Applied Energy最新文献

{"title":"Energy-system optimization for hydrogen-based green steel production from medium-grade iron ore","authors":"Marcel Stolte ,&nbsp;Ali Bourig ,&nbsp;Francesco Demetrio Minuto ,&nbsp;Andrea Lanzini","doi":"10.1016/j.apenergy.2026.127563","DOIUrl":"10.1016/j.apenergy.2026.127563","url":null,"abstract":"<div><div>The steel industry accounts for 8% of global greenhouse gas emissions and is central to industrial decarbonization. Most green-steel assessments focus on hydrogen direct reduction with electric arc furnaces, which require high-grade ores. However, major iron ore producers, including Australia, the world's largest exporter, supply predominantly medium-grade ores that cannot be processed efficiently in this route. This study addresses this gap by assessing whether medium-grade ores can support competitive green-steel production. We develop an integrated optimization framework that links hydrogen supply, storage, and continuous steelmaking under variable renewable resources, applied to the hydrogen direct reduced iron-electric smelting furnace-basic oxygen furnace route tailored to medium-grade ores. The results show that an optimised mix of wind and solar power, supported by moderate grid supply, can lower production costs. The current cost gap of roughly 400 USD t⁻¹ relative to conventional blast furnace steel can be closed through a combination of technology learning, carbon prices similar to the European Union Emissions Trading System, and targeted support that declines over time. Hourly temporal matching and limits on hydrogen-emission intensity have a strong influence on electrolyser utilisation, renewable overbuild, and the levelised cost of steel. A moderate emission threshold near 3 kg CO₂ kg⁻¹H₂, combined with hourly matching, captures most attainable abatement while avoiding the marked cost escalation associated with stricter limits. These findings clarify how ore quality, renewable-resource profiles, and hydrogen-system constraints interact to determine the feasibility of green steel production, and they offer guidance for regions planning large-scale hydrogen-based industrial systems.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127563"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable Singular Spectrum Analysis deep learning model for half-hourly electricity price prediction","authors":"Sujan Ghimire ,&nbsp;Ravinesh C. Deo ,&nbsp;Hangyue Liu ,&nbsp;Konstantin Hopf ,&nbsp;Thong Nguyen-Huy ,&nbsp;David Casillas-Pérez ,&nbsp;Jorge Pérez-Aracil ,&nbsp;Sancho Salcedo-Sanz","doi":"10.1016/j.apenergy.2026.127556","DOIUrl":"10.1016/j.apenergy.2026.127556","url":null,"abstract":"<div><div>Electricity price (EP) prediction is crucial for efficient operations and cost management in the power industry. However, the inherent complexity and nonlinearity of EP series pose challenges for accurate energy management. This study introduces an innovative prediction system for half-hourly EP, integrating Singular Spectrum Analysis (SSA) with Neural Basis Expansion Analysis for Time Series (NBEATS). Bayesian optimization is employed to optimize NBEATS’ hyperparameters. SSA decomposes the EP series into sub-series, enabling NBEATS to predict each sub-series individually. Real-world data from New South Wales (NSW) and Queensland (QLD), Australia, spanning from January 2016 to October 2022, validates the model’s effectiveness. Evaluation using deterministic metrics (Root Mean Square Error, Mean Absolute Error, Symmetric Mean Absolute Percentage Error) demonstrates that SSA-NBEATS outperforms other decomposition-based models in prediction accuracy, precision, and stability. Furthermore, the Global Performance Indicator (GPI), which integrates these metrics, positions the proposed SSA-NBEATS model at the forefront with a GPI of <span><math><mo>≈</mo><mn>2.787</mn></math></span> (QLD) and <span><math><mo>≈</mo><mn>2.117</mn></math></span> (NSW), surpassing benchmark models. Statistical tests including Diebold-Mariano and Giacomini-White confirm the superior accuracy of EP predictions by SSA-NBEATS over benchmark models. Additionally, eXplainable Artificial Intelligence (xAI) techniques—SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME)—are employed to interpret NBEATS model predictions effectively.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127556"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147385959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resilient microgrid planning for socially vulnerable communities","authors":"Farzane Ezzati ,&nbsp;Zhijie Sasha Dong ,&nbsp;Gino Lim ,&nbsp;Junfeng Jiao","doi":"10.1016/j.apenergy.2026.127434","DOIUrl":"10.1016/j.apenergy.2026.127434","url":null,"abstract":"<div><div>Climate change has increased the frequency and severity of natural disasters, disrupting power systems and disproportionately impacting socially vulnerable communities. While recent research has explored technical and socio-economic aspects of microgrid deployment, there remains limited work on designing microgrids that specifically enhance energy resilience for socially vulnerable communities during disasters. To address this gap, this study proposes an investment and resilience-oriented framework for planning and operation of renewable energy-integrated Residential Community Microgrid (RCMG). A two-stage stochastic programming model is developed to optimize long-term investment, operation, and capacity expansion under uncertainties in load demand, renewable generation, and outage duration. The framework also incorporates a load-curtailing demand response program (DRP) that incentivizes households through bill discounts. Results from case studies in three Texas communities demonstrate that integrating capacity expansion with DRP can reduce total system costs by up to 16% while improving resilience by more than 60% and increasing household bill savings by 13%. The findings highlight the critical roles of DRP design, expansion timing, and differentiated electricity pricing in balancing financial accessibility and resilience. Scalability analysis shows that while expansion costs scale with demand, investment responses are shaped by social vulnerability, highlighting the need for proactive, community-specific planning and front-loaded funding to ensure equitable microgrid growth. These insights provide practical guidance for utilities and policymakers in planning equitable, community-specific microgrids that strengthen energy resilience under growing climate risks.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127434"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive multi-stage planning of electric vehicle charging infrastructure with photovoltaic and energy storage systems: a transportation-aware optimization approach","authors":"PeiHua Wang ,&nbsp;Jiaxin Yuan","doi":"10.1016/j.apenergy.2026.127517","DOIUrl":"10.1016/j.apenergy.2026.127517","url":null,"abstract":"<div><div>The electrification of urban transportation is essential for achieving carbon neutrality, yet large-scale electric vehicle integration poses significant challenges to power distribution networks requiring coordinated infrastructure planning. Current approaches exhibit four critical limitations: static planning horizons inadequately capture dynamic electric vehicle adoption patterns; user satisfaction metrics remain simplistic, neglecting multidimensional service quality; transportation-power system integration is insufficient, with frameworks selecting locations based on electrical nodes rather than mobility dynamics; and solution methodologies lack problem-specific customization for complex optimization landscapes.To address these gaps, this research develops a multi-stage co-planning framework integrating electric vehicle charging infrastructure with photovoltaic and energy storage systems. Three methodological innovations are proposed. First, a dynamic adaptive planning paradigm divides a 15-year horizon into three five-year stages with objective weights shifting from economic efficiency (0.50, 0.25, 0.25) to user satisfaction (0.25, 0.50, 0.25) and environmental benefits (0.25, 0.25, 0.50). Second, a comprehensive four-component satisfaction model integrates voltage quality, waiting time, traffic-based coverage, and temporal availability into a composite utility function. Third, traffic flow matrices establish data-driven coupling between transportation and power networks, deriving node importance directly from aggregate traffic throughput. Validation on a modified IEEE 33-bus system integrated with a 12-node transportation network demonstrates framework effectiveness. User satisfaction peaks at 0.580 in Stage 2, while carbon emissions decrease to 1.385 × 10⁷ kg in Stage 3. Total cumulative investment reaches 328.8 × 10⁴ CNY with 5.0-year payback periods. Traffic analytics concentrate 38 chargers at each of Nodes 6, 20, and 31, demonstrating effective translation of transportation data into technically feasible, economically viable infrastructure deployment strategies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127517"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliability evaluation of solar pavements-integrated power system considering seasonal meteorological factors and traffic road congestion","authors":"Wei Dai,&nbsp;Huan Zheng,&nbsp;Bochen Shi,&nbsp;Hui Liu","doi":"10.1016/j.apenergy.2026.127566","DOIUrl":"10.1016/j.apenergy.2026.127566","url":null,"abstract":"<div><div>In pursuit of carbon neutrality and emission peak, the coordinated development of transportation-energy integration has significant practical implications. Under this context, actively promoting the application of renewable energies in the transportation sector to build a new transportation-energy system is a pivotal way. Solar pavements (SPs), as an emerging power generation technology that integrates clean electricity generation and transportation functions, are highly favored to accelerate the low-carbon transition for the transportation sector. However, the rapid expansion of SPs introduces significant uncertainties arising from weather conditions and traffic flows, which may adversely affect the reliability of urban power distribution systems. Here, we develop a novel reliability evaluation model to comprehensively assess the generation potential of SPs and the operational reliability of power systems. Road traffic congestion, weather variability, and the output characteristics of SPs are modeled in detail to accurately assess the power system with integrated SPs. To accurately capture the uncertainties of road congestion and weather conditions, a multi-state probability transition matrix based on the Markov chain is established to simulate the actual output of SPs under multiple operational scenarios. Case studies are conducted using real-world data from multiple cities in China. The simulation results indicate that the randomness of weather and traffic conditions will cause great fluctuations in the reliability of the system. The Expected Demand Not Supplied (EDNS) index reveals that as congestion on SPs increases from free-flow to heavy, reliability improvement drops from 9.77% to 3.89%. In high-solar areas, variations in weather conditions cause the reliability enhancement to fluctuate between 5.44% and 12.63%, whereas in low-solar regions this range decreases to 4.33%–8.99%.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127566"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electro-thermal-aging modeling of Li-ion batteries with active-material loss","authors":"Hui Pang ,&nbsp;Xiangping Yan ,&nbsp;Nan Jiang ,&nbsp;Xudong Qu ,&nbsp;Bingbing Jing ,&nbsp;Andrew F. Burke ,&nbsp;Jingyuan Zhao","doi":"10.1016/j.apenergy.2026.127539","DOIUrl":"10.1016/j.apenergy.2026.127539","url":null,"abstract":"<div><div>Most aging models for lithium-ion batteries (LIBs) focus on the loss of lithium inventory (LLI) while neglecting the loss of active material (LAM), which limits their ability to capture long-term capacity fade and heat generation. To address this gap, a coupled electro-thermal-aging (ETA) model is developed by explicitly incorporating both LLI and LAM, along with an analysis of the associated heat-generation behavior. The modeling framework begins with the construction of an LLI-only baseline model. A quantitative LAM indicator is then derived through differential voltage analysis (DVA), which exhibits a stable power-law relationship with cumulative charge throughput. Because experimental data for LAM parameter mapping are sparse, the training dataset is expanded through physics-informed augmentation, and a hybrid multilayer perceptron-Gaussian process regression approach is used to obtain accurate and continuous parameter estimates. The complete ETA model is validated using experimental measurements and COMSOL simulations, followed by an evaluation of the evolution of individual heat-generation components over extended cycling. Relative to the baseline, the ETA model reduces voltage and capacity prediction errors by 40.63% and 21.96%, respectively. The thermal analysis reveals a nonlinear increase in total heat generation with aging, driven predominantly by activation polarization heat, with ohmic heat increasing more moderately and reversible heat remaining nearly unchanged. Overall, the ETA framework strengthens understanding of how multiple degradation pathways influence the electrochemical and thermal behaviors of LIBs, thereby informing the design of more effective thermal-management strategies across the battery life cycle.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127539"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attack-resilient and communication-efficient distributed secondary control of distributed energy resources in microgrids: Methods and hardware-in-the-loop validations","authors":"Xing Huang ,&nbsp;Yucan Zhang ,&nbsp;Yulin Chen ,&nbsp;Donglian Qi ,&nbsp;Shaohua Yang ,&nbsp;Fushuan Wen","doi":"10.1016/j.apenergy.2026.127521","DOIUrl":"10.1016/j.apenergy.2026.127521","url":null,"abstract":"<div><div>Secondary control of distributed energy resources (DERs) in AC microgrids (MGs) is critical for system stable operation, requiring a secure and efficient communication network. Although advanced information technologies enable numerous DERs coordination and enhance secondary frequency and power performances of MGs, they also increase communication burdens and expand the attack surface, exposing MGs to deceptive cyber attacks (DCAs). These attacks can disrupt resource coordination and even lead to potential MG system outages. To this end, we propose an attack-resilient and communication-efficient distributed secondary control (ArCeDSC) method for DERs to guarantee secure operation even under DCAs while reducing communication burden. First, a formulation of MG is established based on the large-signal model to achieve high-fidelity characterization of system dynamics. Within this formulation, a novel distributed secure sliding surface is developed for MGs operating over directed communication networks, enabling the closed-loop structure to inherently reject falsified signals. On this basis, a resilient distributed control protocol is proposed to force the MG system’s secondary frequency and power trajectories onto this secure surface, thereby completely eliminating the impacts of diverse DCAs. Moreover, a fully distributed event-triggered mechanism is proposed without relying on any global information or continuous monitoring to significantly reduce the communication burden and its exposure surface to DCAs. Furthermore, rigorous proofs are presented for the convergence properties, finite-time reachability, and Zeno-free behavior. Finally, compared with existing methods, comparative simulations and Hardware-in-the-Loop (HIL) experimental results validate the superior communication-efficient and attack-resilient performance.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127521"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable hydrogel smart windows with moisture retention and low-emissivity for sustainable buildings","authors":"Zhenhui Hu ,&nbsp;Yutong Tan ,&nbsp;Kai Yao ,&nbsp;Jiashuo Sun ,&nbsp;Hengshan Wei ,&nbsp;Yu Zhao ,&nbsp;Xi Chen ,&nbsp;Yi Long ,&nbsp;Yongsheng Yang ,&nbsp;Jinqing Peng ,&nbsp;Yujie Ke","doi":"10.1016/j.apenergy.2026.127511","DOIUrl":"10.1016/j.apenergy.2026.127511","url":null,"abstract":"<div><div>Thermochromic hydrogels have shown promise for smart windows but face challenges such as high thermal emissivity and rapid water loss. This paper reports a scalable hydrogel-based smart window that simultaneously addresses the key challenges of moisture retention, low long-wave infrared emissivity (<em>ɛ</em>_LWIR), and large-area fabrication. The hydrogel is synthesized by copolymerizing the moisturizing agent sodium pyrrolidone carboxylate (PCA<img>Na) with N-isopropylacrylamide (PNIPAM), forming a stable structure that lowers the phase transition temperature to 25.7 °C and improves water retention by 12% compared to the pure PNIPAM hydrogels. This hydrogel is further integrated with an indium tin oxide (ITO) layer for reduced <em>ɛ</em>_LWIR. We produce a large-area smart window demo (40 × 45 cm²), achieving a visible transmittance (<em>Т</em>_lum) of 69.3%, a solar modulation (Δ<em>Т</em>_sol) of 60.3%, and a low <em>ɛ</em>_LWIR of 0.32. To our knowledge, the demo featured with this performance and the water retention character is rarely achieved in previous reports. The demo test proves an indoor temperature reduction of up to 9.0 °C under daytime illumination compared with glass-based window. EnergyPlus simulations further indicate annual Heating, Ventilation, and Air Conditioning (HVAC) energy savings of 44.9%, 46.1%, and 10.1% in Bangkok, Pheonix, and Changsha, respectively, outperforming conventional glazing systems. The integrated design maintains excellent optical performance over 100 cycles and provides a scalable pathway toward practical, energy-efficient building applications.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127511"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Capturing CO2 from waste-fired CHP plants at low marginal cost","authors":"Shuo Wang ,&nbsp;Beibei Dong ,&nbsp;Kåre Gustafsson ,&nbsp;Eva Thorin ,&nbsp;Qie Sun ,&nbsp;Hailong Li","doi":"10.1016/j.apenergy.2026.127558","DOIUrl":"10.1016/j.apenergy.2026.127558","url":null,"abstract":"<div><div>Capturing CO₂ from waste-fired combined heat and power (w-CHP) plants has attracted increasing attention. However, there has been no method that can guide the operation of CO₂ capture for w-CHP plants to attain economic feasibility. To bridge this knowledge gap, this paper proposes a novel method based on the marginal cost of CO₂ capture (MCoC) for the operation planning of w-CHP plants at different time scales. Two operating rules (ORs) are considered, which are based on the hourly MCoCs (OR1) and monthly MCoCs (OR2), and a real w-CHP plant is used as a case study. Results reveal that, under the electricity price of 2020 and with a carbon allowance price of 25 €/tonne, the integration of CO₂ capture decreased the net revenue by 7.3 million Euro (M€) and 5.4 M€ under OR1 and OR2, respectively, compared to the reference plant without CO₂ capture. Although OR2 could lead to a lower revenue loss, more CO₂ could be captured under OR1. Key factors affecting CO₂ capture include the electricity price, the fossil share of waste, the transport and storage cost, the price of carbon allowances, and the price of waste. Higher electricity prices can benefit the w-CHP plant under OR1, while increases in the fossil share of waste, transport and storage costs, and prices of waste decrease the plant's revenue under both ORs. To achieve net revenue from CO₂ capture, the price of carbon allowances must exceed the thresholds of 58 €/tonne and 49 €/tonne under OR1 and OR2, respectively.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127558"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact assessment of battery-electric HDVs charging loads on the transmission and distribution system in Iceland","authors":"Albert Alonso-Villar ,&nbsp;Brynhildur Davíðsdóttir ,&nbsp;Hlynur Stefánsson ,&nbsp;Eyjólfur Ingi Ásgeirsson ,&nbsp;Ragnar Kristjánsson","doi":"10.1016/j.apenergy.2026.127514","DOIUrl":"10.1016/j.apenergy.2026.127514","url":null,"abstract":"<div><div>This study aims to investigate the impact of battery-electric truck (BET) fast-charging loads on Iceland's transmission and distribution system, focusing on long-haul freight transport under Arctic conditions, and to identify potential grid reinforcements required to support BET operations along the country's primary freight routes during the initial phase of electric truck adoption in Iceland's freight transport sector.</div><div>To do so, the research presents a novel integrated approach combining a detailed vehicle energy consumption model, a charging optimisation framework, and power flow analysis. Vehicle telemetry data are used to estimate the energy consumption of battery-electric tractor-trucks, which informs the allocation of on-route fast-charging stations along Iceland's main freight corridors. Combined with truck traffic flow data, these estimates are used to derive charging demand loads, which are then analysed using power flow simulations under multiple scenarios.</div><div>The findings indicate that BET charging demand is highly uneven, significantly reshaping regional load profiles with loads rising to 16.5% in the South and 10.8% in the North compared to the 2030 scenario. The power flow results suggest that the forecasted rise in general power consumption by 2030 may lead to voltage instability across the national grid, a challenge exacerbated by BET charging loads. The Westfjords emerge as the most constrained region, exhibiting critical voltage violations due to limited grid capacity. Overall, the analysis highlights the feasibility of electrifying long-haul freight transport, subject to targeted grid reinforcements. This research provides valuable insights into the technical feasibility of electrifying long-haul freight in Arctic regions and contributes to the global understanding of sustainable transport electrification in isolated and renewable-energy-dominated power systems.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"410 ","pages":"Article 127514"},"PeriodicalIF":11.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147386305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}