Applied Energy最新文献

Energy-system optimization for hydrogen-based green steel production from medium-grade iron ore 中品位铁矿石氢基绿色炼钢的能源系统优化

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-20 DOI: 10.1016/j.apenergy.2026.127563

Marcel Stolte , Ali Bourig , Francesco Demetrio Minuto , Andrea Lanzini

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.

钢铁行业占全球温室气体排放量的8%，是工业脱碳的核心。大多数绿色钢的评估都集中在电弧炉的氢直接还原上，这需要高品位的矿石。然而，包括世界最大出口国澳大利亚在内的主要铁矿石生产国，主要供应的是无法通过这条路线进行有效加工的中等品位矿石。本研究通过评估中品位矿石是否能够支持有竞争力的绿色钢铁生产来解决这一差距。开发了可再生资源可变条件下的供氢、储氢、连续炼钢一体化优化框架，应用于针对中品位矿石的氢直接还原铁电熔炼炉-碱性氧炉路线。结果表明，在适度电网供应的支持下，风能和太阳能的优化组合可以降低生产成本。与传统高炉钢相比，目前约400美元的成本差距可以通过技术学习、类似于欧盟排放交易体系的碳价格以及随着时间的推移而下降的有针对性的支持相结合来缩小。每小时的时间匹配和氢排放强度的限制对电解槽的利用、可再生能源的过度建设和钢铁的平准化成本有很大的影响。一个接近3 kg CO₂kg−1H₂的适度排放阈值，结合每小时匹配，可以捕获最可实现的减排，同时避免与更严格的限制相关的显著成本上升。这些发现阐明了矿石质量、可再生资源概况和氢系统约束如何相互作用，以确定绿色钢铁生产的可行性，并为规划大规模氢基工业系统的地区提供了指导。

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引用次数: 0

Explainable Singular Spectrum Analysis deep learning model for half-hourly electricity price prediction 半小时电价预测的可解释奇异谱分析深度学习模型

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-20 DOI: 10.1016/j.apenergy.2026.127556

Sujan Ghimire , Ravinesh C. Deo , Hangyue Liu , Konstantin Hopf , Thong Nguyen-Huy , David Casillas-Pérez , Jorge Pérez-Aracil , Sancho Salcedo-Sanz

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

\approx 2.787

(QLD) and

\approx 2.117

(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.

电价预测对于电力行业的高效运行和成本管理至关重要。然而，EP系列固有的复杂性和非线性给精确的能量管理带来了挑战。本文介绍了一种将奇异谱分析（SSA）与时间序列神经基展开分析（NBEATS）相结合的半小时EP预测系统。采用贝叶斯优化对NBEATS的超参数进行优化。SSA将EP序列分解为子序列，使NBEATS能够单独预测每个子序列。2016年1月至2022年10月，来自澳大利亚新南威尔士州（NSW）和昆士兰州（QLD）的真实数据验证了该模型的有效性。使用确定性度量（均方根误差、平均绝对误差、对称平均绝对百分比误差）的评估表明，SSA-NBEATS在预测精度、精度和稳定性方面优于其他基于分解的模型。此外，整合这些指标的全球绩效指标（GPI）将所提出的SSA-NBEATS模型定位在前列，GPI为≈2.787 （QLD）和≈2.117 (NSW)，超过基准模型。包括Diebold-Mariano和Giacomini-White在内的统计测试证实，SSA-NBEATS预测EP的准确性优于基准模型。此外，可解释的人工智能（xAI）技术- shapley加性解释（SHAP）和局部可解释模型不可知解释(LIME) -被用来有效地解释NBEATS模型预测。

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引用次数: 0

Resilient microgrid planning for socially vulnerable communities 针对社会弱势群体的弹性微电网规划

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-13 DOI: 10.1016/j.apenergy.2026.127434

Farzane Ezzati , Zhijie Sasha Dong , Gino Lim , Junfeng Jiao

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.

气候变化增加了自然灾害的频率和严重程度，扰乱了电力系统，对社会弱势群体造成了不成比例的影响。虽然最近的研究探索了微电网部署的技术和社会经济方面，但在设计微电网方面的工作仍然有限，特别是在灾害期间提高社会弱势社区的能源恢复能力。为了解决这一差距，本研究提出了一个以投资和弹性为导向的框架，用于规划和运营可再生能源集成住宅社区微电网（RCMG）。在负荷需求、可再生能源发电和停电时间不确定的情况下，建立了一种两阶段随机规划模型来优化长期投资、运行和扩容。该框架还包括一个通过电费折扣激励家庭的减负荷需求响应计划（DRP）。德克萨斯州三个社区的案例研究结果表明，将容量扩展与DRP相结合可以将系统总成本降低16%，同时将弹性提高60%以上，并将家庭账单节省13%。研究结果强调了DRP设计、扩建时机和差异化电价在平衡融资可及性和弹性方面的关键作用。可扩展性分析表明，虽然扩建成本随需求而变化，但投资反应受到社会脆弱性的影响，因此需要积极主动、针对社区的规划和前期资金，以确保微电网的公平增长。这些见解为公用事业公司和政策制定者规划公平的、针对社区的微电网提供了实际指导，从而在日益增长的气候风险下增强能源弹性。

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引用次数: 0

Adaptive multi-stage planning of electric vehicle charging infrastructure with photovoltaic and energy storage systems: a transportation-aware optimization approach 基于光伏和储能系统的电动汽车充电基础设施自适应多阶段规划：一种交通感知优化方法

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-13 DOI: 10.1016/j.apenergy.2026.127517

PeiHua Wang , Jiaxin Yuan

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.

城市交通的电气化对于实现碳中和至关重要，但大规模的电动汽车整合对配电网络构成了重大挑战，需要协调的基础设施规划。目前的方法有四个关键的局限性：静态规划视野不能充分捕捉动态的电动汽车采用模式；用户满意度指标仍然过于简单，忽视了多维度的服务质量；交通-电力系统集成不足，框架根据电节点而不是移动动态选择位置；解决方案方法缺乏针对复杂优化场景的特定问题定制。为了解决这些差距，本研究开发了一个多阶段的协同规划框架，将电动汽车充电基础设施与光伏和储能系统集成在一起。提出了三种方法创新。首先，动态适应性规划范式将15年远景划分为三个五年阶段，客观权重从经济效率（0.50,0.25,0.25）转移到用户满意度（0.25,0.50,0.25）和环境效益（0.25,0.25,0.50）。其次，综合四分量满意度模型将电压质量、等待时间、基于交通的覆盖率和时间可用性集成到一个复合效用函数中。第三，交通流矩阵在交通和电力网络之间建立了数据驱动的耦合，直接从总交通吞吐量中得出节点重要性。在改进的IEEE 33总线系统与12节点运输网络集成上验证了框架的有效性。用户满意度在第二阶段达到峰值0.580，碳排放量在第三阶段下降到1.385 × 107 kg。累计投资328.8 × 104元，投资回收期5.0年。交通分析集中了节点6、20和31的38个充电器，展示了将交通数据有效地转化为技术上可行、经济上可行的基础设施部署策略。

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引用次数: 0

Reliability evaluation of solar pavements-integrated power system considering seasonal meteorological factors and traffic road congestion 考虑季节气象因素和交通道路拥堵的太阳能路面集成电力系统可靠性评估

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-23 DOI: 10.1016/j.apenergy.2026.127566

Wei Dai, Huan Zheng, Bochen Shi, Hui Liu

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%.

为了实现碳中和和排放峰值，交通能源一体化协调发展具有重要的现实意义。在此背景下，积极推进可再生能源在交通领域的应用，构建交通能源新体系是关键途径。太阳能路面作为一种集清洁发电与交通运输功能于一体的新兴发电技术，在加快交通运输行业低碳转型方面备受青睐。然而，SPs的快速扩张引入了由天气条件和交通流量引起的重大不确定性，这可能对城市配电系统的可靠性产生不利影响。在此，我们开发了一种新的可靠性评估模型，以综合评估电力系统的发电潜力和运行可靠性。通过对道路交通拥堵、天气变异性和sp输出特性的详细建模，对集成sp的电力系统进行了准确评估。为了准确捕捉道路拥堵和天气条件的不确定性，建立了基于马尔可夫链的多状态概率转移矩阵，模拟了sp在多种运行场景下的实际输出。案例研究使用来自中国多个城市的真实数据进行。仿真结果表明，天气和交通条件的随机性会对系统的可靠性造成较大的波动。EDNS （Expected Demand Not supply）指数显示，当SPs上的拥塞从自由流增加到严重拥塞时，可靠性改善率从9.77%下降到3.89%。在高太阳活动区，天气条件的变化导致可靠性增强在5.44% ~ 12.63%之间波动，而在低太阳活动区，这一范围下降到4.33% ~ 8.99%。

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引用次数: 0

Electro-thermal-aging modeling of Li-ion batteries with active-material loss 具有活性物质损失的锂离子电池电热老化模型

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-18 DOI: 10.1016/j.apenergy.2026.127539

Hui Pang , Xiangping Yan , Nan Jiang , Xudong Qu , Bingbing Jing , Andrew F. Burke , Jingyuan Zhao

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.

大多数锂离子电池（lib）的老化模型关注的是锂库存（LLI）的损失，而忽略了活性物质（LAM）的损失，这限制了它们捕捉长期容量衰减和热量产生的能力。为了解决这一差距，我们开发了一个耦合的电热老化（ETA）模型，该模型明确地结合了LLI和LAM，并分析了相关的发热行为。建模框架从构建仅限lili的基线模型开始。然后，通过差分电压分析（DVA）推导出定量的LAM指标，该指标与累积电荷吞吐量呈稳定的幂律关系。由于LAM参数映射的实验数据是稀疏的，因此通过物理信息增强来扩展训练数据集，并使用多层感知器-高斯过程混合回归方法来获得准确和连续的参数估计。通过实验测量和COMSOL模拟验证了完整的ETA模型，随后评估了单个发热部件在长周期循环中的演变。与基线相比，ETA模型的电压和容量预测误差分别降低了40.63%和21.96%。热分析表明，随着老化，总发热量呈非线性增加，主要由活化极化热驱动，欧姆热增加较为温和，可逆热几乎保持不变。总体而言，ETA框架加强了对多种降解途径如何影响锂离子电池电化学和热行为的理解，从而为设计更有效的电池生命周期热管理策略提供了信息。

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引用次数: 0

Attack-resilient and communication-efficient distributed secondary control of distributed energy resources in microgrids: Methods and hardware-in-the-loop validations 微电网中分布式能源的抗攻击和通信效率分布式二次控制：方法和硬件在环验证

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-18 DOI: 10.1016/j.apenergy.2026.127521

Xing Huang , Yucan Zhang , Yulin Chen , Donglian Qi , Shaohua Yang , Fushuan Wen

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.

交流微电网中分布式能源的二次控制对系统的稳定运行至关重要，需要一个安全高效的通信网络。虽然先进的信息技术使众多的DERs能够协调并增强mg的二次频率和功率性能，但它们也增加了通信负担并扩大了攻击面，使mg暴露于欺骗性网络攻击（dca）。这些攻击会破坏资源协调，甚至导致潜在的MG系统中断。为此，我们提出了一种抗攻击、通信高效的分布式二次控制（ArCeDSC）方法，以保证在dca下的安全运行，同时减少通信负担。首先，建立了基于大信号模型的MG公式，实现了系统动力学的高保真度表征。在该公式中，为在定向通信网络上运行的mg开发了一种新的分布式安全滑动面，使闭环结构能够固有地拒绝伪造信号。在此基础上，提出了一种弹性分布式控制协议，将MG系统的二次频率和功率轨迹强制到该安全表面上，从而完全消除各种dca的影响。提出了一种不依赖全局信息、不依赖连续监测的全分布式事件触发机制，显著降低了通信负担和对dca的暴露面。进一步给出了收敛性、有限时间可达性和无芝诺性的严格证明。最后，对比仿真和硬件在环（HIL）实验结果验证了该方法具有良好的通信效率和抗攻击性能。

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引用次数: 0

Scalable hydrogel smart windows with moisture retention and low-emissivity for sustainable buildings 可伸缩的水凝胶智能窗户，具有保湿性和低辐射性，适用于可持续建筑

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-17 DOI: 10.1016/j.apenergy.2026.127511

Zhenhui Hu , Yutong Tan , Kai Yao , Jiashuo Sun , Hengshan Wei , Yu Zhao , Xi Chen , Yi Long , Yongsheng Yang , Jinqing Peng , Yujie Ke

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 (ɛ_LWIR), and large-area fabrication. The hydrogel is synthesized by copolymerizing the moisturizing agent sodium pyrrolidone carboxylate (PCANa) 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 ɛ_LWIR. We produce a large-area smart window demo (40 × 45 cm²), achieving a visible transmittance (Т_lum) of 69.3%, a solar modulation (ΔТ_sol) of 60.3%, and a low ɛ_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.

热致变色水凝胶在智能窗户方面显示出前景，但面临着诸如高热发射率和快速失水等挑战。本文报道了一种可扩展的基于水凝胶的智能窗口，它同时解决了水分保持、低长波红外发射率（LWIR）和大面积制造的关键挑战。该水凝胶由保湿剂吡啶烷酮羧酸钠（PCANa）与n -异丙基丙烯酰胺（PNIPAM）共聚而成，形成了稳定的结构，相变温度降至25.7℃，与纯PNIPAM水凝胶相比，保水率提高了12%。该水凝胶进一步与氧化铟锡（ITO）层集成，以降低LWIR。我们制作了一个大面积的智能窗口演示（40 × 45 cm2），实现了69.3%的可见光透过率（Тlum）， 60.3%的太阳调制（ΔТsol）和0.32的低LWIR。据我们所知，具有这种性能和保水特性的演示在以前的报道中很少实现。演示测试证明，与基于玻璃的窗户相比，在日间照明下室内温度降低高达9.0°C。EnergyPlus的模拟进一步表明，曼谷、凤凰城和长沙的供暖、通风和空调（HVAC）年度节能分别为44.9%、46.1%和10.1%，优于传统的玻璃系统。集成设计在100个周期内保持出色的光学性能，并为实用的节能建筑应用提供了可扩展的途径。

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引用次数: 0

Capturing CO2 from waste-fired CHP plants at low marginal cost 以低边际成本从废物燃烧的热电联产工厂捕获二氧化碳

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-23 DOI: 10.1016/j.apenergy.2026.127558

Shuo Wang , Beibei Dong , Kåre Gustafsson , Eva Thorin , Qie Sun , Hailong Li

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.

从废物燃烧的热电联产（w-CHP）工厂捕获二氧化碳已经引起了越来越多的关注。然而，目前还没有一种方法可以指导水热电联产电厂的二氧化碳捕集操作达到经济可行性。为了弥补这一知识缺口，本文提出了一种基于CO2捕集边际成本（MCoC）的新方法，用于不同时间尺度的热电联产电厂的运行规划。考虑了基于小时MCoCs （OR1）和月MCoCs （OR2）的两种运行规则，并以实际的热电联产电厂为例进行了研究。结果表明，在2020年电价和碳配额价格为25欧元/吨的情况下，与没有二氧化碳捕集的参考工厂相比，在OR1和OR2下，二氧化碳捕集的整合分别减少了730万欧元和540万欧元的净收入。虽然OR2可能导致较低的收入损失，但在OR1下可以捕获更多的二氧化碳。影响二氧化碳捕集的关键因素包括电价、废物中化石燃料的比例、运输和储存成本、碳配额价格和废物价格。在OR1下，较高的电价可以使w-CHP电厂受益，而在OR1下，废物的化石份额、运输和储存成本以及废物价格的增加会减少电厂的收入。为了实现二氧化碳捕获的净收入，碳排放配额的价格必须分别超过OR1和OR2规定的58欧元/吨和49欧元/吨的门槛。

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引用次数: 0

Impact assessment of battery-electric HDVs charging loads on the transmission and distribution system in Iceland 电池-电动hcv充电负荷对冰岛输配电系统的影响评估

IF 11 1区工程技术 Q1 ENERGY & FUELS

Applied Energy

Pub Date : 2026-05-01 Epub Date: 2026-02-18 DOI: 10.1016/j.apenergy.2026.127514

Albert Alonso-Villar , Brynhildur Davíðsdóttir , Hlynur Stefánsson , Eyjólfur Ingi Ásgeirsson , Ragnar Kristjánsson

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.

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.

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.

本研究旨在调查电池电动卡车（BET）快速充电负载对冰岛输配电系统的影响，重点是北极条件下的长途货运，并确定在冰岛货运部门采用电动卡车的初始阶段，支持该国主要货运路线上的BET运营所需的潜在电网加固。为此，该研究提出了一种新颖的集成方法，结合了详细的车辆能耗模型、充电优化框架和功率流分析。车辆遥测数据用于估计电池电动拖拉机卡车的能源消耗，从而为冰岛主要货运走廊沿线快速充电站的分配提供信息。结合卡车交通流数据，这些估计值用于推导充电需求负荷，然后使用多种场景下的功率流模拟对其进行分析。研究结果表明，与2030年的情景相比，BET充电需求高度不均衡，显著重塑了区域负荷分布，南方的负荷上升到16.5%，北方的负荷上升到10.8%。潮流结果表明，到2030年，预计的一般用电量增长可能导致整个国家电网的电压不稳定，而BET充电负荷加剧了这一挑战。西峡湾是最受限制的地区，由于有限的电网容量，表现出严重的电压违规。总体而言，该分析强调了长途货运电气化的可行性，前提是有针对性地加强电网。这项研究为北极地区长途货运电气化的技术可行性提供了有价值的见解，并有助于全球对孤立和可再生能源主导的电力系统中可持续运输电气化的理解。

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引用次数: 0