基于极端天气数据模型预测完全由环境能源调节的建筑物性能

M. K. Sharp
{"title":"基于极端天气数据模型预测完全由环境能源调节的建筑物性能","authors":"M. K. Sharp","doi":"10.1115/1.4065155","DOIUrl":null,"url":null,"abstract":"\n This study reports the development of extreme meteorological year (XMY) data for simulating buildings that are heated and cooled entirely by ambient energy in four climates varying in outdoor temperature and cloudiness. Electrification of conventional buildings is insufficient to meet climate goals, since nearly half of US electricity will still be produced from fossil fuels by 2050. Ambient-conditioned buildings depend on non-fossil sources such as the sun for heating, and nighttime air or sky radiation for cooling. Such buildings are more susceptible to weather variability than conventional buildings, which simply use more auxiliary energy whenever weather conditions are challenging. On the other hand, ambient-conditioned buildings are more resilient to power outages so long as the design accounts for unusual weather during extreme years to consistently maintain indoor comfort. Ambient-conditioned buildings designed to remain comfortable with typical meteorological year (TMY2020) data produced up to over 1000 hours per year of uncomfortable indoor temperature during the years (1998–2020) from which the TMY was derived. Parameters related to outdoor air temperature, sky temperature and insolation were found to be unreliable for identifying the most challenging years. Rather, a whole-building model allowed identification of the two most challenging years for heating and cooling, respectively. An XMY file concatenated from the most challenging summer and the most challenging winter provided a good match of indoor temperature predictions to those from the full, individual years. This new XMY file facilitates the design of ambient-conditioned buildings for reliable indoor comfort.","PeriodicalId":326594,"journal":{"name":"ASME Journal of Engineering for Sustainable Buildings and Cities","volume":" 38","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Model-based extreme weather data for predicting the performance of buildings entirely conditioned by ambient energy\",\"authors\":\"M. K. Sharp\",\"doi\":\"10.1115/1.4065155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n This study reports the development of extreme meteorological year (XMY) data for simulating buildings that are heated and cooled entirely by ambient energy in four climates varying in outdoor temperature and cloudiness. Electrification of conventional buildings is insufficient to meet climate goals, since nearly half of US electricity will still be produced from fossil fuels by 2050. Ambient-conditioned buildings depend on non-fossil sources such as the sun for heating, and nighttime air or sky radiation for cooling. Such buildings are more susceptible to weather variability than conventional buildings, which simply use more auxiliary energy whenever weather conditions are challenging. On the other hand, ambient-conditioned buildings are more resilient to power outages so long as the design accounts for unusual weather during extreme years to consistently maintain indoor comfort. Ambient-conditioned buildings designed to remain comfortable with typical meteorological year (TMY2020) data produced up to over 1000 hours per year of uncomfortable indoor temperature during the years (1998–2020) from which the TMY was derived. Parameters related to outdoor air temperature, sky temperature and insolation were found to be unreliable for identifying the most challenging years. Rather, a whole-building model allowed identification of the two most challenging years for heating and cooling, respectively. An XMY file concatenated from the most challenging summer and the most challenging winter provided a good match of indoor temperature predictions to those from the full, individual years. This new XMY file facilitates the design of ambient-conditioned buildings for reliable indoor comfort.\",\"PeriodicalId\":326594,\"journal\":{\"name\":\"ASME Journal of Engineering for Sustainable Buildings and Cities\",\"volume\":\" 38\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ASME Journal of Engineering for Sustainable Buildings and Cities\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4065155\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASME Journal of Engineering for Sustainable Buildings and Cities","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4065155","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究报告了极端气象年(XMY)数据的开发情况,用于模拟在室外温度和云量不同的四种气候条件下完全依靠环境能源供暖和制冷的建筑物。传统建筑电气化不足以实现气候目标,因为到 2050 年,美国近一半的电力仍将来自化石燃料。环境调节型建筑依靠非化石能源,如太阳取暖和夜间空气或天空辐射制冷。与传统建筑相比,这类建筑更容易受到天气变化的影响,因为传统建筑只需在天气条件恶劣时使用更多的辅助能源。另一方面,环境调节型建筑更能抵御停电的影响,只要在设计时考虑到极端年份的异常天气,就能始终保持室内的舒适度。根据典型气象年(TMY2020)数据设计的常温空调建筑,在典型气象年得出的年份(1998-2020 年)中,每年有多达 1000 多个小时的室内温度不舒适。与室外气温、天空温度和日照有关的参数对于确定最具挑战性的年份并不可靠。相反,通过整个建筑物模型,可以分别确定供暖和制冷两个最具挑战性的年份。由最具挑战性的夏季和最具挑战性的冬季连接而成的 XMY 文件与完整的单独年份的室内温度预测结果非常吻合。这种新的 XMY 文件有助于设计环境调节型建筑,从而获得可靠的室内舒适度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Model-based extreme weather data for predicting the performance of buildings entirely conditioned by ambient energy
This study reports the development of extreme meteorological year (XMY) data for simulating buildings that are heated and cooled entirely by ambient energy in four climates varying in outdoor temperature and cloudiness. Electrification of conventional buildings is insufficient to meet climate goals, since nearly half of US electricity will still be produced from fossil fuels by 2050. Ambient-conditioned buildings depend on non-fossil sources such as the sun for heating, and nighttime air or sky radiation for cooling. Such buildings are more susceptible to weather variability than conventional buildings, which simply use more auxiliary energy whenever weather conditions are challenging. On the other hand, ambient-conditioned buildings are more resilient to power outages so long as the design accounts for unusual weather during extreme years to consistently maintain indoor comfort. Ambient-conditioned buildings designed to remain comfortable with typical meteorological year (TMY2020) data produced up to over 1000 hours per year of uncomfortable indoor temperature during the years (1998–2020) from which the TMY was derived. Parameters related to outdoor air temperature, sky temperature and insolation were found to be unreliable for identifying the most challenging years. Rather, a whole-building model allowed identification of the two most challenging years for heating and cooling, respectively. An XMY file concatenated from the most challenging summer and the most challenging winter provided a good match of indoor temperature predictions to those from the full, individual years. This new XMY file facilitates the design of ambient-conditioned buildings for reliable indoor comfort.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Impact of Building Design and Operating Strategies on Urban Heat Island Effects Part II: Sensitivity Analysis ASSESSING ENERGY SAVINGS: A COMPARATIVE STUDY OF REFLECTIVE ROOF COATINGS IN FOUR USA CLIMATE ZONES AN ELEMENTARY APPROACH TO EVALUATING THE THERMAL SELF-SUFFICIENCY OF RESIDENTIAL BUILDINGS WITH THERMAL ENERGY STORAGE A PROPOSED METHOD AND CASE STUDY OF WASTE HEAT RECOVERY IN AN INDUSTRIAL APPLICATION Impact of Building Operating Strategies on Urban Heat Island Effects Part I: Model Development and Validation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1