Advances in Applied Energy最新文献_第2页

Enhancing the feasibility of direct air capture by utilizing environmental variability 利用环境变异性提高直接空气捕获的可行性

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-30 DOI: 10.1016/j.adapen.2025.100253

Kuihua Wang , Lijun Zhu , Junye Wu , Tianshu Ge

A primary challenge impeding the large-scale deployment of direct air capture (DAC) is its high energy consumption, mainly associated with external input to drive process parameter swings (such as temperature, humidity, and CO₂ concentration). Environmental parameter exhibits strong spatiotemporal variability, significantly impacting the performance of DAC. By adapting DAC operation with environmental variability, potential energy can be effectively extracted from air, thus lowering the energy demand. Diurnal fluctuations can be leveraged for passive desorption, while intense wind facilitates the passive adsorption, Seasonal and long-term environmental changes necessitate adaptive scheduling and operational optimization to maintain performance. Geographical disparities in climate act as natural energy reservoirs, offering opportunities for region-specific deployment strategies. Particularly, high ambient temperatures enable efficient integration of air-source heat pumps; cold climates suppress water co-adsorption and provide effective condensation; humid regions employ water-source heat pump to recovery excessive condensation heat efficiently; and arid regions, with low humidity, minimize water desorption requirements. Future research should prioritize the practical experimental testing, adaptive control and optimization algorithms, alongside establishing quantitative assessment frameworks to guide climate-specific deployment.

阻碍直接空气捕获（DAC）大规模部署的主要挑战是其高能耗，主要与驱动工艺参数波动（如温度、湿度和二氧化碳浓度）的外部输入有关。环境参数表现出强烈的时空变异性，显著影响DAC的性能。通过使DAC操作适应环境的可变性，可以有效地从空气中提取势能，从而降低能源需求。可以利用日波动进行被动解吸，而强风促进被动吸附，季节性和长期的环境变化需要自适应调度和操作优化来保持性能。气候的地理差异是天然的能源储藏库，为特定区域的部署战略提供了机会。特别是，高环境温度使空气源热泵能够有效地集成；寒冷的气候抑制水的共吸附，提供有效的冷凝；潮湿地区采用水源热泵高效回收过多冷凝热；而干旱地区，湿度低，最大限度地减少水的解吸需求。未来的研究应优先考虑实际的实验测试、自适应控制和优化算法，并建立定量评估框架，以指导针对气候的部署。

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引用次数: 0

Assessing the techno-economic impact of district heating on electrical distribution grid reinforcements 评估集中供热对配电网加固的技术经济影响

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-29 DOI: 10.1016/j.adapen.2025.100251

Jerry Lambert , Hermann Kraus , Markus Doepfert , Miaomiao He , David Gschossmann , Amedeo Ceruti , Isabell Nemeth , Oliver Brückl , Thomas Hamacher , Hartmut Spliethoff

Enhanced sector coupling across electricity, mobility, and heating sectors leads to higher efforts for distribution grid upgrades. Based on a case study, this paper evaluates the role of district heating networks in reducing electrical distribution grid reinforcements and compares their economic viability against a building-specific heat supply using heat pumps. A detailed energy system model is used to analyze two building energy renovation scenarios: a business-as-usual scenario with a 1 % annual renovation rate and an ambitious scenario with a rate of 2 %. Using a two-step optimization, the impact of different district heating network penetration levels on the distribution grid is evaluated, followed by an ex-post analysis to incorporate a simultaneity factor into district heating networks. Overall, district heating networks can reduce distribution grid reinforcements, but the associated savings alone do not justify their construction, particularly in the ambitious renovation scenario. In the business-as-usual scenario, a district heating network can reduce reinforcement costs by up to 71 %. However, in the ambitious scenario, grid reinforcements are already reduced due to lower heat peak demand, and the maximal reinforcement cost savings only amount to 35 %. Compared economically, district heating networks are cost-competitive with building-specific heating only in the business-as-usual scenario, up to a heat supply share of 70 % and in the ambitious scenario, up to 40 %. In both scenarios, a district heating network can be a robust solution to lower macroeconomic costs for a carbon-neutral heat supply.

电力、交通和供热部门之间的部门耦合增强，导致配电网升级的力度加大。基于一个案例研究，本文评估了区域供热网络在减少配电网加固方面的作用，并比较了它们与使用热泵的建筑特定供热的经济可行性。一个详细的能源系统模型被用来分析两种建筑能源改造方案：一种是常规方案，年翻新率为1%，另一种是雄心勃勃的方案，年翻新率为2%。采用两步优化，评估了不同区域供热网络渗透水平对配电网的影响，然后进行了事后分析，将同步因素纳入区域供热网络。总的来说，区域供热网络可以减少配电网的加固，但相关的节省本身并不能证明其建设的合理性，特别是在雄心勃勃的改造方案中。在一切照旧的情况下，区域供热网络可以减少高达71%的加固成本。然而，在雄心勃勃的情况下，由于较低的热峰值需求，网格加固已经减少，并且最大加固成本节约仅达35%。与经济相比，区域供热网络只有在一切照旧的情况下才具有成本竞争力，供热份额高达70%，而在雄心勃勃的情况下，则高达40%。在这两种情况下，区域供热网络都可以成为降低碳中性供热宏观经济成本的有力解决方案。

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引用次数: 0

Variability of technology learning rates 技术学习率的可变性

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-28 DOI: 10.1016/j.adapen.2025.100252

Angelo Carlino , Alicia Wongel , Lei Duan , Edgar Virgüez , Steven J. Davis , Morgan R. Edwards , Ken Caldeira

Climate and energy policy analysts and researchers often forecast the cost of low-carbon energy technologies using Wright’s model of technological innovation. The learning rate, i.e., the percentage cost reduction per doubling of cumulative production, is assumed constant in this model. Here, we analyze the relationship between cost and scale of production for 87 technologies in the Performance Curve Database spanning multiple sectors. We find that stepwise changes in learning rates provide a better fit for 58 of these technologies and produce forecasts with equal or significantly lower errors compared to constant learning rates for 36 and 30 technologies, respectively. While costs generally decrease with increasing production, past learning rates are not good predictors of future learning rates. We show that these results affect technological change projections in the short and long term, focusing on three key mitigation technologies: solar photovoltaics, wind power, and lithium-ion batteries. We suggest that investment in early-stage technologies nearing cost-competitiveness, combined with techno-economic analysis and decision-making under uncertainty methods, can help mitigate the impact of uncertainty in projections of future technology cost.

气候和能源政策分析师和研究人员经常使用赖特的技术创新模型来预测低碳能源技术的成本。在这个模型中，学习率，即每增加一倍的累积产量所降低的成本百分比，被假设为常数。在此，我们分析了跨越多个行业的87种技术的成本与生产规模之间的关系。我们发现，与36种和30种技术的恒定学习率相比，学习率的逐步变化为其中58种技术提供了更好的拟合，并产生了误差相等或显着更低的预测。虽然成本通常随着产量的增加而降低，但过去的学习率并不能很好地预测未来的学习率。我们表明，这些结果会影响短期和长期的技术变化预测，重点关注三种关键的缓解技术：太阳能光伏发电、风力发电和锂离子电池。我们认为，投资于接近成本竞争力的早期技术，结合不确定性方法下的技术经济分析和决策，可以帮助减轻未来技术成本预测中不确定性的影响。

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引用次数: 0

Evaluating grid stress and reliability in future electricity grids across a range of demand, generation mix, and weather trends 在各种需求、发电组合和天气趋势下评估未来电网的压力和可靠性

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-19 DOI: 10.1016/j.adapen.2025.100249

Kerem Ziya Akdemir , Kendall Mongird , Cameron Bracken , Casey D. Burleyson , Jordan D. Kern , Konstantinos Oikonomou , Travis B. Thurber , Chris R. Vernon , Nathalie Voisin , Mengqi Zhao , Jennie S. Rice

The reliability of power grids in the future will depend on how system planners account for the integration of new technologies, extreme weather events, and uncertainties in demand growth from increased electrification and data centers. This study introduces an open-source, multisectoral, multiscale modeling framework that projects grid stress and reliability trends between 2020 and 2055 in the Western Interconnection of the United States. The framework integrates global to national energy-water-land dynamics with power plant siting and hourly grid operations modeling. We analyze future wholesale electricity price shocks and unserved energy events across eight scenarios spanning a range of population growth and economic change, generation mixes, and weather conditions. Our results show future grids with high percentage of non-renewable generation and strong economic growth are characterized by higher reliability and lower wholesale electricity prices than lower growth scenarios because of larger reliance on dispatchable generators and lower fossil fuel extraction costs. Scenarios with high percentage of renewable resources have lower median but more volatile wholesale electricity prices as well as more frequent and severe unserved energy events compared to scenarios relying more on dispatchable generators. These events occur because higher proportion of solar and wind energy causes net demand curves to deepen during midday (duck curves get progressively severe), exacerbating the challenge of meeting demand during summer evening peaks. This study suggests that robust and co-optimized transmission and energy storage planning could help maintain low wholesale electricity prices and high reliability levels in future electricity grids across uncertainties in generation mixes.

未来电网的可靠性将取决于系统规划者如何考虑新技术的集成、极端天气事件以及电气化和数据中心增加带来的需求增长的不确定性。本研究介绍了一个开源、多部门、多尺度的建模框架，该框架预测了2020年至2055年美国西部电网的电网应力和可靠性趋势。该框架将全球到国家的能源-水-土地动态与发电厂选址和每小时电网运行建模相结合。我们在人口增长、经济变化、发电组合和天气条件等八种情况下分析了未来批发电价冲击和未服务的能源事件。我们的研究结果表明，与低增长情景相比，具有高比例不可再生发电和强劲经济增长的未来电网具有更高的可靠性和更低的批发电价，因为对可调度发电机的依赖程度更高，化石燃料开采成本更低。与更多依赖可调度发电机的情景相比，可再生资源比例较高的情景电价中位数较低，但批发电价波动更大，能源供应不足的事件也更频繁、更严重。这些事件的发生是因为太阳能和风能的较高比例导致净需求曲线在中午加深（鸭曲线逐渐变得严重），加剧了满足夏季晚间高峰需求的挑战。这项研究表明，在不确定的发电组合中，强大的、协同优化的输电和储能规划可以帮助在未来电网中保持低批发电价和高可靠性水平。

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引用次数: 0

Life cycle CO2e intensity of power-to-liquid sustainable aviation fuel scenarios and specific use cases 动力-液体可持续航空燃料方案和具体用例的生命周期二氧化碳当量强度

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-05 DOI: 10.1016/j.adapen.2025.100248

Aron Bell , Liam Anthony Mannion , Mark Kelly , Robert Parker , Mohammad Reza Ghaani , Stephen Dooley

The life cycle carbon dioxide equivalent (CO₂e) intensity of Power-to-Liquid (PtL) sustainable aviation fuel (SAF) scenarios in Spain are evaluated using a specific, granular, and transparent modelling approach. Post combustion CO₂ capture and direct air CO₂ capture are considered, in addition to grid and renewable electricity sources. The mass and energy requirements of the PtL system are determined from a mass and energy conserved reaction mechanism and a comprehensive literature review. The SAF yield is constrained by its molecular composition, formulated to meet the physical property specifications for Fischer-Tropsch synthetic paraffinic kerosene (FT-SPK) in ASTM D7566 Annex 1. The results of the life cycle assessment (LCA) show large ranges in CO₂e intensity of PtL SAF scenarios, from 11 to 101 gCO₂e/MJ. The electricity emission factors at which the CO₂e intensity of PtL SAFs meet the 70% reduction required under the ReFuelEU Aviation legislation are 112 – 168 gCO₂e/kWh for direct air capture and post combustion capture of biogenic CO₂. As the average EU grid is approximately 300 gCO₂e/kWh, the use of renewable electricity (onsite or power purchase agreement) is therefore essential to achieve the 70% reduction. The carbon intensity of the Madrid to Dublin commercial flight route is analysed, per revenue-passenger-kilometre (RPK), as a specific use case with actual data of Ryanair Boeing 737-800 and 737 MAX 8 aircraft. Compared to the Science Based Targets 1.5°C limit of 3.3 gCO₂/RPK, it is shown that sustainable aviation is challenging using PtL SAF, with a best case of 9 gCO₂/RPK.

采用一种具体的、颗粒状的、透明的建模方法，对西班牙可持续航空燃料（SAF）方案的生命周期二氧化碳当量（CO2e）强度进行了评估。除了电网和可再生电力来源外，还考虑了燃烧后二氧化碳捕获和直接空气二氧化碳捕获。PtL系统的质量和能量需求是根据质量和能量守恒的反应机理和全面的文献综述确定的。SAF产率受其分子组成的限制，其配方符合ASTM D7566附件1中费托合成石蜡煤油（FT-SPK）的物理性能规范。生命周期评价（LCA）的结果表明，PtL - SAF情景的CO2e强度变化幅度较大，在11 ~ 101 gCO2e/MJ之间。在直接空气捕获和燃烧后捕获生物源二氧化碳的情况下，PtL saf的二氧化碳当量强度达到燃料燃料航空立法要求的70%的电力排放因子为112 - 168 gCO2e/kWh。由于欧盟电网的平均排放量约为300克二氧化碳当量/千瓦时，因此使用可再生电力（现场或电力购买协议）对于实现70%的减排至关重要。以瑞安航空波音737-800和737 MAX 8飞机的实际数据为例，分析了马德里至都柏林商业航线的碳强度，每收入乘客公里（RPK）。与基于科学的1.5°C目标3.3 gCO2/RPK相比，使用PtL SAF的可持续航空具有挑战性，最佳情况下为9 gCO2/RPK。

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引用次数: 0

Advanced fault diagnosis in batteries: Insights into fault mechanisms, sensor fusion, and artificial intelligence 电池的高级故障诊断：故障机制、传感器融合和人工智能

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-10-03 DOI: 10.1016/j.adapen.2025.100247

Kailong Liu , Shiwen Zhao , Yu Wang , Kang Li , Jiayue Wang , Yaojie Sun , Qiuwei Wu , Qiao Peng

With the increasing demand for sustainable and clean energy, lithium-ion batteries have emerged as one of the most essential energy storage technologies. However, safety concerns have become a major bottleneck, significantly constraining their widespread deployment. This highlights the critical need for efficient fault diagnosis to ensure the safe and reliable operation of battery systems. In recent years, artificial intelligence (AI) techniques, in combination with advanced sensing technologies, have attracted growing attention for battery fault diagnosis and prognosis. Nevertheless, their full potential and broad applicability remain underexplored. This review provides a systematic analysis of the integration of AI methodologies with advanced sensors, emphasizing their capabilities for accurate fault detection and prediction, while also identifying key challenges and future research directions in this evolving field. The study begins by outlining common battery fault types and their underlying mechanisms, offering a foundational understanding of the associated complexities. It then introduces state-of-the-art AI techniques applied in fault diagnosis. Then, recent advances in combining AI with advanced sensing technologies for battery diagnostics are examined. Finally, the limitations of current approaches are discussed, and promising directions are proposed to facilitate the development of intelligent, scalable, and robust fault diagnosis frameworks for lithium-ion battery systems.

随着人们对可持续和清洁能源的需求日益增长，锂离子电池已成为最重要的储能技术之一。然而，安全问题已经成为主要的瓶颈，极大地限制了它们的广泛部署。因此，高效的故障诊断是保证电池系统安全可靠运行的关键。近年来，人工智能技术与先进的传感技术相结合，在电池故障诊断与预测方面受到越来越多的关注。然而，它们的全部潜力和广泛适用性仍未得到充分开发。本文对人工智能方法与先进传感器的集成进行了系统分析，强调了其准确故障检测和预测的能力，同时也确定了这一不断发展的领域的关键挑战和未来研究方向。该研究首先概述了常见的电池故障类型及其潜在机制，为相关复杂性提供了基本的理解。然后介绍了应用于故障诊断的最先进的人工智能技术。然后，研究了将人工智能与先进传感技术相结合用于电池诊断的最新进展。最后，讨论了当前方法的局限性，并提出了有希望的方向，以促进智能，可扩展和健壮的锂离子电池系统故障诊断框架的发展。

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引用次数: 0

Prediction-based control of energy storage systems using dynamic accuracy weighting 基于动态精度加权的储能系统预测控制

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-09-29 DOI: 10.1016/j.adapen.2025.100246

Xiao Wang , Xue Liu , Xuyuan Kang , Fu Xiao , Da Yan

Integrating domain knowledge into artificial intelligence models is increasingly recognized as essential for improving energy storage system control based on load predictions. Commonly used accuracy metrics for load prediction models, such as mean absolute percentage error, coefficient of variation of mean absolute error, and coefficient of variation of root mean squared error, are not monotonically correlated with final control performance; in other words, the model with the highest prediction accuracy does not necessarily yield optimal control outcomes. This study introduces a dynamically weighted error metric, which incorporates the attributes of energy storage systems and the temporal dynamics of prediction-based control by leveraging domain knowledge from heating, ventilation, and air conditioning systems. The proposed dynamically weighted error metric enhanced the selection of load prediction models, and these models reduced the operating cost of six energy storage systems by up to 6.5 % compared to those using traditional prediction accuracy metrics. The scalability of dynamically weighted error metric was further validated across 10 energy storage capacities and 18 Time-of-Use tariffs in the six building cases, achieving 93.9 %–97.2 % of the ideal cost reductions and outperforming traditional metrics (86.4 %–95.4 %). The applicability of dynamically weighted error metric to common energy storage systems is discussed and confirmed. Additionally, a web-based tool was developed to facilitate dynamically weighted error calculation in practical applications. This study demonstrates that incorporating domain knowledge through dynamic accuracy weighting evidently enhances the whole-process performance of artificial intelligence in energy storage system control.

将领域知识集成到人工智能模型中，对于改善基于负荷预测的储能系统控制至关重要。负荷预测模型常用的精度指标，如平均绝对百分比误差、平均绝对误差变异系数和均方根误差变异系数，与最终控制性能不是单调相关的；换句话说，具有最高预测精度的模型并不一定产生最优的控制结果。本研究引入了一个动态加权误差度量，该度量通过利用供热、通风和空调系统的领域知识，结合了储能系统的属性和基于预测的控制的时间动态。提出的动态加权误差度量增强了负荷预测模型的选择，与使用传统预测精度度量相比，这些模型可将6个储能系统的运行成本降低6.5%。动态加权误差指标的可扩展性在6个建筑案例的10个储能容量和18个使用时间关税中得到进一步验证，实现了93.9% - 97.2%的理想成本降低，优于传统指标（86.4% - 95.4%）。讨论并验证了动态加权误差度量在普通储能系统中的适用性。此外，还开发了一个基于web的工具，以便在实际应用中进行动态加权误差计算。研究表明，通过动态精度加权方法引入领域知识，可以明显提高人工智能在储能系统控制中的全过程性能。

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引用次数: 0

Price formation and intersectoral distributional effects in a fully decarbonised European electricity market 完全脱碳的欧洲电力市场中的价格形成和部门间分配效应

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-09-25 DOI: 10.1016/j.adapen.2025.100245

Silke Johanndeiter , Niina Helistö , Juha Kiviluoma , Valentin Bertsch

Future power supply will be dominated by solar and wind energy with near zero variable costs. Hence, wholesale market prices could frequently drop near zero. We use a sector-coupled power system model to optimise scenarios of a fully decarbonised European electricity market with a high penetration of variable renewables. Resulting electricity prices exceed near zero levels throughout most hours of the year as they are predominantly determined by the opportunity costs of cross-sectoral demand, particularly electrolysers. Consequently, even in markets with a high penetration of variable renewables, electricity prices continue to be driven by fuel costs, as they determine the opportunity costs of a price-setting demand. We find market actors in different sectors to be heterogeneously exposed to associated price risks. Price-responsive electricity demand can mitigate cost increases, while investors in variable renewables and inflexible electricity consumers are similarly exposed to revenue and cost risks. Thus, they could mutually benefit from risk-mitigating instruments. Conversely, our results indicate that hydrogen producers and consumers do not share such a common interest as hydrogen consumers’ final energy consumption costs vary more across scenarios and countries than electrolysers’ profits due to their role as price-setters.

未来的电力供应将以太阳能和风能为主，其可变成本接近于零。因此，批发市场价格可能经常降至接近零的水平。我们使用一个部门耦合电力系统模型来优化完全脱碳的欧洲电力市场的情景，其中可变可再生能源的渗透率很高。因此，在一年中的大部分时间里，电价都超过接近零的水平，因为它们主要取决于跨部门需求的机会成本，特别是电解槽。因此，即使在可变可再生能源渗透率较高的市场，电价也继续受到燃料成本的驱动，因为燃料成本决定了定价需求的机会成本。我们发现，不同行业的市场参与者面临的相关价格风险是不同的。价格敏感型电力需求可以缓解成本上涨，而可变可再生能源的投资者和不灵活的电力消费者同样面临收入和成本风险。因此，它们可以从降低风险的工具中相互受益。相反，我们的研究结果表明，氢气生产商和消费者并没有共同的利益，因为氢气消费者的最终能源消耗成本在不同的情景和国家之间的差异比电解槽的利润更大，因为它们是价格制定者。

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引用次数: 0

Reaching carbon neutrality in China: Temporal and subnational limitations of renewable energy scale-up 中国实现碳中和：可再生能源规模扩大的时间和地方限制

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-09-23 DOI: 10.1016/j.adapen.2025.100238

Zhenhua Zhang , Ziheng Zhu , Jessica A. Gordon , Xi Lu , Da Zhang , Michael R. Davidson

Acute temporal impacts and subnational limitations can hinder a country’s decarbonization pathway, despite national planning efforts. China, as the world’s largest greenhouse gas (GHG) emitter, has announced an ambitious climate policy goal of achieving carbon neutrality by 2060, which will require an unprecedented scale-up of low-carbon energy technologies. China’s variable renewable energy (VRE) deployment is historically imbalanced with large geographic concentrations driven by resource endowment and institutional heterogeneities. If continued, this pattern can run into deployment limits and exacerbate challenges associated with socio-economic benefits distribution, threatening the ability to timely integrate VRE. We develop a capacity expansion model with grid operational detail and high spatial resolution to examine decadal pathways to carbon neutrality by 2060 considering localized and temporal impacts. Over these four decades, we find that all regions will increase deployment rates of renewable energy, first driven by the use of high-quality resources, and later by coal retirement and electricity demand growth. The share of provinces with high deployment pressure, where deployment requirements exceed historical rates, increases from around 45% to 100% by the final decade. If carbon capture and storage (CCS) is not available, maximum annual average deployment rates will increase by 33% and occur a decade earlier. A more stringent 1.5 °C emission target leads to more acute temporal and spatial deployment pressures in the first decade, with VRE concentrated in regions with high-quality resources and demand centers and a doubling of new transmission capacity in the first decade. Effective national and subnational policy support is necessary to coordinate VRE deployment and facilitate transitions in impacted regions.

尽管做出了国家规划努力，但严重的时间影响和地方限制可能会阻碍一个国家的脱碳之路。作为世界上最大的温室气体（GHG）排放国，中国宣布了一项雄心勃勃的气候政策目标，即到2060年实现碳中和，这将需要前所未有地扩大低碳能源技术的规模。中国的可变可再生能源（VRE）部署在历史上是不平衡的，受资源禀赋和制度异质性驱动的大地理集中度。如果持续下去，这种模式可能会遇到部署限制，并加剧与社会经济效益分配相关的挑战，从而威胁到及时整合VRE的能力。我们开发了一个具有网格运行细节和高空间分辨率的容量扩展模型，以考虑局部和时间影响，研究到2060年实现碳中和的年代际路径。在这40年里，我们发现所有地区都将提高可再生能源的部署率，首先是受优质资源使用的推动，然后是煤炭退役和电力需求的增长。在未来十年内，部署压力大的省份（部署需求超过历史水平）所占比例将从45%左右增加到100%。如果碳捕集与封存（CCS）无法实现，最高年平均部署率将提高33%，并提前十年实现。更严格的1.5°C排放目标会在第一个十年带来更大的时空部署压力，VRE集中在拥有优质资源和需求中心的地区，并且在第一个十年中将新增传输能力增加一倍。有效的国家和地方政策支持对于协调VRE的部署和促进受影响地区的过渡是必要的。

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引用次数: 0

Rethinking the atmospheric downward longwave radiation: A black-gray body model for accurate estimation 对大气向下长波辐射的再思考：一种精确估计的黑灰体模型

IF 13.8 Q1 ENERGY & FUELS

Advances in Applied Energy

Pub Date : 2025-09-18 DOI: 10.1016/j.adapen.2025.100244

Lanxin Li , Xianze Ao , Qiangyan Hao , Meiling Liu , Xiansheng Li , Kegui Lu , Chongwen Zou , Bin Zhao , Gang Pei

Accurately estimating atmospheric downward longwave radiation is critical for applications ranging from radiative cooling to building energy efficiency. The main challenge lies in its spectral variability, which depends strongly on sky conditions such as humidity and cloud cover. In this study, we propose a Black–Gray body atmospheric radiation model that divides the infrared spectrum into three regions, treating the atmosphere as a graybody in the 8–13 μm and a blackbody outside this band. The model integrates locally measured radiative power to dynamically capture temporal and spatial variations. Validation experiments were conducted using radiative cooling processes in three Chinese cities (Hefei, Lhasa, and Haikou) under different climates and weather conditions. The BG model consistently predicted radiative cooling power with high accuracy, with mean absolute percentage errors generally below 10 %, outperforming both the effective sky emissivity method and MODTRAN-based predictions. Furthermore, we introduce the concept of band-resolved atmospheric energy databases, analogous to solar radiation databases, and demonstrate it with a full-year case study in Hefei. This work provides a new modeling framework that enhances precision and enables broader applications in energy systems, climate studies, and environmental design.

准确估算大气向下长波辐射对于辐射冷却和建筑节能等应用至关重要。主要的挑战在于它的光谱变异性，这在很大程度上取决于天空条件，如湿度和云层。在本研究中，我们提出了一个黑-灰体大气辐射模型，该模型将红外光谱划分为3个区域，将8-13 μm波段内的大气视为灰体，将该波段外的大气视为黑体。该模型集成了本地测量的辐射功率，以动态捕获时间和空间变化。在合肥、拉萨和海口三个城市进行了不同气候和天气条件下的辐射冷却验证实验。BG模式对辐射冷却功率的预测具有较高的准确性，平均绝对百分比误差一般在10%以下，优于有效天空发射率方法和基于modtran的预测。此外，我们还引入了类似于太阳辐射数据库的波段分辨大气能量数据库的概念，并以合肥市全年为例进行了验证。这项工作提供了一种新的建模框架，可以提高精度，并在能源系统、气候研究和环境设计中得到更广泛的应用。

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引用次数: 0