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

Richard York, S. Bell

Abstract Is an energy transition currently in progress, where renewable energy sources are replacing fossil fuels? Previous changes in the proportion of energy produced by various sources – such as in the nineteenth century when coal surpassed biomass in providing the largest share of the global energy supply and in the twentieth century when petroleum overtook coal – could more accurately be characterized as energy additions rather than transitions. In both cases, the use of the older energy source continued to grow, despite rapid growth in the new source. Evidence from contemporary trends in energy production likewise suggest that as renewable energy sources compose a larger share of overall energy production, they are not replacing fossil fuels but are rather expanding the overall amount of energy that is produced. We argue that although it is reasonable to expect that renewables will come to provide a growing share of the global energy supply, it is misleading to characterize this growth in renewable energy as a “transition” and that doing so could inhibit the implementation of meaningful policies aimed at reducing fossil fuel use.

Çağatay Iris, J. Lam

Abstract Many ports and terminals endeavor to enhance energy efficiency as energy prices have increased through years and climate change mitigation is a key target for the port industry. Stricter environmental regulations are adopted by authorities to limit pollutants and GHG emissions arising from energy consumption. Increasingly, port operational strategies and energy usage patterns are under scrutiny. To ingrain sustainability and environmental protection of ports, the use of innovative technology appears as a critical conduit in achieving a transition from a carbon-intensive port industry (dependent on fossil fuels) to a low-carbon port model by harnessing renewable energy, alternative fuels (e.g. LNG, hydrogen, biofuel), smarter power distribution systems, energy consumption measurement systems. In this context, this paper conducts a systematic literature review to analyze operational strategies (e.g. peak shaving, operations optimization), technology usage (e.g. electrification of equipment, cold-ironing, energy storage systems), renewable energy, alternative fuels and energy management systems (e.g. smart grid with renewable energy) for improving the energy efficiency and environmental performance of ports and terminals. Research gaps and future research directions are identified. Analysis shows that there is a great potential for ports to achieve further energy efficiency and researchers have many impactful research opportunities.

J. Bergthorson

Abstract Metal fuels, as recyclable carriers of clean energy, are promising alternatives to fossil fuels in a future low-carbon economy. Fossil fuels are a convenient and widely-available source of stored solar energy that have enabled our modern society; however, fossil-fuel production cannot perpetually keep up with increasing energy demand, while carbon dioxide emissions from fossil-fuel combustion cause climate change. Low-carbon energy carriers, with high energy density, are needed to replace the multiple indispensable roles of fossil fuels, including for electrical and thermal power generation, for powering transportation fleets, and for global energy trade. Metals have high energy densities and metals are, therefore, fuels within many batteries, energetic materials, and propellants. Metal fuels can be burned with air or reacted with water to release their chemical energy at a range of power-generation scales. The metal-oxide combustion products are solids that can be captured and then be recycled using zero-carbon electrolysis processes powered by clean energy, enabling metals to be used as recyclable zero-carbon solar fuels or electrofuels. A key technological barrier to the increased use of metal fuels is the current lack of clean and efficient combustor/reactor/engine technologies to convert the chemical energy in metal fuels into motive or electrical power (energy). This paper overviews the concept of low-carbon metal fuels and summarizes the current state of our knowledge regarding the reaction of metal fuels with water, to produce hot hydrogen on demand, and the combustion of metal fuels with air in laminar and turbulent flames. Many important questions regarding metal-fuel combustion processes remain unanswered, as do questions concerning the energy-cycle efficiency and life-cycle environmental impacts and economics of metals as recyclable fuels. Metal fuels can be an important technology option within a future low-carbon society and deserve focused attention to address these open questions.

Tekalign Aregu Tikish, Yared Worku, Nithyadharseni Palaniyandy et al.

The growing demand for green energy has made energy storage crucial in energy generation systems. Supercapacitors (SCs) are gaining popularity in energy storage due to their high-power density and long cycle life. Bimetallic cobalt oxides (MCo2O4) are promising electrode materials due to their enhanced electrochemical performance and synergistic effects. This review provides a unique and exclusive focus on the recent 5-year progress (2020–2025) in MCo2O4 materials for SC applications. It provides a detailed analysis of various synthesis processes, the relationship between crystal structure (particularly the stable spinel structure) and electrochemical activity, the inherent battery-like charge storage mechanism of cobalt oxides, and a comparative performance evaluation. It also analyzes the electrolyte in Bimetallic Metal Oxides and their composites. The review highlights the strategic inclusion of a secondary metal (M = Ni, Cu, Fe, Mn, Zn) into cobalt oxide, which enhances key metrics, including specific capacitance, rate capability, and cyclic stability. Furthermore, this review demonstrated the strategies for improving overall SC performance through composite formation with conductive additives (carbon materials, metal oxides, conducting polymers, and MOFs). Lastly, the review concludes by summarizing the advanced and outlining crucial future research pathways to guide the development of superior bimetallic cobalt oxide-based SCs.

K. Oshiro, S. Fujimori

Hydrogen-based energy carriers, including hydrogen, ammonia and synthetic hydrocarbons, are expected to help reduce residual carbon dioxide emissions in the context of the Paris Agreement goals, although their potential has not yet been fully clarified in light of their competitiveness and complementarity with other mitigation options such as electricity, biofuels and carbon capture and storage (CCS). This study aimed to explore the role of hydrogen in the global energy system under various mitigation scenarios and technology portfolios using a detailed energy system model that considers various energy technologies including the conversion and use of hydrogen-based energy carriers. The results indicate that the share of hydrogen-based energy carriers generally remains less than 5% of global final energy demand by 2050 in the 2 ◦ C scenarios. Nevertheless, such carriers contribute to removal of residual emissions from the industry and transport sectors under specific conditions. Their share increases to 10 – 15% under stringent mitigation scenarios corresponding to 1.5 ◦ C warming and scenarios without CCS. The transport sector is the largest consumer, accounting for half or more of hydrogen production, followed by the industry and power sectors. In addition to direct usage of hydrogen and ammonia, synthetic hydrocarbons converted from hydrogen and carbon captured from biomass or direct air capture are attractive transport fuels, growing to half of all hydrogen-based energy carriers. Upscaling of electrification and biofuels is another common cost-effective strategy, revealing the importance of holistic policy design rather than heavy reliance on hydrogen.

M. Donno

The year 2022 marked a turning point for global energy security, forcing nations to rethink their reliance on traditional fossil fuels. The geopolitical turmoil triggered by Russia's invasion of Ukraine exposed critical vulnerabilities in energy supply chains, particularly in Europe, where the dependence on imported oil and natural gas led to extreme price volatility and uncertainty. This crisis accelerated the need for stable, low-carbon, and geopolitically secure energy sources, bringing nuclear power and uranium back to the forefront of energy policy discussions. As countries worked to diversify their energy portfolios and enhance supply security, nuclear energy emerged as a key pillar of the energy transition. Governments once hesitant about nuclear power began reversing their phase-out policies, extending the lifetimes of existing reactors, and investing in new-generation nuclear technologies. This renewed momentum for nuclear energy has significantly increased uranium demand, leading to structural supply challenges, price surges, and a reevaluation of global uranium trade dynamics, especially for Western countries. This article explores the evolving role of uranium in the modern energy landscape, analyzing key consumption trends, supply challenges, geopolitical risks, and technological advancements shaping the future of the nuclear industry. With nuclear energy expanding across both established and emerging markets, uranium is set to play a critical role in securing a resilient, low-carbon, and geopolitically stable energy future.

Yu Zhou

Abstract Aiming at the critical challenges of fragmented environmental-economic value tracking and inefficient multi-stakeholder coordination in green electricity trading, this study proposes a blockchain-based collaborative management method integrating environmental attributes (e.g., carbon offsets) with economic transactions. Leveraging blockchain’s decentralized, tamper-proof distributed ledger, the method ensures transaction transparency, automates settlement via smart contracts, and establishes a verifiable audit trail for environmental benefits. Experimental comparisons demonstrate that the blockchain platform ​reduces transaction costs by 30%, shortens settlement time by 75%, and significantly enhances market liquidity and transparency versus traditional modes. This approach optimizes resource allocation, minimizes intermediary dependencies, and provides a robust technical pathway for scaling green power adoption. Key implementation barriers include blockchain’s energy consumption, smart contract vulnerabilities, and regulatory fragmentation across jurisdictions. Future work will focus on enhancing blockchain energy efficiency and developing cross-regional regulatory frameworks for green power markets.

Mamta Motiramani, Priyanshi Solanki, Vidhi Patel et al.

Green hydrogen is a cleaner source to replace fossil-based fuels and is critical in the global shift toward energy production to combat climate change. This review of embedding artificial intelligence (AI) and machine learning (ML) in the value chain of green hydrogen outlines the significant potential for full transformation. These include optimizing the utilization of renewable sources of energy, improving electrolysis process, hydrogen storage in the salt cavern that has better condition, and smarter systems in distribution side with inexpensive logistics. In this, it nullifies leak risks and safeguards the safety operations with detection using AI. Consequently, it positions the paper emphasizing AI-ML approaches demonstrating significant advancements in efficiency and sustainability in green hydrogen technology.

Muhammad Imran, Muhammad Tufail, Chen Mo et al.

As Asia faces the dual challenges of rapid economic expansion and mounting environmental pressures, the region's ability to balance growth with sustainability has become a focal point of global discourse. With increasing energy demands, escalating CO₂ emissions, and widening income inequality, an integrated approach to managing natural resources has never been more critical. This study responds to this urgent need by examining the complex interplay between energy consumption, living standards, and natural resource rents—factors that will determine whether Asia can sustain its growth without depleting its ecological assets. Our analysis incorporates key variables such as standard of living, income inequality, renewable and nonrenewable energy consumption, CO₂ emissions, gross fixed capital formation, and foreign direct investment, all of which play crucial roles in shaping natural resource rents across Asian economies. Using Moment Quantile Regression (MMQR), we uncover nuanced insights into how these factors interact across different economic contexts. The findings reveal a negative correlation between higher living standards and resource rents, indicating that countries like Japan and South Korea, which have transitioned to more diversified, technology-driven sectors, demonstrate a pathway for sustainable growth. Conversely, economies like Indonesia and Malaysia, with lower living standards and higher dependence on resource rents, face challenges related to income inequality and environmental degradation. Renewable energy consumption positively impacts resource rents, while reliance on fossil fuels has a detrimental effect, reinforcing the need for energy portfolio diversification. A strong link between CO₂ emissions and resource rents highlights the necessity of balancing economic growth with environmental preservation. This study provides policymakers with actionable insights, emphasizing the importance of adopting sustainable energy practices, addressing income inequality, and managing foreign investments responsibly to ensure long-term resilience and prosperity in Asian economies while safeguarding vital natural resources for future generations.

Shobanadevi Ayyavu, Md Shohel Sayeed, Siti Fatimah Abdul Razak

Abstract Accurate and robust wind power prediction for wind farms could significantly decrease the substantial effect on grid operating safety caused by integrating high-permeability intermittent power supplies into the power grid. The article introduces a new wind power multistep prediction model combining Variational Mode De-composition (VMD) with the Long Short-Term Enhanced Forget Gate (LSTM_EFG) network. The VMD is occupied to break down the initial wind power and speed data into various sub-layers. The LSTM_EFG network predicts the low-frequency sub-layers extracted from the VMD. In contrast, the Artificial Bee Colony optimization algorithm fine-tunes the network for the high-frequency sub-layers acquired from the VMD-LSTM-EFG model. The high performance of projected methods in multistep prediction was evaluated by comparing them with eight different models. Results from four experiments show that: (a) the projected model exhibits the most superior multistep prediction performance out of all models tested; (b) in comparison to other models, the proposed model proves to be more efficient and resilient in capturing trend information. The implementation of accurate wind power prediction models continues to pose challenges due to the unpredictable, sudden, and seasonal changes in wind patterns.

Harald Winkler, A. Black

ABSTRACT South Africa faces huge challenges of poverty and unemployment, yet at the same time, needs to make a contribution to climate action. Historically, our pattern of development gave rise to the ‘minerals-energy complex’, locking us into low employment and high emissions development. It has proved difficult to change this structure, with political economy interests opposing shifts and high adjustment costs. We analyse policy instruments that can reshape the development path: reducing incentives to capital-intensive and high emissions heavy industry, ending direct and indirect support for cheap electricity, and removing fossil fuel subsidies. Industrial policy should pay attention to creating comparative advantage in more labour-demanding sectors. Agriculture can create employment, while enhancing carbon sinks. Based on our exploration of such policy instruments, we suggest that future development can align employment and mitigation objectives, seeking synergies across industrial, energy, and climate policy, while at the same time managing trade-offs.

Andres Sebastian Cespedes-Cubides, Muhyiddine Jradi

Abstract The majority of Europe’s building stock consists of facilities built before 2001, presenting a substantial opportunity for energy efficiency improvements during their operation and maintenance phase. Digitalizing these buildings with digital twin technology can significantly enhance their energy efficiency. Reviewing the applications and trends of digital twins in this context is beneficial to understand the current state of the art and the specific challenges encountered when applying this technology to older buildings. This study focuses on the application of digital twins in building operations and maintenance (O & M), emphasizing energy efficiency throughout the building lifetime. A systematic process to select 21 pertinent use-case studies was performed, complemented by an analysis of six enterprise-level digital twin solutions. This was followed by an overview of general characteristics, thematic classification, detailed individual study analyses, and a comparison of digital twin solutions with commercial tools. Five main applications of digital twins were identified and examined: component monitoring, anomaly detection, operational optimization, predictive maintenance and simulation of alternative scenarios. The paper highlights challenges like the reliance on Building Information Modeling (BIM) and the need for robust data acquisition systems. These limitations hinder the implementation of digital twins, in particular in existing buildings with no digital information available. It concludes with future research directions emphasizing the development of methods not solely reliant on BIM data, integration challenges, and potential enhancements through AI and machine learning applications.

Mariam El Jaadi, Touria Haidi, Abdelaziz Belfqih et al.

With the growing need for renewable energy, wind farms are playing an important role in generating clean power from wind resources. The best wind turbine architecture in a wind farm has a major influence on the energy extraction efficiency. This paper describes a unique strategy for optimizing wind turbine locations on a wind farm that combines the capabilities of particle swarm optimization (PSO) and artificial neural networks (ANNs). The PSO method was used to explore the solution space and develop preliminary turbine layouts, and the ANN model was used to fine- tune the placements based on the predicted energy generation. The proposed hybrid technique seeks to increase energy output while considering site-specific wind patterns and topographical limits. The efficacy and superiority of the hybrid PSO-ANN methodology are proved through comprehensive simulations and comparisons with existing approaches, giving exciting prospects for developing more efficient and sustainable wind farms. The integration of ANNs and PSO in our methodology is of paramount importance because it leverages the complementary strengths of both techniques. Furthermore, this novel methodology harnesses historical data through ANNs to identify optimal turbine positions that align with the wind speed and direction and enhance energy extraction efficiency. A notable increase in power generation is observed across various scenarios. The percentage increase in the power generation ranged from approximately 7.7% to 11.1%. Owing to its versatility and adaptability to site-specific conditions, the hybrid model offers promising prospects for advancing the field of wind farm layout optimization and contributing to a greener and more sustainable energy future.

N. Trivyza, A. Rentizelas, G. Theotokatos et al.

The shipping sector has been under great pressure since the last decade to improve its environmental footprint, more so recently with the International Maritime Organisation target for a 50% reduction in greenhouse gas emissions by 2050, benchmarked to 2008 levels. These challenging goals have increased the interest towards alternative fuels and ship energy systems that can offer a more sustainable performance. The variety of potential technological solutions along with the multiple criteria employed to evaluate the ship energy systems with respect to sustainability considerations, renders the decision-making process for selecting ship energy systems challenging and highlights the need for dedicated decision support methods. This study presents a state-of-the-art review of the literature on decision support methods for enhancing the ship energy systems sustainability. The trends and gaps in the literature are identified, based on which, recommendations for future research are proposed. This study findings indicate that, among others, further research is needed to adapt more holistic approaches that include safety and reliability indicators as well as the social aspect of sustainability. This review can be beneficial for the maritime industry stakeholders, including policy makers, academics and ship owners/operators.

Shiwei Yu, Shuhong Zheng, Xia Li et al.

China has committed to a peak in carbon dioxide emissions circa 2030. However, current policies cannot meet this ambitious goal. Adjusting its energy-intensive, heavy and chemical-based industrial structure is not only the main way China can change its economic growth pattern but also a key policy strategy to achieve its carbon emission peak goal. In addition to carbon emissions goals, economic growth and employment security must be considered for China's development in the context of addressing climate change. Hence, by proposing a new economic-carbon emission-employment multi-objective optimization model, we take a different approach to analyze China's emissions trajectory. The optimized results show that China's energy-related carbon dioxide emissions could peak between 2022 and 2025, most likely in 2023, with CO2 emissions of 11.21–11.56 Gt. When pursuing this peak (from 2013 to 2030), China could still maintain an average growth of approximately 6.1 to 6.4% yr−1 for GDP and approximately 0.24% to 0.51% yr−1 for employment. Furthermore, China's coal consumption has peaked in 2013 while oil would be peaked around 2023 to 2025, based on the optimized industrial structure adjustment trajectory from 2013 to 2030.

Zixing WANG, Meie YANG, Haopeng WANG et al.

[Introduction] Hydrogen energy is characterized by the advantages of wide sources, high calorific value, storability, no pollution, and zero carbon emissions. It has become a zero-carbon clean energy with great development potential. At present, mature hydrogen production technologies are mostly based on large-scale hydrogen production, which can hardly meet the demand for compact portable hydrogen production equipment in some important occasions. [Method] In order to meet this demand, this paper first analyzed and summarized the characteristics, advantages and disadvantages, and development trends of the existing large-scale hydrogen production technologies. Besides, considering that ammonia has the advantages of easy liquefaction and storage and high hydrogen content and is an excellent carrier for hydrogen, this paper further proposed the technical idea of using porous medium burner with adiabatic flame temperature to produce hydrogen by ammonia reformation and carried out a systematic analysis from the aspects of technical feasibility, research methods and research contents. [Result] Based on the existing research results of porous medium burners, the feasibility of using porous medium burner for ammonia reforming to produce hydrogen is analyzed. On this basis, the research methods, research contents and technical routes of ammonia reforming for hydrogen production by using porous medium burner are summarized and prospected. [Conclusion] Obtaining the optimal design for the overall structure, microchannel, and reaction carrier structure of the porous medium burner and developing non-precious metal catalyst materials with good performance and low cost will be the main research directions of the porous medium burner for hydrogen production by ammonia reforming. The research in this paper can provide some theoretical and technical support for the development of the technology of hydrogen production by ammonia reforming with porous medium burner.

Nihad Hodžić, Kenan Kadić, Anes Kazagić

The thermal energy sector is very important at this time of global energy transition. From the aspect of stable energy independence, this is especially important in countries whose energy system is based on fossil fuels, especially coal. This is why decarbonisation of the energy sector is necessary, with a partial and gradual substitution of coal with renewable fuels. However, the use of these fuels is not always possible in existing plants. This refers to the establishment of energy, economic and environmentally acceptable proportion of the co-firing of these fuels, i.e. a mixture of coal and renewable fuels. The success of the establishment of this process is a function of several variables, the dominant of which are the aggregate properties of the fuel, basic and their mixtures, including the ash properties of those fuels. With the motive of contributing to a more successful implementation of the energy transition in the thermal energy sector, and with the aim of obtaining new scientific knowledge about the characteristics of the combustion of lignite and brown coal with different renewable fuels, laboratory research was carried out. In particular, different mixtures of lignite and brown coal, waste woody biomass and Miscanthus as a fast-growing energy crop were subjected to co-firing with variable process conditions. In addition to changing the composition of fuel mixtures, the test regimes included a significant change in process temperature (1250-1450 °C) and the primary measure of staged air supply to the furnace. In these combustion conditions, the emission of undesirable and harmful components into the environment, the efficiency of combustion, and the tendency of the ash from the fuel mixture to possible soiling of the heating surfaces in the furnace were evaluated – an analysis of the characteristics of the ash samples from the reaction zone and samples of the slag and ash to the furnace. Here, in both cases of co-firing, lignite and brown coal with different types of biomass, it was shown that in real conditions it is possible to establish a sustainable primary energy conversion process from fuel with a low unburnt carbon content in the slag (unburnt carbon content, UBC<1%) as well as low CO emission, below 350 mg/mn3. At the same time, the NOx emission is below 320 mg/mn3 during the co-firing of lignite mixtures at 1250 °C, and in the case of brown coal mixtures below 740 mg/mn3 at 1450 °C. In both cases, the net CO2 emission decreases in proportion to the proportion of biomass in the mixture, while the SO2 emission is still high, at a level of up to 2500 mg/mn3 for lignite mixtures and up to 6400 mg/mn3 for brown coal mixtures. None of the treated types of biomass, up to the level of applicable content in the mixture with lignite and brown coal, does not worsen the progress of the process from the aspect of possible slagging/fouling heating surfaces in the boiler.

Xinlei Liu, Priybrat Sharma, Mickael Silva et al.

This work explored the potential of methanol pre-chamber combustion (PCC) for heavy-duty engine applications. An optical engine experiment was conducted to visualize the jet flame development. The measured pressure traces and natural flame luminosity images were also used for the validation of three-dimensional computational fluid dynamics simulations. It was demonstrated that the main chamber (MC) combustion was successfully established by the reactive jet issued from the pre-chamber. Compared to methane PCC in our previous study, the distributed reacting jets were significantly thinner, in particular at the learner condition. The active PCC mode, which comprises enrichment of the mixture in the pre-chamber (PC) by means of direct methane injection, was effective in improving the engine performance. However, excessive PC fueling ratio (PCFR) resulted in lower thermal efficiency due to the higher wall heat transfer and combustion losses. In addition, the effects of various PC and piston geometries on the methanol/methane PC combustion were evaluated. The combination of an optimized PC and a flat piston yielded the highest thermal efficiency owing to the relatively lower combustion and wall heat transfer losses. At engine loads higher than 12.5 bar indicated mean effective pressure, exhaust gas recirculation must be implemented to avoid end-gas autoignition and reduce nitric oxides (NOx) emissions. As expected, the increase in (CR) further promoted engine work because of the higher expansion ratio. With CR of 13 and 14, higher thermal efficiency and lower NOx emission were simultaneously achieved under both intermediate and high loads when the engine was operating at the pure methanol PC combustion mode.

Zhongwei Li, Yang Liu, Peng Qiu et al.

Abstract With the increase in inverter‐based renewable energy resources, the complexity and uncertainty of low‐carbon power systems have increased significantly. Deep reinforcement learning (DRL)–based approaches have been extensively studied for frequency control to overcome the limitations of traditional model‐based approaches. The goal of DRL‐based methods for primary frequency control is to minimise load shedding while satisfying frequency safety requirements, thereby reducing control costs. However, the vulnerabilities of DRL models pose new security threats to power systems. These threats have not been identified and addressed in the existing literature. Therefore, here, a series of vulnerability assessment methods are proposed for DRL‐based frequency control with a focus on the under‐frequency load shedding (UFLS) problem. Three adversarial sample production methods are designed with different optimisation directions: Q‐value‐based FGSM (Q‐FGSM), action‐based JSMA (A‐JSMA), and state‐action‐based CW (SA‐CW). Furthermore, combining the advantages of the above three attack methods, a hybrid adversarial attack algorithm is designed, Q‐value‐state‐action‐based mix (QSA‐MIX), to significantly affect the decision process of the DRL model. In case studies of the IEEE39 bus system, the proposed attack methods had a severe impact on system operation and control. In particular, the high attack transferability of the proposed attack algorithms in a black‐box setting provides further evidence that the vulnerability of current DRL‐based control schemes is prevalent.

P. Zeppini, J. Bergh

We develop a stochastic decision model to analyse the global competitive dynamics of fossil fuels and renewable energy. It describes coal, oil/gas, solar and wind. These differ not only in pollution intensities but also in profitability and innovation potential. The model accounts for the effect of learning curves, path-dependence and climate policies. Adoption shares endogenously affect agents' utility through increasing returns to adoption, learning, and a ‘peak oil’ capacity constraint. We find that peak oil induces a transition to coal rather than renewable energy, which worsens climate change. By introducing climate policies - such as a carbon tax, market adoption or RD and how uncertain or variable are final market shares of energy sources.