Energy and Buildings最新文献_第10页

Low corrosive dual desiccant air conditioning: Antimicrobial activity, performance characteristics, and economic valuation with traditional VCRS

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115145

Juri Sonowal , P. Muthukumar , R. Anandalakshmi

Liquid desiccant dehumidification systems (LDDS) serve as an energy-efficient alternative to conventional vapor compression refrigeration (VCR) systems, providing enhanced control over both temperature and humidity levels. However, the broader implementation of LDDS is limited due to the corrosive effects of the liquid desiccants on metal components. In response, this study introduces an economical blend of potassium formate (HCOOK) and magnesium chloride (MgCl₂) designed to minimize corrosion while maintaining energy efficiency and performance. Selection of mixture ratio and solution concentration and determination of thermo-physical properties were conducted by initial lab-scale tests. Significant bactericidal effects against E. coli and S. aureus were observed. The feasibility and effectiveness of the developed solution were experimentally tested by a comparative investigation in a large-scale solar-integrated liquid desiccant dehumidification system against standard HCOOK (63.5 wt%). The cyclic performance of the novel desiccant solution was examined under varying operational conditions for tropical climates. Results demonstrated that the corrosion levels of the new mixture are comparable to those observed with a standard 63.5 wt% HCOOK solution, while the dehumidification efficiency showed significant improvements, with moisture removal and effectiveness enhanced by 8.7–14.3 % and 5.8–15.2 %, respectively. Significant regeneration occurred between 45 °C and 55 °C. Regeneration efficiency improved by a maximum of 12.5 % relative to the standard HCOOK solution. Notably, the deployment of a solar-assisted regeneration system led to energy cost reductions by 22.8 % compared to traditional VCR systems, achieving a return on investment within 1.8 years.

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引用次数: 0

Dual-grating smart window with vertically distributed transmittance to optimize indoor daylight distribution and solar heat gain

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115189

Rustam Zakirullin

Predicting year-round daylight and solar heat gain using building simulation software is an effective approach to assessing indoor visual and thermal comfort. This study proposes a method for modelling and optimizing daylight distribution and solar heat gain in a room with a dual-grating smart window having angular-selective and vertically distributed light and solar transmission. This newly developed smart technology features a dual-grating optical filter consisting of alternating transmissive and non-transmissive strips that can be sloped on window surfaces to adapt to the Sun’s trajectory and have different transmittances along the height of the vertical window for optimal indoor daylight distribution and optimal solar heat gain. The calculation methodology was validated by numerical simulation of the illuminance distribution for a conventional double-glazed window without coatings and for the same window with four types of grating coatings. The best distribution was demonstrated by two windows with an exponential increase in the absorptive strip widths along the window height from top to bottom (1) with preset minimum and maximum strip widths in the upper and lower zones of the window and (2) with a preset total area of all absorptive strips; the distribution was worse for windows (3) with an increase in the strip widths in an arithmetic progression and (4) with their uniform distribution; the worst distribution was shown by (5) conventional window.

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引用次数: 0

Measurement of urbanization and its spatiotemporal heterogenous effects on carbon emission from district heating industry in China

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115182

Weishi Zhang , Ying Xu , David G. Streets , Can Wang

With urbanization and city facility development, cities have become major contributors to carbon emissions. This study examines the influence of urbanization on carbon dioxide emissions from the district heating industry (CEDH) in cities between 2012 and 2020. By adopting a STIRPAT approach, CEDH was quantified, and urbanization levels evaluated through nighttime light (NTL) imagery. The results of Geographically Temporally Weighted Regression model reveal both temporal and spatial variations in how urbanization affects CEDH. The median coefficients are 0.41 (95 %CI: 0.15,0.63) and 0.91 (95 %CI: 0.66,0.32) in 2012 and 2020, respectively. Socioeconomic indicators including population density, per capita GDP, carbon intensity, showed significant positive impacts on CEDH. The GTWR model demonstrated the best performance among the models applied, with the percentage of explained variance reaching 91.5 %, the lowest value of AIC values (498.87), the lowest value of residual-sum-of-squares (RIS) (34.86). To accounting for the temporal and geographical heterogeneity in impacts of urbanization level on CEDH, detailed analysis on four clustered groups of cities. In cities with higher urbanization, the coal-based boilers dominate CO₂ emissions with a rising portion of CEDH attributed to the gas-based boilers, while in less urbanized cities, CHP systems and coal-based boilers contribute 94 % of the emission increase from 2012 to 2020. This study underscores the importance of city-specific clean heating policies to address the diverse impacts of urbanization, socio-economic, and meteorological factors on carbon mitigation.

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引用次数: 0

Deep learning based on image analysis for refrigerant charging and leakage detection in building heat pump 基于图像分析的深度学习建筑热泵制冷剂充注与泄漏检测

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115157

Yanfeng Zhao, Zhao Yang, Zhaoning Hou, Shuping Zhang, Yansong Hu, Yong Zhang

In heat pump systems, refrigerant leakage and charging faults are the common issues. Diagnosing refrigerant leakage and charging faults of the heat pump systems are crucial for reducing system energy consumption and maintaining stable high-efficiency operation. With the iteration of computing technology, data-driven approaches play an important role in fault detection and diagnosis. This research introduces a novel algorithm that transforms one-dimensional data into image format using Gramian Angular Field (GAF) and optimizes hyperparameters through Triangular Topology Aggregation Optimization (TTAO) within a Parallel Convolutional Neural Network (PCNN). Additionally, the approach integrates a Multi-head Self-Attention Mechanism (MSA) and employs a Support Vector Machine (SVM) in lieu of a Softmax layer for enhanced fault detection efficiency. A dataset for refrigerant leakage and charging faults was created using a Water-to-water Heat Pump (WWHP) test bench, providing the basis for evaluation against innovative algorithm and three existing algorithms: SVM, CNN-SVM, and PCNN-MSA-SVM. The findings highlight that TTAO successfully optimized the solution, minimizing the adaptation value from 0.167 to 0.025. The iterative process consistently demonstrated low loss values and steady accuracy improvements, trending towards enhanced stability. The proposed algorithm significantly outperformed the compared methods, achieving an impressive 97.5% accuracy rate and enhancing fault detection by 34.2%, 9.2%, and 4.2% respectively. Moreover, it showed robust and uniform F1 Scores across different fault types, marking an average increase of 42.0% over traditional SVM. This methodology not only optimizes hyperparameters adaptively but also identifies the best parameter settings, improving algorithm performance substantially.

在热泵系统中，制冷剂泄漏和充注故障是常见的问题。诊断热泵系统制冷剂泄漏和充注故障对于降低系统能耗、保持系统高效稳定运行至关重要。随着计算技术的不断迭代，数据驱动方法在故障检测和诊断中发挥着重要作用。本研究提出了一种新的算法，利用Gramian角场（GAF）将一维数据转换为图像格式，并通过并行卷积神经网络（PCNN）中的三角形拓扑聚合优化（TTAO）来优化超参数。此外，该方法集成了多头自关注机制（MSA），并采用支持向量机（SVM）代替Softmax层来提高故障检测效率。利用水对水热泵（WWHP）试验台建立了制冷剂泄漏和充注故障数据集，为创新算法和现有SVM、CNN-SVM和PCNN-MSA-SVM三种算法的评估提供了基础。结果表明，TTAO成功地优化了该方案，使自适应值从0.167降至0.025。迭代过程始终显示出低损耗值和稳定的精度改进，趋于增强稳定性。该算法的准确率达到了97.5%，提高了34.2%、9.2%和4.2%。此外，该方法在不同故障类型上均表现出鲁棒性和均匀性，比传统支持向量机平均提高42.0%。该方法不仅可以自适应优化超参数，而且可以识别最佳参数设置，大大提高了算法性能。

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引用次数: 0

Developing a spatial optimization design approach towards energy-saving and outdoor thermal comfortable densely-built residential blocks using a dynamic local energy balance model 利用动态局部能量平衡模型，为节能和室外热舒适的高密度住宅小区开发空间优化设计方法

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115194

Lin Liu , Zihong Zhang , Shiying Lan , Xiaoyu Tian , Jing Liu , Wei Liao , Dan Wang

Towards the dual goals of energy conservation and outdoor thermal comfort, this study proposed a parametric-oriented optimization design technology for densely-built residential blocks based on the dynamic local energy balance (DLEB) model. The DLEB model was corrected by hourly error formulas based on the field measurement data conducted in Guangzhou, China, which used six local climate zone-derived spatial morphological parameters as inputs. Additionally, the corrected DLEB model was improved by adding dual-goal calculation modules of building energy consumption and physiologically equivalent temperature. Orthogonal experiments were designed considering five parameters: building density, floor, and the area ratios of greenland, woodland, and water. A comprehensive indicator (CI) reflecting lower building energy consumption and higher outdoor environmental thermal comfort was used to design the objective function. Then, the corrected DLEB model was used to calculate the hourly environmental parameters and the CI of different cases. Results found that wind-thermal environments were affected by background weather and spatial morphological parameters. The error formulas show higher fitting effects with the goodness of fit higher than 0.4. A parametric-oriented spatial optimization strategy for high-density residential blocks was formed by determining the suitable value ranges of each spatial variable. The recommended building density ranged from 0.45 to 0.5, building floors were 10 ∼ 20 floors, and the area ratio of Greenland and woodland ranged from 0.25 to 0.4. Building floors and density contributed 48 % and 43 % to the comprehensive indicator, respectively. This study provides theoretical and technical guidance in dual-goal densely built residential areas.

为了实现节能和室外热舒适的双重目标，本研究提出了一种基于动态局部能量平衡（DLEB）模型的面向参数的密集住宅小区优化设计技术。DLEB 模型以中国广州的实地测量数据为基础，采用每小时误差公式对其进行了修正，并以六个当地气候带衍生的空间形态参数作为输入。此外，通过增加建筑能耗和生理当量温度的双目标计算模块，对修正后的 DLEB 模型进行了改进。设计的正交实验考虑了五个参数：建筑密度、楼层以及绿地、林地和水域的面积比。在设计目标函数时，使用了反映较低建筑能耗和较高室外环境热舒适度的综合指标（CI）。然后，使用修正后的 DLEB 模型计算不同情况下的每小时环境参数和 CI。结果发现，风热环境受到背景天气和空间形态参数的影响。误差公式显示出较高的拟合效果，拟合优度高于 0.4。通过确定各空间变量的合适取值范围，形成了以参数为导向的高密度住宅区空间优化策略。推荐的建筑密度范围为 0.45 至 0.5，建筑层数为 10 ∼ 20 层，绿地和林地的面积比范围为 0.25 至 0.4。建筑层数和密度分别占综合指标的 48% 和 43%。本研究为双目标密集居住区提供了理论和技术指导。

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引用次数: 0

Impact of block form on building energy consumption, urban microclimate and solar potential: A case study of Wuhan, China 街区形态对建筑能耗、城市小气候和太阳能潜力的影响——以武汉市为例

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115224

Liangyu Du , Hanyuan Wang , Chenhang Bian , Xi Chen

To enhance the overall energy efficiency of buildings and peripheral urban environment, a holistic approach is essential, requiring the integration of urban microclimate and energy modeling as well as building-integrated photovoltaics (BIPV) potential estimation. However, there is a notable paucity of studies that address the interaction between these metrics and urban block form design. The objective of this paper is to develop a parametric model that investigates the interplay between key urban design factors (i.e. the sky view factor, building density, and building height), and urban energy and thermal performances, within selected typical urban block form patterns. The study evaluates the overall energy performance of buildings, including the energy use intensity and photovoltaic power generation, while considering the local climate regulation such as mitigating the urban heat island effect. Additionally, an integrated urban performance optimization platform was developed to conduct modeling experiments in several high-density areas in Wuhan. The findings provide valuable insights for urban designers in selecting optimal urban forms that maximize solar energy utilization and minimize both building energy consumption and the urban heat island effect. Moreover, a comparison between conventional design optimization processes and advanced techniques, such as machine learning and deep learning based prediction, reveals that deep learning models combined with machine learning algorithms can achieve a prediction accuracy up to 98.3%, offering a more efficient workflow. This approach can significantly improve the decision-making process for urban planning and renovation.

为了提高建筑和周边城市环境的整体能源效率，必须采用整体方法，将城市微气候和能源建模以及建筑集成光伏（BIPV）潜力估算相结合。然而，关于这些指标与城市街区形式设计之间的相互作用的研究明显缺乏。本文的目的是建立一个参数化模型，在选定的典型城市街区形式模式中，研究关键城市设计因素（即天空景观因素、建筑密度和建筑高度）与城市能源和热性能之间的相互作用。该研究评估了建筑的整体能源性能，包括能源使用强度和光伏发电，同时考虑了当地的气候调节，如减轻城市热岛效应。此外，开发了城市综合绩效优化平台，在武汉市多个高密度区域进行了模拟实验。研究结果为城市设计师选择最佳的城市形式提供了有价值的见解，以最大限度地利用太阳能，最大限度地减少建筑能耗和城市热岛效应。此外，将传统的设计优化流程与基于机器学习和深度学习的预测等先进技术进行比较，发现深度学习模型与机器学习算法相结合，预测准确率高达98.3%，提供了更高效的工作流程。这种方法可以显著改善城市规划和改造的决策过程。

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引用次数: 0

Long-Term field testing of the accuracy and HVAC energy savings potential of occupancy presence sensors in A Single-Family home 对单户住宅中占用感测器的准确性和暖通空调节能潜力进行长期现场测试

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115161

Zhihong Pang , Mingyue Guo , Zheng O’Neill , Blake Smith-Cortez , Zhiyao Yang , Mingzhe Liu , Bing Dong

The energy-saving potential of occupancy-centric smart thermostats has been extensively explored in simulations but lacked field testing for energy savings quantification and sensor performance assessment in real buildings. This paper presents a long-term field study conducted in a single-family home in Texas, U.S. to evaluate the performance of occupancy-centric controls (OCC) of HVAC (heating, ventilation, and air-conditioning) system in terms of energy savings, sensor accuracy, and impact on electric peak demand. The test site was equipped with a commercial off-the-shelf (COTS) smart thermostat and multiple occupancy presence sensors for OCC implementation. Additionally, a sub-metering system was installed to monitor electricity consumption of various end-use equipment, including the HVAC system. A supplementary device was installed to track the ground-truth occupancy for the accuracy evaluation of the occupancy presence sensor. Scenarios of baseline and OCC controls were alternated weekly over the 20-month testing period. The results indicated an effective OCC execution, as evidenced by indoor temperature profiles. During the 2023 cooling season, OCC achieved total energy savings of 1,958 kWh, corresponding to a 17.6% energy savings ratio. Under certain conditions, daily HVAC energy savings reached as high as 17 kWh, with a savings ratio of 35%. Sensor performance showed an overall accuracy of 83.8%, a False Positive Rate (FPR) of 12.8%, and a False Negative Rate (FNR) of 47.4%. A key limitation was the sensor’s inability to detect stationary occupants during sleep, leading to a midnight FNR of nearly 100% and significantly compromising thermal comfort. Additionally, the implementation of OCC resulted in extended periods of high electricity demand on summer afternoons, affecting occupant’s thermal comfort and posing potential challenges to community-level grid operations if OCC were widely adopted. This study addresses a critical research gap by empirically investigating energy-saving potential and occupancy sensor performance in residential buildings. Through a comprehensive field-testing study, the research examines the interrelationship between sensor accuracy, energy savings, and thermal comfort, an area that has received limited attention in the current literature.

以乘员为中心的智能恒温器的节能潜力在模拟中得到了广泛的探索，但缺乏在真实建筑中进行节能量化和传感器性能评估的现场测试。本文介绍了在美国德克萨斯州的一个单户住宅中进行的一项长期实地研究，以评估HVAC（采暖、通风和空调）系统在节能、传感器精度和对电力峰值需求影响方面的性能。测试现场配备了商用现货（COTS）智能恒温器和用于OCC实施的多个占用状态传感器。此外，还安装了分计量系统，以监测各种终端设备的用电量，包括暖通空调系统。安装了一个辅助装置来跟踪地面真实占用，以评估占用存在传感器的精度。在20个月的测试期间，基线和OCC对照方案每周交替进行。结果表明，有效的OCC执行，证明了室内温度分布。在2023年制冷季，OCC实现了1958千瓦时的总节能，相当于17.6%的节能率。在一定条件下，每日暖通空调节能高达17千瓦时，节电率达35%。传感器的总体准确率为83.8%，假阳性率（FPR）为12.8%，假阴性率（FNR）为47.4%。一个关键的限制是传感器无法在睡眠时检测到静止的居住者，导致午夜的FNR接近100%，并且严重影响热舒适性。此外，OCC的实施导致夏季下午的高电力需求延长，影响了居住者的热舒适，如果OCC被广泛采用，将对社区电网运营构成潜在挑战。本研究通过实证研究住宅建筑的节能潜力和占用传感器性能，解决了一个关键的研究空白。通过一项全面的现场测试研究，该研究考察了传感器精度、节能和热舒适之间的相互关系，这是目前文献中受到有限关注的一个领域。

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引用次数: 0

Sustainable construction and combo nanocellulose: A synergistic approach to greener building materials 可持续建筑和复合纳米纤维素：绿色建筑材料的协同方法

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115218

Sobia Naseem , Muhammad Rizwan

Combo nanocellulose presents a promising avenue for enhancing the sustainability and performance of cementitious materials. This review explores the potential of Combo nanocellulose as a green additive in cement, focusing on its ability to improve mechanical properties, durability, and environmental impact. The unique characteristics of different nanocellulose types, such as cellulose nanocrystals (CNC), cellulose nanofibrils (CNF), and bacterial nanocellulose (BNC), are manipulated in combination to create superior reinforcement effects. These effects include enhanced tensile strength, reduced shrinkage, and improved crack resistance. Furthermore, the addition of Combo nanocellulose contributes to a significant reduction in the carbon footprint of cement production, aligning with the goals of sustainable construction. Life Cycle Assessment (LCA) studies highlight the environmental benefits, including reduced energy consumption and lower greenhouse gas emissions. This review critically examines the production methods, synergistic effects, and practical applications of Combo Nanocellulose in construction, providing insights into its potential to revolutionize the cement industry. Overall, Combo nanocellulose emerges as a sustainable, efficient, and economically feasible solution for developing next-generation green cementitious materials, paving the way for more resilient and environmentally friendly infrastructure. The potential challenges of utilizing CNC in sustainable construction include its susceptibility to moisture, which can compromise structural integrity, and the high energy demands associated with its extraction and processing. Additionally, scalability and cost-effectiveness remain critical limitations, hindering widespread adoption in the building materials industry.

复合纳米纤维素为增强胶凝材料的可持续性和性能提供了一条有前途的途径。这篇综述探讨了复合纳米纤维素作为一种绿色水泥添加剂的潜力，重点是其改善机械性能、耐久性和环境影响的能力。不同纳米纤维素类型的独特特性，如纤维素纳米晶体（CNC）、纤维素纳米原纤维（CNF）和细菌纳米纤维素（BNC），被操纵在一起，以创造优越的增强效果。这些效果包括增强抗拉强度，减少收缩，改善抗裂性。此外，复合纳米纤维素的加入有助于显著减少水泥生产的碳足迹，与可持续建筑的目标保持一致。生命周期评估（LCA）研究强调了环境效益，包括减少能源消耗和减少温室气体排放。这篇综述对复合纳米纤维素的生产方法、协同效应和在建筑中的实际应用进行了批判性的研究，为其在水泥行业的革命性发展提供了见解。总的来说，Combo纳米纤维素是开发下一代绿色胶凝材料的一种可持续、高效、经济可行的解决方案，为更有弹性和更环保的基础设施铺平了道路。在可持续建筑中使用CNC的潜在挑战包括其对水分的敏感性，这可能会损害结构的完整性，以及与其提取和加工相关的高能耗需求。此外，可扩展性和成本效益仍然是关键的限制，阻碍了建筑材料行业的广泛采用。

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引用次数: 0

Optimizing lighting design in educational settings for enhanced cognitive performance: A literature review 在教育环境中优化照明设计以提高认知能力：文献综述

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115180

Meriç Çelik , Altuğ Didikoğlu , Tuğçe Kazanasmaz

Lighting has more functions than simply illuminating spaces. For humans, light is the main signal that aligns our body’s internal clock, regulating circadian rhythms. This process instructs our bodies to wake up in the morning, become alert during the day, and feel sleepy at night. Disruption of these rhythms can impact neurological and psychiatric health, including cognitive performance. We can utilize light for mood improvements and better cognitive performance to create a suitable learning environment for students in educational buildings. These non-visual effects of light need to be considered from the beginning of the design process, making an interdisciplinary effort necessary. Even with adequate light and dark, the human eye reacts differently under various conditions, influenced by light’s photometric and colorimetric properties. While natural sunlight is ideal for aligning with our biological clock, it is not always sufficient, making artificial lighting essential indoors. LED technology offers promising solutions, catering to our non-visual needs in the absence of natural light and providing energy efficiency. This study reviews the literature that includes students’ cognitive performance and well-being, energy efficiency, running costs, and environment-related issues such as light pollution. It aims to explore the impact of lighting design in learning environments.

照明有更多的功能，而不仅仅是照亮空间。对人类来说，光是调节我们身体内部生物钟、调节昼夜节律的主要信号。这个过程指示我们的身体在早上醒来，白天变得警觉，晚上感到困倦。这些节律的紊乱会影响神经和精神健康，包括认知能力。我们可以利用光来改善情绪和更好的认知表现，为教育建筑中的学生创造一个合适的学习环境。光的这些非视觉效果需要从设计过程的开始就考虑到，这需要跨学科的努力。即使有足够的光和暗，人眼在不同条件下的反应也不同，受光的光度和比色特性的影响。虽然自然阳光是与我们的生物钟保持一致的理想选择，但它并不总是足够的，因此在室内必须使用人工照明。LED技术提供了有前途的解决方案，满足了我们在没有自然光的情况下的非视觉需求，并提供了能源效率。本研究回顾了包括学生认知表现和幸福感、能源效率、运行成本和环境相关问题（如光污染）在内的文献。它旨在探讨照明设计对学习环境的影响。

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引用次数: 0

Coupling thermal energy storage with a thermally anisotropic building envelope for building demand-side management across various US climate conditions 将热能储存与热各向异性建筑围护结构相结合，在美国各种气候条件下进行建筑需求侧管理

IF 6.6 2区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Energy and Buildings

Pub Date : 2025-02-01 DOI: 10.1016/j.enbuild.2024.115204

Zhenglai Shen , Daniel Howard , Diana Hun , Sven Mumme , Som Shrestha

The thermally anisotropic building envelope (TABE) is a novel active building envelope that enhances energy efficiency and thermal comfort in buildings by transferring heat and cold between building envelopes and hydronic loops. When coupled with thermal energy storage (TES) units, the TABE + TES enables the storage of both heat and cold energy captured by the TABE roof or exterior walls. This stored energy can be later released by the TABE floor for indoor heating and cooling, benefiting both the grid and the end user. This paper evaluates the merits of TABE + TES for building demand-side management across various US climate conditions, focusing on peak load shaving, annual energy savings, and cost savings under time-of-use (TOU) electric rate schedules. Simulations were conducted by integrating time-of-day–informed, rule-based control strategies in MATLAB, TABE components and TES units in COMSOL Multiphysics, and whole-building energy analysis in EnergyPlus. A case study using the US Department of Energy’s prototype single-family detached house model in Birmingham, Alabama; Los Angeles, California; Oak Ridge, Tennessee; and Denver, Colorado, showed that the TABE + TES system achieved (1) 70 % peak load shaving in Los Angeles and Denver and 20 % in Birmingham and Oak Ridge; (2) significant peak electricity savings of 351–497 kWh, reducing peak energy consumption by 38 %–78 %; and (3) annual heating cost savings of 0.79 $/m²–1.17 $/m² and cooling cost savings of 0.60 $/m²–1.17 $/m² using a normal utility rate or low-TOU rate. The benefits of employing the TABE + TES system are even more significant under high TOU rates.

热各向异性建筑围护结构（热各向异性建筑围护结构）是一种新型的主动建筑围护结构，通过在建筑围护结构和流体循环之间传递冷热来提高建筑的能源效率和热舒适性。当与热能储存（TES）装置相结合时，table + TES可以储存由table屋顶或外墙捕获的热能和冷能。这些储存的能量随后可以通过table地板释放出来，用于室内供暖和制冷，这对电网和最终用户都有利。本文评估了table + TES在美国各种气候条件下对建筑需求侧管理的优点，重点关注峰值负荷削减、年度节能和在使用时间（TOU）电价表下的成本节约。通过集成MATLAB中的时间信息、基于规则的控制策略、COMSOL Multiphysics中的TABE组件和TES单元以及EnergyPlus中的整栋建筑能耗分析，进行了仿真。以美国能源部在阿拉巴马州伯明翰的单户独立式住宅模型为例进行研究；加州洛杉矶；田纳西州的橡树岭；结果表明，TABE + TES系统在洛杉矶和丹佛实现了70%的调峰，在伯明翰和橡树岭实现了20%的调峰；(2)峰值节电351-497千瓦时，峰值能耗降低38% - 78%；(3)使用正常公用事业费率或低tou费率，每年供暖费用节省0.79美元/平方米至1.17美元/平方米，制冷费用节省0.60美元/平方米至1.17美元/平方米。在高分时电价的情况下，采用表+ TES系统的好处更为显著。

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