al.

Recently, dynamical edge modes (DEM) in Maxwell theory have been constructed using a specific local boundary condition on the horizon. We discuss how to enforce this boundary condition on an infinite parallel plate in the QED vacuum by introducing Lagrange multiplier fields into the action. We carefully introduce appropriate boundary ghosts to maintain BRST invariance. Explicit correspondence of this BRST extended theory with the original DEM formulation is discussed, both directly, and through the correspondence between edge modes and Wilson lines attached to the boundary surface. We then use functional methods to calculate the Casimir energy for the first time with DEM boundary conditions imposed on two infinite parallel plates, both in generalized Coulomb and linear covariant gauge. Depending on the gauge, different fields are contributing, but, after correctly implementing the BRST symmetry, we retrieve the exact same Casimir energy as for two perfectly conducting parallel plates.

Yilun Du, Jiayuan Mao, Joshua B. Tenenbaum

We introduce iterative reasoning through energy diffusion (IRED), a novel framework for learning to reason for a variety of tasks by formulating reasoning and decision-making problems with energy-based optimization. IRED learns energy functions to represent the constraints between input conditions and desired outputs. After training, IRED adapts the number of optimization steps during inference based on problem difficulty, enabling it to solve problems outside its training distribution -- such as more complex Sudoku puzzles, matrix completion with large value magnitudes, and pathfinding in larger graphs. Key to our method's success is two novel techniques: learning a sequence of annealed energy landscapes for easier inference and a combination of score function and energy landscape supervision for faster and more stable training. Our experiments show that IRED outperforms existing methods in continuous-space reasoning, discrete-space reasoning, and planning tasks, particularly in more challenging scenarios. Code and visualizations at https://energy-based-model.github.io/ired/

S. Reddy, G. Murali, A. Shaik et al.

Abstract Stringent emission norms and renewable energy policies of governments are creating necessity to adopt renewable energy sources for diesel engine applications. Changing the operating parameters of the engine is one of feasible technique to enhance the engine performance. The present experimental work is mainly focuses on the influence of changing injection timing along with different EGR rates for the research diesel engine fuelled with 20% mango seed methyl ester (MSME 20). Initially, the fuel injection timing varied at three levels such as retarded injection timing (19° bTDC), standard injection timing (23° bTDC) and advanced injection timing (25° bTDC) for the diesel engine powered with 20% mango seed biodiesel blend and compared with diesel. Based on experimentation, it was found that MSME20 blend at advanced injection timing resulted in higher BTE by 4.54% and also drastic reduction in engine exhaust emissions like carbon monoxide, hydrocarbon and smoke emissions by 32.43%, 29.26% and 15.38% when compared with MSME 20 (23° bTDC) blend at full load conditions. However, there was considerable increment in NOX emissions. In order to mitigate the NOX emissions, the engine is further operated with different EGR rates (5% and 10%) at advanced fuel injection timing. Addition of 5% EGR concentration to advanced injection timing (25° bTDC) was significantly reduced NOX emissions by 43.38% without much compromise in engine performance.

Guangwei Liu, Wenbin Yu, Xiaodong Wang et al.

Due to the harsh actual operating environment of the permanent magnet wind turbine, it is easy to break down and difficult to monitor. Therefore, the electromagnetic characteristics identification of major fault types of large-scale permanent magnet wind turbines is studied in this paper. The typical faults of rotor eccentricity, stator winding short circuit and permanent magnet demagnetization of permanent magnet wind turbines are analyzed theoretically. The wavelet analysis algorithm is used to decompose and reconstruct the abnormal electromagnetic signal waveform band, and the characteristic frequency of the electromagnetic signal is obtained when the fault occurs. In order to verify the effectiveness of the proposed method, a 3.680MW permanent magnet wind turbine was taken as the research object. Its physical simulation model was established, and an external circuit was built to carry out field co-simulation. The results show that the motor fault type can be determined by detecting the change rule of fault characteristic frequency in the spectrum diagram, and the electromagnetic characteristic analysis can be applied to the early monitoring of the permanent magnet wind turbine fault.