Energy and Buildings最新文献_第8页

Nature-inspired temperature-adaptive module: Achieving all-season passive thermal regulation for buildings 受大自然启发的温度适应模块：实现建筑物四季被动式热调节

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

Energy and Buildings

Pub Date : 2024-10-28 DOI: 10.1016/j.enbuild.2024.114949

Lin Liang , Jianheng Chen , Kaixin Lin , Xueming Yang , Sai Liu , Chui Ting Kwok , Hao Pan , Ziai Liu , Aiqiang Pan , Siru Chen , Yihao Zhu , Wei Li , Qingping Sun , Chi Yan Tso

With the increasing focus on sustainable energy practices, thermal management within the building sector has been recognized as an important strategic approach to reducing energy consumption and improving overall energy efficiency. Passive radiative cooling (PRC) offers cooling without external power, but most PRC systems lack the ability to modulate cooling power automatically in response to climate variations, leading to increased heating energy penalties during cold periods. Integrating passive cooling modules with a tunable solar heating function could provide a more efficient solution than one-way control, optimizing energy efficiency in buildings. Inspired by the self-folding leaves of the Mimosa pudica, we introduce a new dual-mode temperature-adaptive module (TAM) for architectural applications. The TAM is composed of a three-layer structure, consisting of a bottom bilayer with Janus thermal expansion properties and a top waterproofing layer. This configuration enables the TAM to autonomously switch between open and closed states in response to changes in ambient temperature, while exhibiting excellent outdoor durability. Field tests confirmed the effective radiative thermal regulation capability of the TAM under varying external conditions. In terms of its diurnal performance, it provides a thermal insulation effect, resulting in an above-ambient temperature increase of 1.98 °C during cold nighttime and a sub-ambient temperature decrease of 8.79 °C during hot daytime. When considering its seasonal/regional performance, it offers up to 16.77 °C of above-ambient heating in cold months/regions while providing cooling in hot conditions. The module also comes in various colors to fulfill aesthetic and design prerequisites. This scalable and economically viable innovation represents a notable leap forward in radiative thermal management, delivering tangible benefits for buildings in climates with considerable diurnal and seasonal temperature fluctuations.

随着可持续能源实践日益受到重视，建筑领域的热管理已被视为降低能耗和提高整体能效的重要战略方法。被动辐射制冷（PRC）无需外接电源即可实现制冷，但大多数被动辐射制冷系统缺乏根据气候变化自动调节制冷功率的能力，从而导致在寒冷时期增加供热能耗。与单向控制相比，将被动冷却模块与可调节的太阳能加热功能相结合，可以提供更有效的解决方案，优化建筑物的能效。受含羞草自折叠叶片的启发，我们为建筑应用推出了一种新型双模温度自适应模块（TAM）。该模块由三层结构组成，包括具有杰纳斯热膨胀特性的底部双层和顶部防水层。这种结构使 TAM 能够根据环境温度的变化在打开和关闭状态之间自主切换，同时表现出卓越的户外耐用性。现场测试证实了 TAM 在不同外部条件下的有效辐射热调节能力。就其昼夜性能而言，它具有隔热效果，在寒冷的夜间可使高于环境温度的温度上升 1.98 °C，在炎热的白天可使低于环境温度的温度下降 8.79 °C。考虑到它的季节/地区性能，在寒冷的月份/地区，它可提供高于环境温度 16.77 °C的供暖，而在炎热的条件下则可提供制冷。该模块还有多种颜色可供选择，以满足美学和设计要求。这种可扩展且经济可行的创新技术代表了辐射热管理领域的一次显著飞跃，为昼夜温差和季节温差较大的气候条件下的建筑物带来了切实的好处。

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引用次数: 0

Optimization and prediction of office building shading devices for energy, daylight, and view consideration using genetic and BO-LGBM algorithms 使用遗传算法和 BO-LGBM 算法优化和预测办公楼遮阳设备，以考虑能源、日光和景观因素

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

Energy and Buildings

Pub Date : 2024-10-28 DOI: 10.1016/j.enbuild.2024.114939

Hangyue Zhang, Yanqiu Cui, Hongbin Cai, Zhengshu Chen

In modern office buildings, the pursuit of a transparent and aesthetically pleasing facade often results in a high window-to-wall ratio, leading to excessive solar radiation entering the interior. This increases air conditioning energy consumption to ensure indoor comfort. Architectural shading design can block solar radiation, but inappropriate shading design can reduce daylight levels or block view out. Therefore, effectively balancing daylight and view out while reducing building energy consumption remains a pressing issue. In this study, an office building in Jinan, Shandong Province as a baseline model. Using Grasshopper and Python, a data-driven method integrating analysis, optimization, and prediction was constructed to optimize various design parameters of shading devices, such as spacing, width, and rotation angle of shading panels, using a genetic algorithm. The BO-LGBM algorithm was used to establish a classification prediction model for office building performance, verifying the model’s accuracy and exploring the contribution of different shading design parameters to performance prediction. The research results indicate that the optimized shading scheme not only improves visual comfort and ensures sufficient natural light and good view out, but also reduces building energy consumption by 0.63%–2.17%. Key factors for energy prediction include the spacing, rotation angle, and width of south facade panels, and the rotation angle of east facade panels. This method improves the interactive feedback efficiency between shading design decisions and building performance assessment, providing a valuable theoretical reference for designers in the early stages of architectural shading design.

在现代办公楼中，为了追求通透美观的外立面，通常会采用较高的窗墙比，从而导致过多的太阳辐射进入室内。这就增加了为确保室内舒适度而消耗的空调能耗。建筑遮阳设计可以阻挡太阳辐射，但不恰当的遮阳设计会降低日照水平或遮挡视线。因此，如何在降低建筑能耗的同时有效平衡日照和视野，仍然是一个亟待解决的问题。本研究以山东省济南市的一栋办公楼为基准模型。使用 Grasshopper 和 Python，构建了一种集分析、优化和预测于一体的数据驱动方法，利用遗传算法优化遮阳设备的各种设计参数，如遮阳板的间距、宽度和旋转角度等。利用 BO-LGBM 算法建立了办公建筑性能分类预测模型，验证了模型的准确性，并探讨了不同遮阳设计参数对性能预测的贡献。研究结果表明，优化的遮阳方案不仅能改善视觉舒适度，确保充足的自然光和良好的视野，还能降低建筑能耗 0.63%-2.17%。能耗预测的关键因素包括南立面遮阳板的间距、旋转角度和宽度，以及东立面遮阳板的旋转角度。该方法提高了遮阳设计决策与建筑性能评估之间的互动反馈效率，为设计师在建筑遮阳设计的早期阶段提供了有价值的理论参考。

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引用次数: 0

Experimental study on improving effect of cooling garment on thermal comfort and salivary IgA concentration 改善降温衣对热舒适度和唾液 IgA 浓度影响的实验研究

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

Energy and Buildings

Pub Date : 2024-10-26 DOI: 10.1016/j.enbuild.2024.114970

Huxiang Lin, Haiying Wang, Renjie Yan, Junli Sun, Hang Meng, Songtao Hu

Phase change cooling garments (PCCGs) can effectively alleviate the heat stress of manual workers in high-temperature environments. The PCCGs bring about cold stimuli to users, which not only affect the thermal perception and thermoregulation of the human body, but also could have some influence on the nervous and endocrine system, and even on the immune system. This study explores the effects of PCCGs on thermal comfort and respiratory mucosal immune function. Experiments were conducted in a climate chamber at 33 °C with a relative humidity of 50 %. Twenty participants were recruited and experienced three experimental conditions (NG, normal garments; PCCGs with a cooling temperature of 21 °C, PCCGs-21 and 17 °C, PCCGs-17). Subjects took packing activity with a metabolic rate of around 2.7 met. Subjective questionnaires (thermal sensation votes, thermal comfort votes) were collected, and physiological parameters (skin temperature, core temperature) were tested. Besides, the salivary samples were gathered to measure the Salivary secretory immunoglobulin A (S-IgA) concentrations using enzyme-linked immunosorbent assay (ELISA). The results showed that the use of PCCGs affected the S-IgA concentration significantly. Compared with the NG condition, the S-IgA concentrations increased by 55.9 % and 46.4 % in the PCCGs-21 and PCCGs-17 conditions, respectively. Additionally, the S-IgA concentrations were the highest when participants felt slightly warm or comfortable. The S-IgA concentration of the comfortable state was 98.5 % higher than that of the intolerable state. The S-IgA concentrations were also found to be negatively correlated with local skin temperatures of the back and chest (p < 0.001). The use of PCCGs has a positive influence on improving thermal comfort and S-IgA concentration.

相变冷却服装（PCCGs）可以有效缓解高温环境下体力劳动者的热应激反应。PCCG 给使用者带来冷刺激，不仅影响人体的热感知和体温调节，还可能对神经系统、内分泌系统甚至免疫系统产生一定影响。本研究探讨了 PCCG 对热舒适性和呼吸道粘膜免疫功能的影响。实验在温度为 33 °C、相对湿度为 50 % 的气候箱中进行。共招募了 20 名参与者，他们在三种实验条件下进行了实验（NG，正常服装；PCCGs 制冷温度为 21 °C，PCCGs-21 和 17 °C，PCCGs-17）。受试者以约 2.7 米的新陈代谢率进行打包活动。收集了主观问卷（热感觉票数、热舒适度票数），并测试了生理参数（皮肤温度、核心温度）。此外，还收集了唾液样本，利用酶联免疫吸附试验（ELISA）测量唾液分泌型免疫球蛋白 A（S-IgA）的浓度。结果显示，使用 PCCGs 对 S-IgA 浓度有显著影响。与 NG 条件相比，PCCGs-21 和 PCCGs-17 条件下的 S-IgA 浓度分别增加了 55.9% 和 46.4%。此外，当参与者感到微热或舒适时，S-IgA 浓度最高。舒适状态下的 S-IgA 浓度比难以忍受状态下的 S-IgA 浓度高 98.5%。研究还发现，S-IgA 浓度与背部和胸部的局部皮肤温度呈负相关（p < 0.001）。使用 PCCG 对改善热舒适度和 S-IgA 浓度有积极影响。

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引用次数: 0

Automatic standard building category classification from smart meter data – A supervised learning approach 从智能电表数据中自动划分标准建筑类别--一种监督学习方法

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

Energy and Buildings

Pub Date : 2024-10-26 DOI: 10.1016/j.enbuild.2024.114954

Synne Krekling Lien , Jayaprakash Rajasekharan

Increased availability of smart meter data offers better insight into buildings’ electricity usage. By classifying smart meter data by building type and presence of heating appliances, we can efficiently gain metadata about the buildings that is useful for research, grid planning, and energy efficiency policy employment. However, current smart meter classification approaches are largely based on limited datasets and building classes, or on unsupervised methods that don’t align with standard building categories and offer limited control over grouping. This article presents a supervised automatic building category classification approach for labelling smart meter data from buildings into standard building categories in the Norwegian building regulations (TEK17), and whether they have electric heating or not. 82 novel physics-based domain features are presented which can be extracted from any hourly electricity smart meter data series from buildings with a duration of months-years. The features are specifically designed to identify the building and heating type of a smart meter data series by capturing patterns such as seasonality, daily usage trends, similarities with standardized building load profiles, temperature dependency, and other domain-specific characteristics. The classification approach is trained and tested on a large dataset of 2724 buildings from 12 different building categories, both residential and non-residential, and correctly identifies the heating type and building category of unseen Norwegian smart meter data from buildings in 84 % of the test cases. The approach is generalizable to meter data from other Norwegian buildings and is also tested on buildings from other climate zones. The proposed method for smart meter data classification is proven to have high accuracy and applicability for extracting metadata for both residential and non-residential buildings in Norway.

智能电表数据的日益普及使我们能够更好地了解建筑物的用电情况。通过对智能电表数据进行建筑类型和取暖设备的分类，我们可以有效地获得有关建筑的元数据，这些数据对研究、电网规划和能效政策的制定都非常有用。然而，目前的智能电表分类方法大多基于有限的数据集和建筑类别，或基于与标准建筑类别不一致的无监督方法，对分组的控制能力有限。本文介绍了一种有监督的自动建筑类别分类方法，用于将建筑物的智能电表数据标记为挪威建筑法规（TEK17）中的标准建筑类别，以及是否有电采暖。该方法介绍了82个基于物理学的新领域特征，这些特征可从建筑物的任何小时智能电表数据系列中提取，持续时间为数月至数年。这些特征专为识别智能电表数据序列中的建筑物和供暖类型而设计，可捕捉到各种模式，如季节性、日常使用趋势、与标准化建筑物负荷曲线的相似性、温度依赖性以及其他特定领域的特征。该分类方法在一个大型数据集上进行了训练和测试，该数据集包含来自 12 个不同建筑类别（包括住宅和非住宅）的 2724 栋建筑，在 84% 的测试案例中正确识别了来自建筑物的未见挪威智能电表数据的供暖类型和建筑类别。该方法适用于挪威其他建筑的电表数据，并在其他气候区的建筑中进行了测试。事实证明，所提出的智能电表数据分类方法具有很高的准确性和适用性，可用于提取挪威住宅和非住宅建筑的元数据。

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引用次数: 0

Radiant heating systems control in buildings via Inverse Conformable Artificial Neural Networks and optimization techniques 通过反适应人工神经网络和优化技术控制建筑物中的辐射供暖系统

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

Energy and Buildings

Pub Date : 2024-10-26 DOI: 10.1016/j.enbuild.2024.114968

A.I. Mata , J.I. Johnson , A. Parrales , J.E. Solís-Pérez , A. Huicochea , J.A. Hernandez

This study introduces an innovative methodology that integrates Inverse Conformable Artificial Neural Networks (CANNi) with Genetic Algorithms (GA) or Particle Swarm Optimization (PSO) to optimize thermal comfort in buildings. Emphasizing the efficacy of conformable transfer functions within CANNi, the research relies on a comprehensive dataset to forecast heat transfer across diverse climates. Notably, the methodology stands out for its meticulous model selection process, employing slope-intercept tests to ensure robust predictability (99%) and strong correlation between input and output variables. The selected model exhibits an optimal equilibrium between predictive precision and computational efficiency, reaching an R-value of 0.9992 with low RMSE (0.0078) and MAPE (2.1099). Such performance enables precise calibration of Radiant Floor Heating Systems (RFH) for enhanced comfort and marks a significant stride toward bolstering energy efficiency and sustainability within the construction sector. These findings advocate for more efficient utilization of energy resources in buildings, adeptly accommodating climatic fluctuations and enhancing the inhabitants’ quality of life.

本研究介绍了一种创新方法，该方法将反适形人工神经网络（CANNi）与遗传算法（GA）或粒子群优化（PSO）相结合，以优化建筑物的热舒适度。该研究强调了 CANNi 中顺应性传递函数的功效，并依靠一个全面的数据集来预测不同气候条件下的热传递。值得注意的是，该方法的突出之处在于其细致的模型选择过程，采用了斜率-截距测试，以确保输入和输出变量之间的稳健可预测性（99%）和强相关性。所选模型在预测精度和计算效率之间实现了最佳平衡，R 值达到 0.9992，RMSE（0.0078）和 MAPE（2.1099）均较低。这种性能可以精确校准地板辐射供暖系统（RFH），从而提高舒适度，并标志着建筑行业在提高能效和可持续性方面取得了重大进展。这些研究结果倡导在建筑物中更有效地利用能源资源，巧妙地适应气候波动，提高居民的生活质量。

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引用次数: 0

Phase change material incorporated paper pulp sludge/gypsum composite reinforced by slag and fly ash for energy efficient buildings: Solar thermal regulation, embody energy, sustainability index and cost analysis 用矿渣和粉煤灰增强纸浆污泥/石膏复合材料的相变材料，用于节能建筑：太阳能热调节、能源体现、可持续性指数和成本分析

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

Energy and Buildings

Pub Date : 2024-10-26 DOI: 10.1016/j.enbuild.2024.114969

Nilay Kucukdogan , Mucahit Sutcu , Savas Ozturk , Hasbi Yaprak , Selcuk Memis , Osman Gencel , Abid Ustaoglu , Ahmet Sari , Gokhan Hekimoglu , Ertugrul Erdogmus

This study focuses on the reuse of some industrial wastes in the development of innovative building materials and the thermal performance, environmental impacts and cost estimates of the gypsum composite material developed in the case of a phase change material impregnation. Lauryl alcohol (LA) was impregnated into paper pulp sludge (PPS) up to 45 % by weight without leakage to obtain shape-stable composites. The LA impregnated PPS (PPS/LA) was replaced with PPS at 50 % and 100 % by weight in gypsum composite. Characteristics of shape-stable composites were studied. Also, the physical, mechanical, thermal properties and solar thermoregulation tests of the produced gypsum composites were examined in addition to the embodied energy, CO₂ emissions and cost analysis. The melting and solidification enthalpies of PPS/LA were found to be 100.4–100.1 J/g, with only a 0.5 % reduction in latent heat storage capacity after 500 cycles, and approximately 3 % after 1500 cycles. Although the presence of PPS/LA in the gypsum composite caused a slight decrease in compressive strength, it significantly improved solar thermoregulation performance, maintaining ambient temperatures 2.55 °C to 5 °C warmer at night and 5.3 °C to 13.8 °C cooler during the day. Gypsum composites containing the PPS/LA offer a suitable alternative for energy-efficient sustainable building application by reusing around 57 % of three different industrial wastes providing a waste-reducing environmental approach and a high level of indoor thermal comfort.

本研究的重点是一些工业废料在创新建筑材料开发中的再利用，以及在相变材料浸渍情况下开发的石膏复合材料的热性能、环境影响和成本估算。将月桂醇（LA）按重量浸渍到纸浆污泥（PPS）中，浸渍率高达 45%，且无渗漏，从而获得形状稳定的复合材料。在石膏复合材料中，用重量百分比为 50% 和 100% 的 PPS 取代经 LA 浸渍的 PPS（PPS/LA）。研究了形状稳定复合材料的特性。此外，还对生产的石膏复合材料的物理、机械、热性能和太阳能热调节测试进行了研究，并进行了体现能源、二氧化碳排放和成本分析。研究发现，PPS/LA 的熔化焓和凝固焓为 100.4-100.1 J/g，在循环 500 次后，潜热储存能力仅降低 0.5%，在循环 1500 次后，降低约 3%。虽然 PPS/LA 在石膏复合材料中的存在会导致抗压强度略有下降，但它显著改善了太阳能热调节性能，使夜间环境温度保持在 2.55 °C 至 5 °C 之间，白天环境温度保持在 5.3 °C 至 13.8 °C 之间。含有 PPS/LA 的石膏复合材料为高能效的可持续建筑应用提供了一个合适的替代方案，它重复利用了约 57% 的三种不同的工业废料，提供了一种减少废物的环保方法和高水平的室内热舒适度。

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引用次数: 0

Seasonal thermal performance of a macro-encapsulated phase change material blind integrated double skin façade system: An experimental study 宏观封装相变材料盲板集成双层幕墙系统的季节热性能：实验研究

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

Energy and Buildings

Pub Date : 2024-10-26 DOI: 10.1016/j.enbuild.2024.114952

Yilin Li , Sipeng Fu , Yidong Li , Yuke Peng , Caiyi Yang , Wanting Tao , Haidong Wang

Double skin facade (DSF) faces problems of overheating issues in warm seasons, and low cavity temperature in cold seasons, which may reduce indoor thermal comfort and increase energy consumption in buildings. Integrating phase change material (PCM) blind in DSFs is a promising solution to improve its thermal performance. However, current research on macro-encapsulated PCM blinds lacks systematic process of system development and comprehensive experimental studies across different seasons. To overcome these limitations, a zonal method was firstly used to establish a heat transfer model for the PCM blind integrated DSF system. A prototype of the proposed macro-encapsulated PCM blinds with aluminium shell and DSF integrated system was developed. Experiments were conducted during warm season and cold season in Shanghai, China. The cavity air temperature and blind surface temperature of the integrated system were analysed and compared with aluminium alloy blind system. The results indicate that PCM blinds can significantly reduce cavity air temperature and blind surface temperature, and provided better thermal stability compared to aluminium blinds during warm seasons. In cold season, PCM blind demonstrated excellent heat sustaining ability, and can maintaining ideal cavity air temperatures, while aluminium blinds experience a significant temperature drop during the same period.

双层幕墙（DSF）在温暖季节面临过热问题，而在寒冷季节则面临空腔温度过低的问题，这可能会降低室内热舒适度并增加建筑能耗。将相变材料（PCM）盲板集成到 DSF 中是改善其热工性能的一个很有前景的解决方案。然而，目前有关宏观封装 PCM 百叶窗的研究缺乏系统的系统开发过程和跨季节的全面实验研究。为了克服这些局限性，研究人员首先采用分区法建立了 PCM 百叶帘集成 DSF 系统的传热模型。随后，开发出了带有铝制外壳和 DSF 集成系统的拟议宏观封装 PCM 百叶窗原型。实验分别在中国上海的暖季和冷季进行。分析了集成系统的空腔空气温度和百叶帘表面温度，并与铝合金百叶帘系统进行了比较。结果表明，与铝合金百叶帘相比，PCM 百叶帘在暖季可显著降低室内空气温度和百叶帘表面温度，并提供更好的热稳定性。在寒冷季节，PCM 百叶帘表现出卓越的保温能力，能保持理想的空腔空气温度，而铝合金百叶帘在同一时期则会出现明显的温度下降。

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引用次数: 0

An innovative Trombe wall with a solar concentrating function 具有太阳能聚光功能的创新型 Trombe 墙

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

Energy and Buildings

Pub Date : 2024-10-26 DOI: 10.1016/j.enbuild.2024.114942

Xianzhang Dong , Huigang Xiao , Min Liu , Baochen Lin , Wei Wang

The Trombe wall, recognized for harnessing solar energy to heat buildings, has become a focal point in energy conservation research. However, its low heating efficiency in winter and increased cooling energy consumption in summer have hindered its broader application. To address these issues, this study proposes a novel Trombe wall with a solar concentration function. Compared to traditional Trombe walls, this innovative design features an added concentrating glass cover to increase solar radiation density, and a zoned configuration that enables the energy-capturing mechanism to automatically activate in winter and shut down in summer. Focusing on the typical winter and summer weather conditions in Jinan, a validated simulation model was developed to analyze the thermal performance and energy consumption of this innovative Trombe wall across both seasons. The results show that the novel Trombe wall offers significant energy-saving benefits. Compared to conventional designs, it improves heating efficiency by 11.7% in winter and enhances thermal resistance efficiency by 85.2% in summer. Consequently, energy consumption is reduced by 28.6% in winter and 75.7% in summer. The introduction of this system provides a new pathway for building energy efficiency and contributes to the realization of zero-energy buildings.

特洛姆贝墙是公认的利用太阳能为建筑物供暖的技术，已成为节能研究的焦点。然而，其冬季供暖效率低、夏季制冷能耗高的缺点阻碍了它的广泛应用。为解决这些问题，本研究提出了一种具有太阳能集中功能的新型 Trombe 墙。与传统的 Trombe 墙相比，这种创新设计的特点是增加了一个聚光玻璃罩，以提高太阳辐射密度，并采用分区配置，使能量捕捉机制在冬季自动启动，在夏季自动关闭。针对济南典型的冬夏气候条件，我们开发了一个经过验证的仿真模型，以分析这种创新型 Trombe 墙在两个季节的热性能和能耗。结果表明，新型 Trombe 墙具有显著的节能优势。与传统设计相比，它在冬季将供暖效率提高了 11.7%，在夏季将热阻效率提高了 85.2%。因此，冬季能耗降低了 28.6%，夏季能耗降低了 75.7%。该系统的引入为建筑节能提供了一条新途径，有助于实现零能耗建筑。

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引用次数: 0

Experimental study and simulation of a solid desiccant cooling system installed in northern Algeria 阿尔及利亚北部安装的固体干燥剂冷却系统的实验研究与模拟

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

Energy and Buildings

Pub Date : 2024-10-24 DOI: 10.1016/j.enbuild.2024.114943

M. Kassim , M. Merzouk , N. Kasbadji Merzouk , L. Merabti , W. Taane , F. Bouzeffour , M.A. Ounnar , D. Belkacemi

An experimental investigation of a solid desiccant cooling system for a research laboratory on the Algerian coast has been carried out. The system utilized flat-plate solar collectors for regeneration and was evaluated through a combination of individual component characterization, system modeling (using TRNSYS), and experimental validation. The results obtained have been validated and show that the efficiency of the rotary heat exchanger reached 65 %, the evaporative humidifier efficiency reached 94 %, and the desiccant wheel achieved efficiencies of 73 % on the process side and 66 % on the regeneration side. This translates to a significant dehumidification effect, reducing absolute humidity in the treated air by 9 g/kg, for the supply air temperature effectively maintained at a comfortable 24 °C. The close agreement between the simulated and experimental COP values (1.13 and 1.08, respectively) validates the chosen approach and confirms the potential of this technology for energy-efficient building cooling in the hot and humid Mediterranean climate of northern Algeria.

对阿尔及利亚海岸研究实验室的固体干燥剂冷却系统进行了实验研究。该系统利用平板太阳能集热器进行再生，并通过单个组件特征描述、系统建模（使用 TRNSYS）和实验验证相结合的方式进行评估。验证结果表明，回转式热交换器的效率达到 65%，蒸发式加湿器的效率达到 94%，干燥轮的处理效率达到 73%，再生效率达到 66%。这意味着除湿效果显著，在供气温度有效保持在舒适的 24 °C 时，处理后空气的绝对湿度降低了 9 克/千克。模拟 COP 值和实验 COP 值（分别为 1.13 和 1.08）之间的接近一致验证了所选择的方法，并证实了该技术在阿尔及利亚北部炎热潮湿的地中海气候条件下用于节能建筑制冷的潜力。

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引用次数: 0

Optimal scheduling strategy of household electrical equipment based on scenario dynamic modeling 基于情景动态建模的家用电器设备优化调度策略

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

Energy and Buildings

Pub Date : 2024-10-24 DOI: 10.1016/j.enbuild.2024.114945

Xuxin He, Xiuying Yan

Household electricity is highly unpredictable, necessitating a deep understanding of its impact on energy scheduling for optimal resource allocation and economic gains. This issue’s complexity can lead traditional optimization methods to converge on suboptimal solutions. In this study, the dynamic Copula (DC) model is used to construct the dynamic correlation between power consumption characteristics, and the Monte Carlo (MC) method is used to generate multiple power consumption scenarios to cope with the uncertainty of user behavior. Then, the optimal scenario set is selected through the average distribution error (ADE) to participate in the subsequent scheduling. In addition, based on the established equipment operation characteristic model, the electricity cost and load peak-to-average ratio (PAR) are comprehensively considered. The Improved Dynamic search multi-objective particle swarm optimization (IDSMOPSO) is introduced to optimize the running time of the equipment. Taking the electricity consumption of a family in Xi’an as an example, the results show that the algorithm is significantly better than the other two improved algorithms in performance. Meanwhile, the electricity cost of the family was significantly reduced by 17.09 %, and the PAR value was also reduced by 31.59 %, which realized the economic operation of household electricity.

家庭用电具有很强的不可预测性，因此需要深入了解其对能源调度的影响，以优化资源配置，提高经济效益。这一问题的复杂性会导致传统优化方法收敛于次优解。本研究采用动态 Copula（DC）模型构建功耗特征之间的动态相关性，并采用蒙特卡罗（MC）方法生成多个功耗场景，以应对用户行为的不确定性。然后，通过平均分布误差（ADE）选择最优场景集参与后续调度。此外，基于已建立的设备运行特性模型，综合考虑了电费和负荷峰均比（PAR）。引入改进动态搜索多目标粒子群优化（IDSMOPSO）来优化设备的运行时间。以西安某家庭用电为例，结果表明该算法在性能上明显优于其他两种改进算法。同时，该家庭的电费大幅降低了 17.09%，PAR 值也降低了 31.59%，实现了家庭用电的经济运行。

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