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

Kaiyuan Zhai, Jiacheng Cui, Zhehao Zhang et al.

Cross-domain HVAC energy prediction is essential for scalable building energy management, particularly because collecting extensive labeled data for every new building is both costly and impractical. Yet, this task remains highly challenging due to the scarcity and heterogeneity of data across different buildings, climate zones, and seasonal patterns. In particular, buildings situated in distinct climatic regions introduce variability that often leads existing methods to overfit to spurious correlations, rely heavily on expert intervention, or compromise on data diversity. To address these limitations, we propose CaberNet, a causal and interpretable deep sequence model that learns invariant (Markov blanket) representations for robust cross-domain prediction. In a purely data-driven fashion and without requiring any prior knowledge, CaberNet integrates i) a global feature gate trained with a self-supervised Bernoulli regularization to distinguish superior causal features from inferior ones, and ii) a domain-wise training scheme that balances domain contributions, minimizes cross-domain loss variance, and promotes latent factor independence. We evaluate CaberNet on real-world datasets collected from three buildings located in three climatically diverse cities, and it consistently outperforms all baselines, achieving a 22.9% reduction in normalized mean squared error (NMSE) compared to the best benchmark. Our code is available at https://github.com/SusCom-Lab/CaberNet-CRL.

Youssef Shaker, Jun Wen Law, Audun Botterud et al.

Policies focused on deep decarbonization of regional economies emphasize electricity sector decarbonization alongside electrification of end-uses. There is growing interest in utilizing hydrogen (H2) produced via electricity to displace fossil fuels in difficult-to-electrify sectors. One such case is heavy-duty vehicles (HDV), which represent a substantial and growing share of transport emissions as light-duty vehicles electrify. Here, we assess the bulk energy system impact of decarbonizing the HDV segment via either H2, or drop-in synthetic liquid fuels produced from H2 and CO2. Our analysis soft-links two modeling approaches: (a) a bottom-up transport demand model producing a variety of final energy demand scenarios for the same service demand and (b) a multi-sectoral capacity expansion model that co-optimizes power, H2 and CO2 supply chains under technological and policy constraints to meet exogenous final energy demands. Through a case study of Western Europe in 2040 under deep decarbonization constraints, we quantify the energy system implications of different levels of H2 and synthetic fuels adoption in the HDV sector under scenarios with and without CO2 sequestration. In the absence of CO2 storage, substitution of liquid fossil fuels in HDVs is essential to meet the deep decarbonization constraint across the modeled power, H2 and transport sectors. Additionally, utilizing H2 HDVs reduces decarbonization costs and fossil liquids demand, but could increase natural gas consumption. While H2 HDV adoption reduces the need for direct air capture (DAC), synthetic fuel adoption increases DAC investments and total system costs. The study highlights the trade-offs across transport decarbonization pathways, and underscores the importance of multi-sectoral consideration in decarbonization studies.

Zhenkai Qin, Jing Ma, Mingfu Zhu et al.

This research focuses on technological progress in energy storage for changing impacts concerning sustainable energy policies and electricity generation within the G-10 countries between 1996 and 2021. It discusses the improvements that energy storage technologies, including lithium-ion batteries, flow batteries, and hydrogen storage systems, bring to the power grid reliability, renewable energy integration, and carbon dioxide emission reduction. By developing a reciprocated relationship between energy storage technologies, renewable energy adoption, and technological advancement, the study offers a thorough analysis of the effects of each on the attainment of sustainable development goals 7 and 13. Thus, the application of the conclusions revealed that advanced energy storage technologies are essential for making energy systems more stable, reducing carbon emissions, and promoting the diversification of the economy in line with environmental objectives. Some policy guidelines include rising investments in energy storage innovations, development, supportive tax policies, and strengthening global cooperation. Therefore, this research highlights the importance of providing sufficient and relevant solutions for productive implementation to spread the international use of the energy storage system, which helps achieve other targets of net-zero development.

Breffní Lennon, Tamara Hajdu, Niall P Dunphy et al.

Forming energy communities and the governance structures needed to facilitate their development is proving more difficult than previously foreseen. This is evidenced by the rather uneven development of sustainable energy communities in Europe and beyond. Living labs offer a useful pathway for co-creating the dynamic renewable energy ecosystems needed to foster user-driven innovation, particularly with regards to integrating digital technology into the engagement practices of citizens in new energy communities. This paper uses the COM-B Model of behaviour to explore the potential of living labs in facilitating more active participation and co-creation among stakeholders, particularly in terms of integrating demand response strategies that foster collaborative end-user engagement. Indeed, it is this interplay between information and communication technology (ICT) and innovation which emerges from living labs that can empower participants to co-design solutions that are more responsive to real-world needs. Also, it should lead to fostering more sustainable changes in behaviour and improve the efficacy of the technical solutions available to us. This paper presents recent findings from multinational European research utilising the living lab model and the collaborative environment it provided for citizens to vision the types of participation they prioritise in bridging the gap between technological potential and user-centric innovation. Such collaborative, co-learning opportunities offer a means towards ensuring current ICT advancements align with the practical demands of the low-carbon societies we wish to create.

Matthew J. Cleary, Bosen Wang, Zixin Chi et al.

The atomisation and combustion of liquid fuel sprays involve a complex interplay of processes, including interface dynamics, primary and secondary atomisation, droplet dispersion, evaporation, mixing, chemical reactions and heat release. These processes are influenced by multiscale turbulent interactions and interphase coupling. Accurate modelling of such flows requires integrating models for each process in a consistent, computationally efficient manner. This paper reviews the field, detailing key aspects and evaluating the performance of established and emerging modelling approaches within single-fluid and two-fluid paradigms. Emphasis is placed on large eddy simulation, conserved scalar formulations, and probability density function models, which offer elegant and tractable solutions for predicting spray atomisation and combustion.

Jafar Sadeghi, Saeed Noori Gashti, Mohammad Reza Alipour et al.

In this paper, we explore the intriguing interplay between fundamental theoretical physics concepts within the context of charged black holes. Specifically, we focus on the consistency of the weak gravity conjecture (WGC) and weak cosmic censorship conjecture (WCCC) in the thermodynamics of conformal field theory (CFT), and restricted phase space thermodynamics (RPST) for AdS Reissner-Nordstrom black holes with a perfect fluid dark matter (RN-PFDM). The WGC ensures that gravity remains the weakest force in the system. Meanwhile, the WCCC addresses the cosmic censorship problem by preventing the violation of fundamental physical laws near the black hole singularity. First, we analyze the RN black hole's free energy in both spaces, revealing a distinctive swallowtail pattern indicative of a first-order phase transition when certain free parameter conditions are met. We explore the WGC across different phase spaces, emphasizing the need for certain conditions in extended phase space thermodynamics (EPST), RPST, and CFT. We demonstrate that PFDM parameter \( γ\) and the radius of AdS \( l \) have a vital role in proving the satisfaction of the WGC. Also, these values have a linear relation with the range compatibility of WGC. The range of compatibility for WGC in RPST and EPST is the same while for CFT, this range is larger than EPST, and RPST. It means somehow the WGC and CFT are more consistent. The WCCC was examined at the critical juncture, confirming its validity in critical points. We conclude that the WGC is supported at the critical point of black holes, and the WCCC is also maintained, demonstrating the robustness of these conjectures within the critical ranges of black hole parameters

Olivia Vitale, Maha Haji

Maximizing the durability and reliability of offshore wind farms is essential for the clean energy transition. In this work, we demonstrate how wave energy converter (WEC) farms can shelter offshore wind farms from cyclic wave loading, resulting in significant reductions in turbine fatigue damage. Using experimentally validated hydrodynamic models, we show that WEC arrays can reduce wave-induced fatigue damage on the turbines by up to 25%, potentially lowering required monopile diameters and extending turbine lifetimes. This damage reduction propagates to the levelized cost of energy (LCOE) of the wind farm, targeting cost reductions in nearly 50% of the total system costs. Additionally, WEC farms can benefit from this co-location by sharing siting costs, operation and maintenance teams, and mooring and transmission cables with the offshore wind farm. This work supports resilient, cost-effective offshore renewables for global deployment.

Tao Tan, Rui Xie, Xiaoyuan Xu et al.

Abstract Robust optimization is an essential tool for addressing the uncertainties in power systems. Most existing algorithms, such as Benders decomposition and column‐and‐constraint generation (C&CG), focus on robust optimization with decision‐independent uncertainty (DIU). However, increasingly common decision‐dependent uncertainties (DDUs) in power systems are frequently overlooked. When DDUs are considered, traditional algorithms for robust optimization with DIUs become inapplicable. This is because the previously selected worst‐case scenarios may fall outside the uncertainty set when the first‐stage decision changes, causing traditional algorithms to fail to converge. This study provides a general solution algorithm for robust optimization with DDU, which is called dual C&CG. Its convergence and optimality are proven theoretically. To demonstrate the effectiveness of the dual C&CG algorithm, we used the do‐not‐exceed limit (DNEL) problem as an example. The results show that the proposed algorithm can not only solve the simple DNEL model studied in the literature but also provide a more practical DNEL model considering the correlations among renewable generators.

Binglong Han, Hangxin Li, Shengwei Wang

Buildings have great energy flexibility potential to manage supply-demand imbalance in power grids with high renewable penetration. Accurate and real-time quantification of building energy flexibility is essential not only for engaging buildings in electricity and grid service markets, but also for ensuring the reliable and optimal operation of power grids. This paper proposes a probabilistic model for rapidly quantifying the aggregated flexibility of buildings under uncertainties. An explicit equation is derived as the analytical solution of a commonly used second-order building thermodynamic model to quantify the flexibility of individual buildings, eliminating the need of time-consuming iterative and finite difference computations. A sampling-based uncertainty analysis is performed to obtain the distribution of aggregated building flexibility, considering major uncertainties comprehensively. Validation tests are conducted using 150 commercial buildings in Hong Kong. The results show that the proposed model not only quantifies the aggregated flexibility with high accuracy, but also dramatically reduces the computation time from 3605 s to 6.7 s, about 537 times faster than the existing probabilistic model solved numerically. Moreover, the proposed model is 8 times faster than the archetype-based model and achieves significantly higher accuracy.

Boxu Chen, Manshuo Feng, Yi Chen et al.

Abstract Electrocatalytic CO2 reduction technology offers an effective way to convert CO2 into valuable chemicals and fuels, presenting a sustainable solution for carbon emissions. Current electrocatalytic CO2 reduction technologies encounter significant issues such as salt precipitation and hydrogen evolution, which prevent energy conversion efficiency, selectivity, current density, and stability from simultaneously meeting industrial standards. In recent years, researchers have discovered that increasing the CO2 pressure on the gas supply could enhance the coverage of the catalyst and activate more CO2 reduction reaction sites on the catalyst surface, which provides a practical and effective approach for optimizing the energy conversion and mass transfer. In this review, we provide a comprehensive review of the development history and current status of high-pressure CO2 electrocatalytic reduction technology, focusing on its reaction devices, catalytic performance, and reaction mechanisms. Furthermore, we summarize and offer insights into the most promising research avenues to propel the field forward.

Hikaru Hoshino, Yosuke Irie, Eiko Furutani

The profitability of solar energy self-consumption in households, the so-called photovoltaic (PV) self-consumption, is expected to boost the deployment of PV and battery storage systems. This paper develops a novel method for economic analysis of PV self-consumption using battery storage based on an extension of the Screening Curve Method (SCM). The SCM enables quick and intuitive estimation of the least-cost generation mix for a target load curve and has been used for generation planning for bulk power systems. In this paper, we generalize the framework of existing SCM to take into account the intermittent nature of renewable energy sources and apply it to the problem of optimal sizing of PV and battery storage systems for a household. Numerical studies are provided to verify the estimation accuracy of the proposed SCM and to illustrate its effectiveness in a sensitivity analysis, owing to its ability to show intuitive plots of cost curves for researchers or policy-makers to understand the reasons behind the optimization results.

Eva Lewin, Andreas Kiesel, Elena Magenau et al.

Abstract Perennial energy grasses have gained attention in recent years as a promising resource for the bioeconomy because of their benign environmental profile, high stress tolerance, high biomass yields and low input requirements. Currently, strong breeding efforts are being made to extend the range of commercially available miscanthus and switchgrass genotypes. In order to foster farmers' acceptance of these crops, and especially of novel hybrids, more information is required about how they can be efficiently integrated into cropping rotations, how they can be removed at the end of their productive lifespan, and what effect they have on subsequently grown crops. Farmers in Europe are meanwhile increasingly constrained in the methods available to them to remove these crops, and there is a risk that the herbicide glyphosate, which has been used in many studies to remove them, will be banned in coming years. This study looks at the removal of seven‐year‐old stands of miscanthus and switchgrass over 1 year at an experimental site in Southern‐Germany. Three novel miscanthus genotypes were studied, alongside one variety of switchgrass, and the impact of each crop's removal on the yield of maize grown as a follow‐on crop was examined. A combination of soil tillage and grass herbicides for maize cultivation was successful in controlling miscanthus regrowth, such that yields of maize grown after miscanthus did not differ significantly from yields of maize grown in monoculture rotation (18.1 t dry biomass ha−1). Yields of maize grown after switchgrass (14.4 t dry biomass ha−1) were significantly lower than maize in monoculture rotation caused by insufficient control of switchgrass regrowth by the applied maize herbicide. Although some regrowth of miscanthus and switchgrass was observed in the follow‐on crop maize, complete eradication of both crops was achieved by subsequent winter wheat cultivation.

Pooya Hoseinpoori, Richard Hanna, Jeremy Woods et al.

This paper uses a whole-system approach to examine different strategies related to the future role of the gas grid in a low-carbon heat system. A novel model of integrated gas, electricity and heat systems, HEGIT, is used to investigate four key sets of scenarios for the future of the gas grid using the UK as a case study: (a) complete electrification of heating; (b) conversion of the existing gas grid to deliver hydrogen; (c) a hybrid heat pump system; and (d) a greener gas grid. Our results indicate that although the infrastructure requirements, the fuel or resource mix, and the breakdown of costs vary significantly over the complete electrification to complete conversion of the gas grid to hydrogen spectrum, the total system transition cost is relatively similar. This reduces the significance of total system cost as a guiding factor in policy decisions on the future of the gas grid. Furthermore, we show that determining the roles of low-carbon gases and electrification for decarbonising heating is better guided by the trade-offs between short- and long-term energy security risks in the system, as well as trade-offs between consumer investment in fuel switching and infrastructure requirements for decarbonising heating. Our analysis of these trade-offs indicates that although electrification of heating using heat pumps is not the cheapest option to decarbonise heat, it has clear co-benefits as it reduces fuel security risks and dependency on carbon capture and storage infrastructure. Combining different strategies, such as grid integration of heat pumps with increased thermal storage capacity and installing hybrid heat pumps with gas boilers on the consumer side, are demonstrated to effectively moderate the infrastructure requirements, consumer costs and reliability risks of widespread electrification. Further reducing demand on the electricity grid can be accomplished by complementary options at the system level, such as partial carbon offsetting using negative emission technologies and partially converting the gas grid to hydrogen.

Bilal Kazmi, Syed Imran Ali, Zahoor Ul Hussain Awan

Energy may be generated in large quantities from fossil fuels, but this comes with environmental concerns. Thus, renewable resources like biogas, comprising carbon dioxide and methane, should be used alone or in combination with fossil fuels to mitigate the environmental footprints of energy generation systems. In this study, a new concept of hybrid solvent was presented, which combines 1-octyl-3-methylimidazolium tetrafluoroborate with aqueous mono diethanolamine for biogas upgrading process to provide high purity (≥ 99 wt%) and recovery (≥ 99 wt%) of biomethane. The process was simulated in ASPEN Plus® V.11. The thermodynamic framework was validated against experimental data, and rigorous regression was conducted to obtain binary parameters. To establish the efficacy of the suggested hybrid solvent, three scenarios were studied by altering the concentration of ionic liquid (5–20 wt%) linked with amine and compared to aqueous mono diethanolamine as the base case (50 wt%). The results showed that a hybrid solvent with 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate could increase CH4 purity to 99% (mol%). The hybrid solvent led to an energy saving of 64.94% compared to the amine-based system. Thermodynamic irreversibilities showed that 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate improved exergy efficiency by 54% over the amine-based procedure. Environmentally, the hybrid solvent system also achieved a higher capture rate (99%) and lower emissions (0.017 kW/kmol). Comparing the economic prospects, 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate saved 56% on total capital cost, making it competitive from an investment perspective.

Benedikt Heidrich, Lisa Mannsperger, Marian Turowski et al.

Abstract Sustainable energy systems are characterised by an increased integration of renewable energy sources, which magnifies the fluctuations in energy supply. Methods to to cope with these magnified fluctuations, such as load shifting, typically require accurate short-term load forecasts. Although numerous machine learning models have been developed to improve short-term load forecasting (STLF), these models often require large amounts of training data. Unfortunately, such data is usually not available, for example, due to new users or privacy concerns. Therefore, obtaining accurate short-term load forecasts with little data is a major challenge. The present paper thus proposes the latent space-based forecast enhancer (LSFE), a method which combines transfer learning and data augmentation to enhance STLF when training data is limited. The LSFE first trains a generative model on source data similar to the target data before using the latent space data representation of the target data to generate seed noise. Finally, we use this seed noise to generate synthetic data, which we combine with real data to enhance STLF. We evaluate the LSFE on real-world electricity data by examining the influence of its components, analysing its influence on obtained forecasts, and comparing its performance to benchmark models. We show that the Latent Space-based Forecast Enhancer is generally capable of improving the forecast accuracy and thus helps to successfully meet the challenge of limited available training data.

Md Nasimul Islam Maruf

The ambitious energy target to achieve climate-neutrality in the European Union (EU) energy system raises the feasibility question of using only renewables across all energy sectors. As one of the EU's leading industrialized countries, Germany has adopted several climate-action plans for the realistic implementation and maximum utilization of renewable energies in its energy system. The literature review shows a clear gap in comprehensive techniques describing an open modeling approach for analyzing fully renewable and sector-coupled energy systems. This paper outlines a method for analyzing the 100% renewable-based and sector-coupled energy system's feasibility in Germany. Based on the open energy modeling framework, an hourly optimization tool 'OSeEM-DE' is developed to investigate the German energy system. The model results show that a 100% renewable-based and sector-coupled system for electricity and building heat is feasible in Germany. The investment capacities and component costs depend on the parametric variations of the developed scenarios. The annual investment costs vary between 17.6 and 26.6 bn Euro/yr for volatile generators and between 23.7 and 28.8 bn Euro/yr for heat generators. The model suggests an investment of a minimum of 2.7-3.9 bn Euro/yr for electricity and heat storage. Comparison of OSeEM-DE results with recent studies validates the percentage-wise energy mix composition and the calculated Levelized Cost of Electricity (LCOE) values from the model. Sensitivity analyses indicate that storage and grid expansion maximize the system's flexibility and decrease the investment cost. The study concludes by showing how the tool can analyze different energy systems in the EU context.

Pei Huang, Marco Lovati, Xingxing Zhang et al.

Distributed renewable energy systems are now widely installed in many buildings, transforming the buildings into electricity prosumers. Existing studies have developed some advanced building side controls that enable renewable energy sharing and that aim to optimise building-cluster-level performance via regulating the energy storage charging/ discharging. However, the flexible demand shifting ability of electric vehicles is not considered in these building side controls. For instance, the electric vehicle charging will usually start once they are plugged into charging stations. But, in such charging period the renewable generation may be insufficient to cover the EV charging load, leading to grid electricity imports. Consequently, the building-cluster-level performance is not optimised. Therefore, this study proposes a coordinated control of building prosumers for improving the cluster-level performance, by making use of energy sharing and storage capability of electricity batteries in both buildings and EVs. An EV charging/discharging model is first developed. Then, based on the predicted future 24h electricity demand and renewable generation data, the coordinated control first considers the whole building cluster as one integrated building and optimises its operation as well as the EV charging/discharging using genetic algorithm. Next, the operation of individual buildings in the future 24h is coordinated using nonlinear programming. For validation, the developed control has been tested on a real building cluster in Ludvika, Sweden. The study results show that the developed control can increase the cluster-level daily renewable self-consumption rate by 19% and meanwhile reduce the daily electricity bills by 36% compared with the conventional controls.

Yan Wang, Dennis Kubiczek, Felix Horlamus et al.

Abstract Lignocellulosic biomass is the most abundant bio‐resource on earth, mainly composed of D‐glucose, D‐xylose and L‐arabinose. It is widely considered to be a promising alternative feedstock for biotechnological processes. Here we evaluated its potential to be the carbon source for growth of broadly distributed and well‐established Escherichia coli laboratory and protein expression strains as well as a classic probiotic E. coli strain. E. coli DH5α, E. coli K12‐MG1655, E. coli K12‐W3110, E. coli BL21(DE3) and E. coli Nissle 1917 were cultivated in mineral media containing single lignocellulosic sugar components. Sugar consumption in these cultures and growth parameters of the different strains were characterized. enhanced green fluorescent protein (eGFP) was chosen as a first easy to measure and prominent model recombinant target protein to demonstrate lignocellulose‐dependent recombinant protein production in E. coli. To open new production routes for high value food proteins based on lignocellulose, structural genes encoding bovine αS1‐casein and human αS1‐casein were synthesized, cloned and then expressed in an E. coli T7 expression system in different media based on single sugars and a synthetic wheat straw mixture. Successful recombinant production of both bovine and human αS1‐caseins in E. coli under these experimental conditions was demonstrated and quantified by densitometric analysis after protein separation in polyacrylamide gels. Finally, efficient casein production in E. coli based on a real hydrolysate obtained by steam explosion of wheat straw lignocellulose in a bioreactor‐based batch production process was successfully demonstrated. We believe that this proof‐of‐concept presented here is a promising starting point to open new routes for the production of food or feed proteins with high nutritional and economic value. As such, a valorization of bulk residual biomass like lignocellulose is envisioned as a key support of a growing and truly sustainable bioeconomy.

Yanmei Liu, Shaolin Chen, Moritz vonCossel et al.

Abstract With a large marginal land area, the Loess Plateau in China holds great potential for biomass production and environmental improvement. Identifying suitable locations for biomass production on marginal land is important for decision‐makers from the viewpoint of land‐use planning. However, there is limited information on the suitability of marginal land within the Loess Plateau for biomass production. Therefore, this study aims to evaluate the suitability of the promising perennial energy crop switchgrass (Panicum virgatum L.) on marginal land across the Loess Plateau. A fuzzy logical model was developed and validated based on field trials on the Loess Plateau and applied to the marginal land of this region, owing to its ability of dealing with the continuous nature of soil, landscape variations, and uncertainties of the input data. This study identified that approximately 12.8–20.8 Mha of the Loess Plateau as available marginal land, of which 2.8–4.7 Mha is theoretically suitable for switchgrass cultivation. These parts of the total marginal land are mainly distributed in northeast and southwest of the Loess Plateau. The potential yield of switchgrass ranges between 44 and 77 Tg. This study showed that switchgrass can grow on a large proportion of the marginal land of the Loess Plateau and therefore offers great potential for biomass provision. The spatial suitability maps produced in this study provide information to farmers and policymakers to enable a more sustainable development of biomass production on the Loess Plateau. In addition, the fuzzy‐theory‐based model developed in this study provided a good framework for evaluating the suitability of marginal land.

Lukáš Tichý, Zbyněk Dubský, Jan Mazač

The aim of this article is to apply the concept of external actorness to an analysis of EU energy relations towards Egypt in 1995–2020, with an emphasis on the related potential for strengthening energy security. The external actorness of the EU in its energy relations is based on a set of predefined criteria of a modified concept: (1) the consistency and specificity of the external energy policy and its goals and interests; (2) the diplomatic apparatus and policy tools; and (3) external recognition of the EU energy actorness by third parties. The article concludes that the EU in its energy relations with Egypt promotes its goals/interests, and has a diplomatic apparatus and political tools, but it is perceived and accepted only as a partial energy actor.