Pub Date : 2024-10-24DOI: 10.1016/j.enbuild.2024.114943
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.
{"title":"Experimental study and simulation of a solid desiccant cooling system installed in northern Algeria","authors":"","doi":"10.1016/j.enbuild.2024.114943","DOIUrl":"10.1016/j.enbuild.2024.114943","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.enbuild.2024.114945
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.
{"title":"Optimal scheduling strategy of household electrical equipment based on scenario dynamic modeling","authors":"","doi":"10.1016/j.enbuild.2024.114945","DOIUrl":"10.1016/j.enbuild.2024.114945","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.enbuild.2024.114948
Building energy models were widely used in building energy performance analysis and efficiency improvement, such as building demand response assessment and energy system optimization. However, building energy modeling was a time-consuming and complex process. Therefore, this paper proposed a hybrid building energy modeling method based on parameterized prototype models and rapid calibration. The main feature of the method was the rapid generation of target building energy models using the prototype building energy performance database. The parameterized prototype building energy model considered 13 uncertainty parameters. Based on the range of 13 uncertainty parameters, such as wall U-value and solar heat gain coefficient, 1000 simulations were performed by Monte Carlo sampling to generate the prototype building energy performance database. The target building energy model was quickly calibrated by learning from this database. It filtered the models that met the requirements based on the actual building measurement data. Based on this hybrid modeling method, the rapid modeling tool AutoBPS-Hybrid was developed in a ruby environment. Shopping mall buildings located in three different climate zones were selected as case studies for this study. The results showed that if only one building energy model meeting the percentage errors was needed, only 3–4 simulations were required. If it was necessary to match the real uncertainty parameter distributions, an average of about 53 simulations was needed. The building energy models were applied to plug load and lighting control in buildings. The shopping mall buildings in Harbin, Beijing and Chengdu could reduce energy consumption by 10.18–13.33 kWh/m2, 14.43–18.15 kWh/m2 and 11.54–14.69 kWh/m2 per year, respectively.
{"title":"Hybrid building energy modeling method with parameterized prototype models and rapid calibration","authors":"","doi":"10.1016/j.enbuild.2024.114948","DOIUrl":"10.1016/j.enbuild.2024.114948","url":null,"abstract":"<div><div>Building energy models were widely used in building energy performance analysis and efficiency improvement, such as building demand response assessment and energy system optimization. However, building energy modeling was a time-consuming and complex process. Therefore, this paper proposed a hybrid building energy modeling method based on parameterized prototype models and rapid calibration. The main feature of the method was the rapid generation of target building energy models using the prototype building energy performance database. The parameterized prototype building energy model considered 13 uncertainty parameters. Based on the range of 13 uncertainty parameters, such as wall U-value and solar heat gain coefficient, 1000 simulations were performed by Monte Carlo sampling to generate the prototype building energy performance database. The target building energy model was quickly calibrated by learning from this database. It filtered the models that met the requirements based on the actual building measurement data. Based on this hybrid modeling method, the rapid modeling tool AutoBPS-Hybrid was developed in a ruby environment. Shopping mall buildings located in three different climate zones were selected as case studies for this study. The results showed that if only one building energy model meeting the percentage errors was needed, only 3–4 simulations were required. If it was necessary to match the real uncertainty parameter distributions, an average of about 53 simulations was needed. The building energy models were applied to plug load and lighting control in buildings. The shopping mall buildings in Harbin, Beijing and Chengdu could reduce energy consumption by 10.18–13.33 kWh/m<sup>2</sup>, 14.43–18.15 kWh/m<sup>2</sup> and 11.54–14.69 kWh/m<sup>2</sup> per year, respectively.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.enbuild.2024.114953
The increment of photovoltaic generation in smart buildings and energy communities makes the use of energy storage systems desired to increase the self-consumption efficiency. This paper proposes and explores a model for energy storage systems management that considers local renewable generation, local demand, and retailer energy prices. The proposed model was tested at both energy community-level and the smart building level, demonstrating their capabilities of deployment. To validate the proposed model, a case study with two scenarios, including a 251 members energy community, was executed. The results demonstrate significant cost reductions for community members when adopting energy storage systems and the proposed management model. Regarding the smart building application four scenarios were tested, it is demonstrated that the demand for energy from the retailer could be set to zero during periods of time to enable its participation in demand response events. Overall, this paper contributes to the state-of-the-art by identifying and evaluating a model that manages the energy storage systems charge and discharge operation to actively reduce energy costs at the community-level (19.26%) and building level (11.75%) and to demonstrate that part of the loads can be optimized to understand if the building can be energy net-zero.
{"title":"Empowering energy management in smart buildings: A comprehensive study on distributed energy storage systems for Sustainable consumption","authors":"","doi":"10.1016/j.enbuild.2024.114953","DOIUrl":"10.1016/j.enbuild.2024.114953","url":null,"abstract":"<div><div>The increment of photovoltaic generation in smart buildings and energy communities makes the use of energy storage systems desired to increase the self-consumption efficiency. This paper proposes and explores a model for energy storage systems management that considers local renewable generation, local demand, and retailer energy prices. The proposed model was tested at both energy community-level and the smart building level, demonstrating their capabilities of deployment. To validate the proposed model, a case study with two scenarios, including a 251 members energy community, was executed. The results demonstrate significant cost reductions for community members when adopting energy storage systems and the proposed management model. Regarding the smart building application four scenarios were tested, it is demonstrated that the demand for energy from the retailer could be set to zero during periods of time to enable its participation in demand response events. Overall, this paper contributes to the state-of-the-art by identifying and evaluating a model that manages the energy storage systems charge and discharge operation to actively reduce energy costs at the community-level (19.26%) and building level (11.75%) and to demonstrate that part of the loads can be optimized to understand if the building can be energy net-zero.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-24DOI: 10.1016/j.enbuild.2024.114936
Decarbonising the built environment is essential for achieving the 2050 European objectives. Multi-family buildings comprise nearly half of Europe’s building stock, yet there is no regulation mandating all housing renovations to be Nearly Zero-Energy Buildings (NZEBs). This paper highlights the role of NZEB renovation for residential buildings constructed between the first energy regulations, after the first oil crisis, and the EPBD 2002 implementation (post-first-energy-regulation housing), as a pivotal factor towards energy transition. In Spain, this period (1980–2006) encompasses approximately 45% of existing dwellings. A case study was conducted in a city with a Cfb temperate climate, focusing on the most representative residential typology of the target period: the linear block. The study evaluates its current state and defines potential measures to meet NZEB requirements, achieving zero consumption when renovation of thermal envelope is combined with heat recovery systems, heat pumps, and PV panels.
This research is based on energy simulations for two climate scenarios: the typical meteorological year (TMY, official series 1970–2000) and the most extreme warm year (EWY, 2022) in Spain. Results indicate active cooling systems are necessary for NZEB renovations in Spanish Cfb climates. Furthermore, low-temperature radiators significantly reduce heating consumption, while splits are the most suitable cooling systems. This study shows Spain is not adequately preparing its housing stock to face climate change, as most typical renovation works are based on official weather files that need updating to reflect harsher summer conditions. Finally, the study aims to encourage new policies and enhance existing regulations to address rising temperatures and heatwaves.
{"title":"Renovating Post-First-Energy-Regulation Housing: Achieving Nearly Zero-Energy buildings under typical and extreme warm conditions in a temperate European city","authors":"","doi":"10.1016/j.enbuild.2024.114936","DOIUrl":"10.1016/j.enbuild.2024.114936","url":null,"abstract":"<div><div>Decarbonising the built environment is essential for achieving the 2050 European objectives. Multi-family buildings comprise nearly half of Europe’s building stock, yet there is no regulation mandating all housing renovations to be Nearly Zero-Energy Buildings (NZEBs). This paper highlights the role of NZEB renovation for residential buildings constructed between the first energy regulations, after the first oil crisis, and the EPBD 2002 implementation (post-first-energy-regulation housing), as a pivotal factor towards energy transition. In Spain, this period (1980–2006) encompasses approximately 45% of existing dwellings. A case study was conducted in a city with a <em>Cfb</em> temperate climate, focusing on the most representative residential typology of the target period: the linear block. The study evaluates its current state and defines potential measures to meet NZEB requirements, achieving zero consumption when renovation of thermal envelope is combined with heat recovery systems, heat pumps, and PV panels.</div><div>This research is based on energy simulations for two climate scenarios: the typical meteorological year (TMY, official series 1970–2000) and the most extreme warm year (EWY, 2022) in Spain. Results indicate active cooling systems are necessary for NZEB renovations in Spanish <em>Cfb</em> climates. Furthermore, low-temperature radiators significantly reduce heating consumption, while splits are the most suitable cooling systems. This study shows Spain is not adequately preparing its housing stock to face climate change, as most typical renovation works are based on official weather files that need updating to reflect harsher summer conditions. Finally, the study aims to encourage new policies and enhance existing regulations to address rising temperatures and heatwaves.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.enbuild.2024.114929
Renewable energy sources facilitate decentralized electricity production, reducing dependence on fossil fuels and contributing to a sustainable energy era. Algeria is one of the countries implementing a policy aimed at energy transition, with buildings playing a major role in this process. They consume more energy than any other sector and therefore significantly contribute to climate change. While various projects related to energy efficiency are being carried out, they are mostly limited to rural and Saharan areas or low-consumption residential buildings. The objective of this paper is to demonstrate the feasibility of integrating a grid-connected photovoltaic system into a medium-consumption building located in one of Algeria’s major cities, Constantine, to meet the building’s electrical energy demand. This paper presents a methodology for optimally sizing a grid-connected photovoltaic system to supply power to the Institute of Nutrition, Food, and Agro-Food Technologies (INATAA) in Constantine, Algeria. The technical and economic aspects of the system’s components were considered to determine the most feasible configuration, using real data from the institute and the HOMER Pro simulation software. The simulation results show that the grid-connected PV system, without storage, can meet the institute’s energy demand (with 671,061 kWh/year of energy produced, of which 81.3 % is photovoltaic energy). This configuration offers the lowest costs, with a Net Present Cost (NPC) of $748,413 and a Cost of Energy (COE) of $0.0894/kWh. Therefore, integration of a grid-connected photovoltaic system in medium-consumption buildings can effectively meet energy needs while reducing costs. Thus, this study demonstrates the technical and economic feasibility of such system to support the energy transition in urban areas in Algeria.
可再生能源有利于分散式发电,减少对化石燃料的依赖,有助于实现可持续能源时代。阿尔及利亚是实施能源转型政策的国家之一,建筑物在这一进程中发挥着重要作 用。建筑消耗的能源比任何其他部门都多,因此对气候变化的影响很大。虽然目前正在开展各种与能源效率有关的项目,但它们大多局限于农村和撒哈拉地区或低耗能的住宅建筑。本文旨在论证将并网光伏系统集成到位于阿尔及利亚主要城市之一君士坦丁的一栋中等能耗建筑的可行性,以满足该建筑的电能需求。本文介绍了一种优化并网光伏系统规模的方法,以向阿尔及利亚君士坦丁市的营养、食品和农产品技术研究所(INATAA)供电。利用该研究所的真实数据和 HOMER Pro 仿真软件,考虑了系统组件的技术和经济方面,以确定最可行的配置。模拟结果表明,并网光伏系统在没有储能的情况下,可以满足研究所的能源需求(年发电量为 671,061 千瓦时,其中 81.3% 为光伏发电)。这种配置的成本最低,净现值成本 (NPC) 为 748,413 美元,能源成本 (COE) 为 0.0894 美元/千瓦时。因此,在中等能耗建筑中集成并网光伏系统可以有效满足能源需求,同时降低成本。因此,这项研究证明了这种系统在支持阿尔及利亚城市地区能源转型方面的技术和经济可行性。
{"title":"Implementing of a grid-connected PV energy system in building with medium consumption: A techno- economic case study","authors":"","doi":"10.1016/j.enbuild.2024.114929","DOIUrl":"10.1016/j.enbuild.2024.114929","url":null,"abstract":"<div><div>Renewable energy sources facilitate decentralized electricity production, reducing dependence on fossil fuels and contributing to a sustainable energy era. Algeria is one of the countries implementing a policy aimed at energy transition, with buildings playing a major role in this process. They consume more energy than any other sector and therefore significantly contribute to climate change. While various projects related to energy efficiency are being carried out, they are mostly limited to rural and Saharan areas or low-consumption residential buildings. The objective of this paper is to demonstrate the feasibility of integrating a grid-connected photovoltaic system into a medium-consumption building located in one of Algeria’s major cities, Constantine, to meet the building’s electrical energy demand. This paper presents a methodology for optimally sizing a grid-connected photovoltaic system to supply power to the Institute of Nutrition, Food, and Agro-Food Technologies (INATAA) in Constantine, Algeria. The technical and economic aspects of the system’s components were considered to determine the most feasible configuration, using real data from the institute and the HOMER Pro simulation software. The simulation results show that the grid-connected PV system, without storage, can meet the institute’s energy demand (with 671,061 kWh/year of energy produced, of which 81.3 % is photovoltaic energy). This configuration offers the lowest costs, with a Net Present Cost (NPC) of $748,413 and a Cost of Energy (COE) of $0.0894/kWh. Therefore, integration of a grid-connected photovoltaic system in medium-consumption buildings can effectively meet energy needs while reducing costs. Thus, this study demonstrates the technical and economic feasibility of such system to support the energy transition in urban areas in Algeria.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.enbuild.2024.114940
With a high share of renewable energy in the power grid, it becomes increasingly difficult to ensure a continuous balance between power generation and consumption, thereby endangering grid stability. A substantial opportunity to address this challenge and align the heating demand with intermittent power production is offered by space heating and domestic hot water, which account for 80% of the energy consumption in buildings. Further research on the control of building clusters is required, where peak load management of multiple buildings can ensure grid stability during peak hours and contribute to avoiding power outages. In this paper, a rule-based controller is presented, called Extended Price Storage Control+ (EPSC+), for the practical and flexible operation of heating systems in a building cluster. Under dynamic pricing, the loads of electric heating devices for the provision of space heating and domestic hot water are shifted by EPSC+ while accounting for peak load constraints. The performance of EPSC+ is evaluated in a nine-week winter simulation study with a building cluster of ten buildings in Germany. For comparison, a hierarchical model predictive controller (MPC) and a hysteresis two-point controller are employed as benchmarks. Results close to those of MPC are achieved by EPSC+by reducing the median peak load by 38.8% and median electricity costs by 15% compared with the hysteresis controller. In contrast to MPC, EPSC+ does not require models, forecasts, or optimization and is computationally inexpensive, rendering it more attainable for real-world implementation.
{"title":"Coordinated price-based control of modulating heat pumps for practical demand response and peak shaving in building clusters","authors":"","doi":"10.1016/j.enbuild.2024.114940","DOIUrl":"10.1016/j.enbuild.2024.114940","url":null,"abstract":"<div><div>With a high share of renewable energy in the power grid, it becomes increasingly difficult to ensure a continuous balance between power generation and consumption, thereby endangering grid stability. A substantial opportunity to address this challenge and align the heating demand with intermittent power production is offered by space heating and domestic hot water, which account for 80% of the energy consumption in buildings. Further research on the control of building clusters is required, where peak load management of multiple buildings can ensure grid stability during peak hours and contribute to avoiding power outages. In this paper, a rule-based controller is presented, called Extended Price Storage Control+ (EPSC+), for the practical and flexible operation of heating systems in a building cluster. Under dynamic pricing, the loads of electric heating devices for the provision of space heating and domestic hot water are shifted by EPSC+ while accounting for peak load constraints. The performance of EPSC+ is evaluated in a nine-week winter simulation study with a building cluster of ten buildings in Germany. For comparison, a hierarchical model predictive controller (MPC) and a hysteresis two-point controller are employed as benchmarks. Results close to those of MPC are achieved by EPSC+by reducing the median peak load by 38.8% and median electricity costs by 15% compared with the hysteresis controller. In contrast to MPC, EPSC+ does not require models, forecasts, or optimization and is computationally inexpensive, rendering it more attainable for real-world implementation.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1016/j.enbuild.2024.114947
Building energy consumption in the severe cold regions of China is an important consideration in building energy conservation because of the high amount of energy consumed by heating. As an important thermal parameter, the thermal transmittance (U-value) of building envelopes can directly affect the operational energy consumption of buildings. Understanding the U-values of buildings in severe cold regions is important to predict building energy accurately. However, the U-values of envelopes fluctuate constantly due to environmental impacts. Therefore, this study aimed to examine the influence of dynamic U-values on building energy efficiency. To achieve this, this study focused on the in-situ measurement of the U-values of two typical building envelopes in Harbin from winter to summer in 2023 to determine the average and dynamic U-values of the tested envelope, comprising a brick envelope and reinforced concrete (RC) envelope. The building energy simulation results based on theoretical U-values were compared with the measured average and dynamic U-values of the tested envelopes. The findings revealed that the fluctuations in the U-values were significant. In the dynamic U-values of tested brick and RC envelopes, the U-values in winter were 159.8% and 30.8% higher than those in summer, respectively. Furthermore, the dynamic U-values significantly influenced heating energy consumption, with an increase of up to 15.9%.
在中国严寒地区,由于采暖能耗较高,建筑能耗是建筑节能的一个重要考虑因素。作为一项重要的热工参数,建筑围护结构的热导率(U 值)会直接影响建筑的运行能耗。了解严寒地区建筑的 U 值对于准确预测建筑能耗非常重要。然而,由于环境影响,围护结构的 U 值会不断波动。因此,本研究旨在探讨动态 U 值对建筑能效的影响。为此,本研究重点对 2023 年哈尔滨市两种典型建筑围护结构从冬季到夏季的 U 值进行了现场测量,以确定测试围护结构(包括砖围护结构和钢筋混凝土(RC)围护结构)的平均 U 值和动态 U 值。基于理论 U 值的建筑能耗模拟结果与测试围护结构的实测平均 U 值和动态 U 值进行了比较。研究结果表明,U 值的波动非常明显。在测试的砖砌围护结构和 RC 围护结构的动态 U 值中,冬季的 U 值分别比夏季高出 159.8% 和 30.8%。此外,动态 U 值对采暖能耗也有很大影响,最多可增加 15.9%。
{"title":"In-situ U-value measurements of typical building envelopes in a severe cold region of China: U-value variations and energy Implications","authors":"","doi":"10.1016/j.enbuild.2024.114947","DOIUrl":"10.1016/j.enbuild.2024.114947","url":null,"abstract":"<div><div>Building energy consumption in the severe cold regions of China is an important consideration in building energy conservation because of the high amount of energy consumed by heating. As an important thermal parameter, the thermal transmittance (U-value) of building envelopes can directly affect the operational energy consumption of buildings. Understanding the U-values of buildings in severe cold regions is important to predict building energy accurately. However, the U-values of envelopes fluctuate constantly due to environmental impacts. Therefore, this study aimed to examine the influence of dynamic U-values on building energy efficiency. To achieve this, this study focused on the in-situ measurement of the U-values of two typical building envelopes in Harbin from winter to summer in 2023 to determine the average and dynamic U-values of the tested envelope, comprising a brick envelope and reinforced concrete (RC) envelope. The building energy simulation results based on theoretical U-values were compared with the measured average and dynamic U-values of the tested envelopes. The findings revealed that the fluctuations in the U-values were significant. In the dynamic U-values of tested brick and RC envelopes, the U-values in winter were 159.8% and 30.8% higher than those in summer, respectively. Furthermore, the dynamic U-values significantly influenced heating energy consumption, with an increase of up to 15.9%.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1016/j.enbuild.2024.114934
On the path to energy transition, advanced metering infrastructures have been installed in distribution systems to support sustainability goals, generating a substantial volume of electricity consumption data that are essential for planning and management studies. Additionally, given the stochastic nature of electricity consumption, understanding and quantifying statistical properties such as data distribution, normality, stationarity, and autocorrelation are crucial for the development of more sustainable systems and the enhancement of building performance. In this context, this paper presents a statistical methodology for assessing key aspects of electricity consumption in buildings on a smart campus, which is an initiative originated on university campuses that integrates sustainable energy systems, efficient electrical infrastructure, and data-driven technologies to establish a sustainable learning environment. Using 28 months of electricity consumption data from a Brazilian smart campus, Electricity Use Profile models are developed and several hypothesis tests and probability distribution fittings are conducted to extract statistical features from the models of 128 buildings. The results indicate that each building exhibits unique statistical properties that cannot be generalized, emphasizing the need for data analysis for each building before using the data in decision-making processes.
{"title":"Statistical characterization of electricity use profile: Leveraging data analytics for stochastic simulation in a smart campus","authors":"","doi":"10.1016/j.enbuild.2024.114934","DOIUrl":"10.1016/j.enbuild.2024.114934","url":null,"abstract":"<div><div>On the path to energy transition, advanced metering infrastructures have been installed in distribution systems to support sustainability goals, generating a substantial volume of electricity consumption data that are essential for planning and management studies. Additionally, given the stochastic nature of electricity consumption, understanding and quantifying statistical properties such as data distribution, normality, stationarity, and autocorrelation are crucial for the development of more sustainable systems and the enhancement of building performance. In this context, this paper presents a statistical methodology for assessing key aspects of electricity consumption in buildings on a smart campus, which is an initiative originated on university campuses that integrates sustainable energy systems, efficient electrical infrastructure, and data-driven technologies to establish a sustainable learning environment. Using 28 months of electricity consumption data from a Brazilian smart campus, Electricity Use Profile models are developed and several hypothesis tests and probability distribution fittings are conducted to extract statistical features from the models of 128 buildings. The results indicate that each building exhibits unique statistical properties that cannot be generalized, emphasizing the need for data analysis for each building before using the data in decision-making processes.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1016/j.enbuild.2024.114944
Existing ventilation technologies often struggle to balance the limited airflow supply with the demands of indoor ventilation and air circulation in winter. This paper introduces a novel ventilation method, vertical single-row inclined slit ventilation (VSISV), which channels airflow through multiple inclined slits spaced at specific intervals along a vertical supply air duct. By ensuring continuity of the upstream and downstream slit jets, a continuous downward airflow is formed, enhancing both winter ventilation performance and indoor air circulation. The method was experimentally measured, with a focus on comparison to the IJV system. At the same airflow rate, it not only efficiently transports the supply air heat from the upper indoor area to the floor but also exhibits strong horizontal diffusion capability. The RNG turbulence model was selected for numerical simulation, focusing on indoor thermal comfort, air quality, and energy-saving potential. The results indicate that, at the same airflow rate, this method effectively maintains high indoor thermal comfort, directs airflow downward from the ceiling, reduces thermal stratification in the upper zone, achieves a more uniform and elevated indoor temperature, enhances indoor air quality, and demonstrates substantial energy-saving potential. This provides valuable insights for energy conservation, emission reduction, and the optimization in winter building ventilation systems.
{"title":"A novel ventilation method: Experimental measurement and numerical simulation of vertical single-row inclined slit ventilation","authors":"","doi":"10.1016/j.enbuild.2024.114944","DOIUrl":"10.1016/j.enbuild.2024.114944","url":null,"abstract":"<div><div>Existing ventilation technologies often struggle to balance the limited airflow supply with the demands of indoor ventilation and air circulation in winter. This paper introduces a novel ventilation method, vertical single-row inclined slit ventilation (VSISV), which channels airflow through multiple inclined slits spaced at specific intervals along a vertical supply air duct. By ensuring continuity of the upstream and downstream slit jets, a continuous downward airflow is formed, enhancing both winter ventilation performance and indoor air circulation. The method was experimentally measured, with a focus on comparison to the IJV system. At the same airflow rate, it not only efficiently transports the supply air heat from the upper indoor area to the floor but also exhibits strong horizontal diffusion capability. The RNG turbulence model was selected for numerical simulation, focusing on indoor thermal comfort, air quality, and energy-saving potential. The results indicate that, at the same airflow rate, this method effectively maintains high indoor thermal comfort, directs airflow downward from the ceiling, reduces thermal stratification in the upper zone, achieves a more uniform and elevated indoor temperature, enhances indoor air quality, and demonstrates substantial energy-saving potential. This provides valuable insights for energy conservation, emission reduction, and the optimization in winter building ventilation systems.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":null,"pages":null},"PeriodicalIF":6.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}