Energy and Built Environment最新文献_第6页

Overview of the application status and development trends of hydropower and geothermal power in New Zealand 新西兰水电和地热发电应用现状及发展趋势概览

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-07-02 DOI: 10.1016/j.enbenv.2024.06.003

Yiheng Guan , Scott Post , Dan Zhao , Senlin Zhang , Sid Becker

Hydropower is an early and well-developed form of electricity generation in New Zealand, as well the most important form of electricity generation globally. This paper analyses the world's energy structure, along with New Zealand's energy structure, the distribution of existing hydroelectric power plants, hydroelectric power operators, the distribution of hydroelectric grids, types of hydroelectric power stations and types of hydro turbines. Furthermore, it also compares the hydropower development in New Zealand relative to other nations, such as China and Norway. New Zealand's power plants: hydro, geothermal and wind farms, are compared in terms of environmental impact, investment benefits, levelized generation costs, Māori culture and generation technology. Because countries worldwide are acting towards the 2050 carbon neutral, the use of electric vehicles is gradually increasing. Finally, Therefore, a surge in electricity generation, and its usage, is anticipated. To overcome this issue, upgrading and expanding existing hydropower plants or building small hydropower is considered to be one of the best options for New Zealand to fulfill the electricity demand and commitment towards low carbon emission.

水力发电是新西兰较早、发展较好的发电方式，也是全球最重要的发电方式。本文分析了世界能源结构，以及新西兰的能源结构，现有水电站的分布，水电运营商，水电电网的分布，水电站的类型和水轮机的类型。此外，它还将新西兰的水电开发与其他国家（如中国和挪威）进行了比较。新西兰的发电厂：水力、地热和风力发电场，在环境影响、投资效益、平化发电成本、Māori文化和发电技术方面进行了比较。由于世界各国都在朝着2050年碳中和的目标行动，电动汽车的使用正在逐渐增加。最后，因此，预计发电量及其使用量将激增。为了克服这一问题，升级和扩建现有水电站或建设小水电被认为是新西兰满足电力需求和实现低碳排放承诺的最佳选择之一。

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引用次数: 0

Exploring the role of skin temperature in thermal sensation and thermal comfort: A comprehensive review 探索皮肤温度在热感觉和热舒适度中的作用：全面回顾

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-03-06 DOI: 10.1016/j.enbenv.2024.03.002

Wenjie Song, Fangliang Zhong, John Kaiser Calautit, Jiaxiang Li

The role of skin temperature as a determinant of human thermal sensation and comfort has gained increasing recognition, prompting a need for a systematic review. This review examines the relationship between skin temperature and thermal sensation, synthesizing insights from 172 studies published since 2000. It uniquely focuses on the indispensable roles of local and mean skin temperatures, a perspective not comprehensively explored in previous literature. The review reveals that the most common measurement points for skin temperature are the face and hands, attributed to their higher thermal sensitivity and the practical ease of measurement. It establishes a clear linear relationship between mean skin temperature and user thermal sensation, though affected by the choice of measurement locations and number of points. A notable finding is the varying impact of local skin temperature on overall thermal sensation in changing environments, with local heating less influential than cooling. The review also uncovers demographic variations in thermal sensation, strongly influenced by differing skin temperatures across age groups, genders, and climatic regions. For example, elderly populations exhibit a decreased temperature sensitivity, especially towards warmth. Gender differences are also significant, with females experiencing higher skin temperatures in warmer environments and lower in colder ones. Machine learning (ML)-based methods, particularly those using classification tree and support vector machine (SVM) techniques, are increasingly used to predict thermal sensation and comfort by leveraging skin temperature data. While ML methods are prevalent, statistical regression-based approaches offer valuable empirical insights. Thermo-physiological model-based methods provide reliable results by incorporating detailed skin temperature dynamics. The review highlights a gap in understanding the influence of gender, age, and regional differences on thermal comfort across various environments. The study recommends conducting more detailed experiments to examine the impact of these factors more closely. It also suggests integrating individual demographic variables into ML models to personalize thermal comfort predictions.

皮肤温度作为人体热感觉和舒适的决定因素的作用已经得到越来越多的认识，促使需要进行系统的综述。本综述综合了自2000年以来发表的172项研究的见解，研究了皮肤温度和热感觉之间的关系。它独特地关注了局部和平均皮肤温度的不可或缺的作用，这是以前文献中没有全面探讨的观点。该综述显示，由于面部和手部的热敏性较高，且实际测量容易，因此最常见的皮肤温度测量点是面部和手部。它在平均皮肤温度和用户热感觉之间建立了明确的线性关系，尽管受到测量位置和点数选择的影响。一个值得注意的发现是，在不断变化的环境中，局部皮肤温度对整体热感觉的影响是不同的，局部加热的影响小于冷却。该综述还揭示了热感觉的人口统计学差异，受不同年龄组、性别和气候区域不同皮肤温度的强烈影响。例如，老年人对温度的敏感度下降，尤其是对温暖的敏感度。性别差异也很明显，女性在温暖的环境中皮肤温度较高，而在寒冷的环境中皮肤温度较低。基于机器学习（ML）的方法，特别是那些使用分类树和支持向量机（SVM）技术的方法，越来越多地用于通过利用皮肤温度数据来预测热感觉和舒适度。虽然机器学习方法很普遍，但基于统计回归的方法提供了有价值的经验见解。基于热生理模型的方法通过结合详细的皮肤温度动态提供可靠的结果。这篇综述强调了在理解性别、年龄和地区差异对各种环境中热舒适的影响方面的差距。该研究建议进行更详细的实验，以更密切地检查这些因素的影响。它还建议将个人人口统计变量整合到ML模型中，以个性化热舒适预测。

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引用次数: 0

Using artificial neural networks to predict indoor particulate matter and TVOC concentration in an office building: Model selection and method development 使用人工神经网络预测办公楼的室内颗粒物和 TVOC 浓度：模型选择与方法开发

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-03-04 DOI: 10.1016/j.enbenv.2024.03.001

Saren Gaowa, Zhen Zhang, Jianchun Nie, Linxiao Li, Han A-ru, Zhili Yu

Indoor particulate matter and TVOC pose a significant threat to the health of staff working in office buildings. The accurate prediction of indoor particulate matter and TVOC concentrations is crucial for the automatic operation of ventilation and filtration system to control these indoor pollutants. Artificial neural networks have the advantages of high accuracy, real-time monitoring, and multi-source data integrations. Their performances in predicting particulate matter and TVOC concentrations in office buildings need to be further studied. In this study, on-site sampling was conducted in a typical office building at northern China. A standardized database of indoor parameters for four different offices was created with a total of 6072 datasets for each parameter. Three artificial neural network models were used in this study: the back propagation neural network (BP-ANN), the multi-layer neural network (MLNN), as well as the long-term and short-term memory neural network (LSTM). Among these three models, the performance of the MLNN model was the best in predicting PM_2.5 and PM₁₀ concentrations. It achieved a FB ranging from -0.02 to -0.01, an NMSE ranging from 0.46 to 0.49 μg/m³, and an R² between 0.78 and 0.81. The MLNN model and the random forest (RF) classification method were further used to predict indoor TVOC concentrations. The RF model achieved a relatively better performance with a prediction accuracy of 89.2 %. In addition, the models’ generalization abilities were further evaluated by using some smaller datasets. For the MLNN model, when predicting indoor PM_2.5 concentration, as the amount of training data decreased from 80 % to 20 %, its FB decreased from 0.41 to 0.03, its NMSE changed from 1.53 μg/m³ to 0.53 μg/m³, and its R² decreased from 0.69 to 0.07. The results in this study can contribute to the use of artificial intelligence algorithm in office buildings aiming at indoor pollutants control.

室内颗粒物和挥发性有机化合物对办公大楼工作人员的健康构成重大威胁。准确预测室内颗粒物和TVOC浓度对通风过滤系统的自动运行控制这些室内污染物至关重要。人工神经网络具有精度高、监测实时、多源数据集成等优点。它们在预测办公建筑中颗粒物和TVOC浓度方面的性能有待进一步研究。在本研究中，在中国北方一个典型的办公大楼进行了现场抽样。创建了四个不同办公室室内参数的标准化数据库，每个参数共有6072个数据集。本研究采用了3种人工神经网络模型：BP-ANN（反向传播神经网络）、MLNN（多层神经网络）和LSTM（长短期记忆神经网络）。在3种模型中，MLNN模型对PM2.5和PM10浓度的预测效果最好。结果表明，该方法的净效谱范围为-0.02 ~ -0.01，NMSE范围为0.46 ~ 0.49 μg/m3， R2范围为0.78 ~ 0.81。采用MLNN模型和随机森林（RF）分类方法对室内TVOC浓度进行预测。该模型具有较好的预测效果，预测精度为89.2%。此外，通过使用一些较小的数据集进一步评估了模型的泛化能力。对于MLNN模型，在预测室内PM2.5浓度时，随着训练数据量从80%减少到20%，其FB从0.41下降到0.03，NMSE从1.53 μg/m3下降到0.53 μg/m3， R2从0.69下降到0.07。本研究结果可为人工智能算法在办公大楼室内污染物控制中的应用提供参考。

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引用次数: 0

Geothermal systems classification, coupling, and hybridization: A recent comprehensive review 地热系统分类、耦合和混合：近期全面回顾

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-03-01 DOI: 10.1016/j.enbenv.2024.02.009

Hanan Dokmak , Khaireldin Faraj , Jalal Faraj , Cathy Castelain , Mahmoud Khaled

Fossil fuels have been heavily used to meet the rising global energy demand brought on by population growth, which has resulted in negative environmental effects such pollution, deteriorating air quality, and climate change. Heating, Ventilating, and Air Conditioning (HVAC) systems make up a large amount of this demand. In response, renewable energy sources (RES) have drawn significant attention as a solution to problems brought on by the use of fossil fuels. Notably, geothermal energy stands out as a strong option, providing both heating and cooling needs with special benefits including consistent availability and cost-effective operation. This paper offers a comprehensive short recent review of the geothermal energy landscape, delving into geothermal systems classification, coupling to HVAC and heat recovery systems, geothermal energy piles, and various hybrid systems. Furthermore, the application of nanotechnology to closed geothermal heat pumps, the use of Phase Change Materials (PCM) to stabilise geothermal-powered HVAC systems, and the investigation of energy heaps as a potential alternative energy source are notable studies in this field. This study is unique because it takes a methodical approach to classifying and evaluating various geothermal concepts. It also considers how these concepts are coupled with other systems and hybridized, all of which have a substantial impact on the advancement of geothermal energy approaches.

化石燃料被大量用于满足人口增长带来的全球能源需求，这导致了诸如污染、空气质量恶化和气候变化等负面环境影响。供暖、通风和空调（HVAC）系统占了这一需求的很大一部分。因此，可再生能源（RES）作为解决使用化石燃料带来的问题的一种方法引起了极大的关注。值得注意的是，地热能作为一个强大的选择脱颖而出，它提供了加热和冷却需求的特殊好处，包括持续的可用性和经济高效的操作。本文对地热能景观进行了全面的简要回顾，深入研究了地热能系统的分类、与暖通空调和热回收系统的耦合、地热能桩和各种混合系统。此外，纳米技术在闭式地热热泵中的应用，相变材料（PCM）用于稳定地热驱动的HVAC系统，以及能源堆作为潜在替代能源的研究都是该领域值得关注的研究。这项研究是独一无二的，因为它采用了一种系统的方法来分类和评估各种地热概念。它还考虑了这些概念如何与其他系统相结合和混合，所有这些都对地热能方法的进步产生重大影响。

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引用次数: 0

Heat supply prediction method of a heat pump system based on timing analysis and a neural network 基于时序分析和神经网络的热泵系统供热预测方法研究

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-02-29 DOI: 10.1016/j.enbenv.2024.02.005

Xin Liu , Xiuhui Wu , Jingmeng Sang , Kailiang Huang , Guohui Feng , Mengmeng Song , Xiangdong Wang

The prediction of heat pump system has more complicated characteristics, and the prediction accuracy of the existing single model is not ideal. From the perspective of energy efficiency and energy consumption, it is necessary to improve the accuracy of prediction. A sewage source heat pump system in Shenyang, China, was used as the research object in this paper. The ARIMA model, the BP neural network model, and the ARIMA-BP integrated model, were built. The accuracy of the predicted values of heat supply obtained by the models was verified. The prediction accuracy of the model was verified in extreme weather. The completeness of the model validation was improved. Three prediction models had been applied to the water source heat pump system and the soil source heat pump system. The adaptability and generalization of the model were verified. The number of training sets for heat supply prediction was divided. The number of training sets at the beginning of the heating season was analyzed. The results showed that the mean absolute percentage errors of the ARIMA model, BP neural network model and ARIMA-BP integrated model were 5.37 %, 5.97 % and 3.21 %, respectively. The root mean square errors were 177.31, 186.98, 139.44, respectively. The ARIMA-BP integrated model had a prediction accuracy that improved by 2.16 % compared to the ARIMA model. The ARIMA-BP integrated model had a prediction accuracy that improved by 2.76 % compared to the BP model. In extreme weather, the mean absolute percentage error was 7.83 %, the root mean square error was 296.42. The overall error was also within a reasonable range. The ARIMA-BP integrated model had high prediction accuracy and good applicability and generalization. At the beginning of the heating season, the heat supply can be better predicted when the number of training sets is 4 days.

热泵系统的预测具有较为复杂的特点，现有的单一模型预测精度不理想。从能源效率和能源消耗的角度来看，需要提高预测的准确性。本文以沈阳某污水源热泵系统为研究对象。建立了ARIMA模型、BP神经网络模型和ARIMA-BP集成模型。验证了模型所得到的供热预测值的准确性。在极端天气条件下验证了模型的预测精度。提高了模型验证的完整性。将三种预测模型分别应用于水源热泵系统和土壤源热泵系统。验证了模型的适应性和泛化性。划分供热预测训练集的个数。对采暖季开始时的训练集数量进行了分析。结果表明，ARIMA模型、BP神经网络模型和ARIMA-BP综合模型的平均绝对百分比误差分别为5.37%、5.97%和3.21%。均方根误差分别为177.31、186.98、139.44。与ARIMA模型相比，ARIMA- bp综合模型的预测精度提高了2.16%。ARIMA-BP综合模型的预测精度比BP模型提高了2.76%。在极端天气条件下，平均绝对百分比误差为7.83%，均方根误差为296.42。总体误差也在合理范围内。ARIMA-BP综合模型预测精度高，具有较好的适用性和泛化性。在采暖季开始时，当训练集数为4天时，可以较好地预测供热量。

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引用次数: 0

Experimental study and performance enhancement of micro heat pipe PV/T system 微型热管 PV/T 系统的实验研究与性能提升

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-02-27 DOI: 10.1016/j.enbenv.2024.02.008

Rui Li , Panpan Zhai , Jinping Li , Xiaomin Liu

The integration of photovoltaic/thermal (PV/T) systems, which enable the simultaneous conversion of solar energy into both electricity and thermal energy, holds great promise in the solar-rich northwest region of China. This study aims to assess the performance of a micro heat pipe (MHP) PV/T system through comprehensive experiments conducted over the four seasons in Lanzhou. The experimental setup involved the measurement of various parameters including environmental temperature, surface temperature of the PV/T panel, back temperature of the PV/T panel, and water temperature, as well as the determination of the power collection efficiency (PCE) and thermal conversion efficiency (TCE). The PV/T system was installed at a tilt angle of 45°, resulting in an average PCE of 12.42 % and TCE of 34.7 %. To further understand the system performance, a two-dimensional mathematical model was developed and validated using the experimental data, demonstrating good agreement between the simulated and actual results. The simulation provided valuable insights into the temperature distribution across different components of the PV/T module, such as the glass cover, solar cell, and single shell of the MHP. The findings revealed that increasing the number of MHPs from 12 to 20 led to a modest improvement of 0.21 % and 2.72 % in the PCE and TCE, respectively. Similarly, raising the flow rate from 0.108 L/s to 0.128 L/s resulted in a corresponding increase of 0.25 % and 3.01 % in the PCE and TCE, respectively. These experimental investigations and numerical simulations established a solid scientific foundation and offered practical guidance for the implementation of MHP-PV/T systems, thereby facilitating the efficient utilization of solar energy in future applications.

光伏/热（PV/T）系统的集成，使太阳能能够同时转化为电能和热能，在中国太阳能资源丰富的西北地区具有很大的前景。本研究旨在通过在兰州进行的四季综合试验，对微热管PV/T系统的性能进行评估。实验设置包括环境温度、PV/T面板表面温度、PV/T面板背面温度、水温等参数的测量，以及功率收集效率（PCE）和热转换效率（TCE）的测定。PV/T系统以45°倾角安装，平均PCE为12.42%，TCE为34.7%。为了进一步了解系统性能，建立了二维数学模型，并利用实验数据进行了验证，结果表明仿真结果与实际结果吻合较好。模拟为PV/T组件的不同组件（如玻璃罩、太阳能电池和MHP的单个外壳）之间的温度分布提供了有价值的见解。结果显示，将MHPs的数量从12个增加到20个，PCE和TCE分别有0.21%和2.72%的适度改善。同样，将流量从0.108 L/s提高到0.128 L/s， PCE和TCE分别相应提高了0.25%和3.01%。这些实验研究和数值模拟为MHP-PV/T系统的实现奠定了坚实的科学基础和实践指导，从而促进太阳能在未来应用中的高效利用。

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引用次数: 0

Thermal performances and NOx emission studies on an ammonia-hydrogen fueled double-channel outlet micro-combustor for thermophotovoltaic applications 用于热光电应用的氨氢燃料双通道出口微型燃烧器的热性能和氮氧化物排放研究

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-02-17 DOI: 10.1016/j.enbenv.2024.02.007

Hui Rong , Dan Zhao , Nay Lin Oo , Tao Cai , He Zhao , Dakun Sun , Jingyuan Xu

In this work, we propose and examine an ammonia-hydrogen fueled micro-combustor with a single-channel inlet and double-channel outlet (SIDO). The combustion characteristics and nitrogen oxide emission of ammonia/hydrogen-oxygen premixed combustion are explored. Comparison is then made between the conventional and the proposed SIDO combustors. It is found that our proposed new design could lead to an increase of the outer wall temperature and reduced nitrogen oxide emission. The performances of different hydrogen blended ratios (Φ_b), inlet velocities (V_in), and equivalence ratios (Φ) are evaluated. It is found that increasing Φ_b reduces the maximum flame temperature and the pressure loss, enabling the flame to move upstream. When Φ_b is set to 25 %, the convective heat transfer performance reaches its optimal level. The wall temperature and its uniformity can be improved by increasing V_in. However, it is accompanied by increased NO emissions at the outlet. Increasing Φ can significantly reduce nitrogen oxide emission, and such a reduction effect is much more remarkable at a lower Φ_b. Examining the exergy efficiency is shown to be greatly improved by increasing Φ_b. Increasing Φ could reduce the combustion efficiency of hydrogen in the mixed fuel and have almost no effect on ammonia. This study demonstrates the feasibility of improving thermal performance and reducing emissions by varying its structure for thermophotovoltaic applications.

在这项工作中，我们提出并研究了一种单通道进口和双通道出口（SIDO）的氨氢燃料微燃烧室。探讨了氨/氢氧预混燃烧的燃烧特性和氮氧化物排放。然后对传统燃烧器和拟议的SIDO燃烧器进行了比较。结果表明，本文提出的新设计可以提高外壁温度，减少氮氧化物的排放。对不同混氢比（Φb）、进口速度（Vin）和等效比（Φ）的性能进行了评价。研究发现，增大Φb可降低火焰最高温度和压力损失，使火焰向上游运动。当Φb设置为25%时，对流换热性能达到最佳。提高温度可以提高管壁温度和均匀性。然而，它伴随着出口NO排放量的增加。增加Φ可以显著减少氮氧化物排放，且在Φb较低时，这种减少效果更为显著。研究表明，通过增加Φb，可以大大提高火用效率。增加Φ会降低混合燃料中氢的燃烧效率，对氨几乎没有影响。这项研究证明了通过改变其结构来改善热光伏应用的热性能和减少排放的可行性。

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引用次数: 0

Inverse estimation of the release rate of the heated pollutant source with strong convection and its application to the exhaust system design 强对流加热污染源释放率的逆估算及其在排气系统设计中的应用

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-02-14 DOI: 10.1016/j.enbenv.2024.02.006

Lei Cao , Yi Wang , Yanqiu Huang , Shengnan Guo , Junwei Guo , Yingke Zheng

Accurate release rate of the source is a crucial parameter for the refined design of the exhaust system in the industrial buildings. For the heated pollutant sources emitted by strong convection (SCHP source), it is difficult to accurately measure the source release rate with instruments due to inconsistent emission parameters tested at different locations near the source. In this paper, the three-dimensional CFD (Computational Fluid Dynamics) simulation was used to obtain the hourly concentration of pollutants and to study the applicability of four different regularization methods in the inverse estimation of the release rate of the SCHP source. The influence of the denoising filter and the strong convection of the SCHP source on the accuracy of the inverse estimated source release rate (IESR) was analyzed, and an exhaust flow rate calculation method based on the IESR is proposed. The results show that, compared with the zero-order Tikhonov regularization (ZOTR) and the LSQR methods, the second-order Tikhonov regularization (SOTR) and the truncated SVD (TSVD) methods are more suitable for the inverse estimation of the SCHP source. And it is found that, the introduction of the denoising filter can effectively eliminate the high-frequency or the high-amplitude deviations caused by the regularization method, compared with the SOTR method, the RMSE can be reduced by a maximum of 37.04 %. It is also concluded that the strong convection and the measurement error both have the negative impact on the accuracy of the IESR. Finally, compared to the calculation methods in the existing design manuals, the local exhaust system designed by the IESR method can efficiently capture the pollutants with a 46 % reduction in the exhaust flow rate. This study is useful for the accurately determining the SCHP source release rate and the optimal design of the exhaust system.

准确的辐射源释放率是工业建筑排气系统精细化设计的重要参数。对于强对流热源（SCHP源），由于在源附近不同位置测试的排放参数不一致，难以用仪器准确测量源释放率。本文采用三维CFD （Computational Fluid Dynamics）模拟得到污染物的小时浓度，并研究了四种不同正则化方法在反估SCHP源释放速率中的适用性。分析了消噪滤波器和源强对流对源释放率反演精度的影响，提出了一种基于源释放率反演的排气流量计算方法。结果表明，与零阶Tikhonov正则化（ZOTR）和LSQR方法相比，二阶Tikhonov正则化（SOTR）和截断SVD （TSVD）方法更适合于SCHP源的逆估计。研究发现，引入去噪滤波器可以有效消除正则化方法引起的高频或高幅度偏差，与SOTR方法相比，RMSE最大可降低37.04%。强对流和测量误差都对IESR的精度有负面影响。最后，与现有设计手册中的计算方法相比，采用IESR方法设计的局部排气系统可以有效地捕获污染物，排气流量减少46%。这一研究结果对准确确定SCHP源释放率和排气系统的优化设计具有重要意义。

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引用次数: 0

Operating characteristics and evaluation of air source heat pumps in cold regions during heating season in China 中国寒冷地区采暖季空气源热泵的运行特性与评估

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-02-12 DOI: 10.1016/j.enbenv.2024.02.003

Xin Liu , Qiannan Zhou , Kailiang Huang , Yue Wu , Chuanzhi Liang , Huihong Cao , Jie Wei

The mismatch between the actual heat production of an air source heat pump (ASHP) and the instantaneous load of the building it heats is a critical cause of low energy efficiency. Research on the measured heating effect provides an effective approach to improve the energy efficiency of an ASHP. This study therefore focused on two small office buildings to explore the operating data describing the ASHP system source and load sides during the heating season. A sensitivity analysis was employed to explore the actual operational effects of the ASHP. Common problems associated with system operation were comprehensively identified, including the operation characteristics, energy efficiency coefficients, load characteristics, and energy consumption characteristics of the transmission and distribution systems. The effects of these problems were evaluated from three perspectives: integrated part load value (IPLV), system performance loss, and indoor environmental parameters. The results shows that the highest coefficient of performance (COP) of the ASHP in Building A was 3.27 while the IPLV was 2.68, operating status reached the standard. The COP value of the ASHP in Building B was 1.55 while the IPLV was 2.45. Poor value shows the low performance in operating phase, which can be further optimised by matching the building instantaneous load to the heat production of the ASHP, improves the operating effect of two buildings comprehensively.

空气源热泵（ASHP）的实际产热量与其加热建筑物的瞬时负荷之间的不匹配是导致能源效率低的关键原因。研究实测热效应为提高空气源热泵的能源效率提供了一条有效途径。因此，本研究以两座小型办公楼为研究对象，探讨了在采暖季节描述空气源热泵系统源侧和负荷侧的运行数据。采用敏感性分析探讨空气源热泵的实际运行效果。全面识别了系统运行中常见的问题，包括输配电系统的运行特性、能效系数、负荷特性和能耗特性。从集成部分负载值（IPLV）、系统性能损失和室内环境参数三个方面对这些问题的影响进行了评估。结果表明：A楼空气源热泵的最高性能系数（COP）为3.27，IPLV为2.68，运行状态达到标准。B栋空气源热泵COP值为1.55，IPLV值为2.45。数值较差说明运行阶段性能较差，可通过将建筑瞬时负荷与空气源热泵发热量相匹配进行进一步优化，综合提高两栋建筑的运行效果。

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引用次数: 0

Study on the thermal load of building exterior walls with aerogel slurry insulation under microclimate conditions 小气候条件下使用气凝胶浆料保温的建筑外墙热负荷研究

Q1 Engineering

Energy and Built Environment

Pub Date : 2024-02-09 DOI: 10.1016/j.enbenv.2024.02.002

Wen Yang , Zihan Shi , Guanjie Zhang , Jun Wen

This study aims to address the solubility issue of aerogel particles in water while maintaining their low thermal conductivity properties. To achieve this, different proportions of aerogel slurry were incorporated into coral sand to develop enhanced insulation materials. The goal is to make these materials more economically viable and promote their practical application in various engineering scenarios. This study conducted experiments to measure thermal and moisture performance parameters. The results show that higher aerogel content increases the sensitivity of thermal conductivity to relative humidity. Compared to the dry condition (0% aerogel content), the thermal conductivity difference is minimal (43.5%), while it becomes significant (108.34%) at 32% aerogel content. Regarding wall loads, the largest discrepancy occurs in microclimate heat-humidity conditions during summer and in pure heat transfer conditions under meteorological data during winter. The 32% ASECSC wall experiences the greatest impact from both heat-humidity and urban heat island effects.

本研究旨在解决气凝胶颗粒在水中的溶解度问题，同时保持其低导热性。为了实现这一目标，将不同比例的气凝胶浆掺入珊瑚砂中，以开发增强保温材料。目标是使这些材料在经济上更可行，并促进它们在各种工程场景中的实际应用。本研究通过实验测量了热湿性能参数。结果表明，气凝胶含量越高，导热系数对相对湿度的敏感性越高。与干燥条件下（气凝胶含量为0%）相比，导热系数差异最小（43.5%），而在气凝胶含量为32%时，导热系数差异显著（108.34%）。在墙体荷载方面，夏季小气候热湿条件与冬季气象资料下的纯换热条件差异最大。32%的ASECSC墙体受湿热和城市热岛效应的影响最大。

引用次数: 0