P. Gallagher, Stefan Gunnsteinsson, Alan Morse, M. Gevelber
{"title":"优化商业建筑变风量空调设置以提高能源效率的气流系统识别分析","authors":"P. Gallagher, Stefan Gunnsteinsson, Alan Morse, M. Gevelber","doi":"10.1109/ACC.2015.7170748","DOIUrl":null,"url":null,"abstract":"The paper presents a system identification method that can determine individual room air change rates in commercial building HVAC systems. This is achieved by utilizing a combined low order model based on the room's thermal dynamics and experimental approach. The low order model is shown to capture the dominant dynamics of the room air temperature response. This method can help enable significant building energy use reduction by reassessing the air flow rates needed for each room in a building.","PeriodicalId":223665,"journal":{"name":"2015 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Airflow system identification analysis for optimizing commercial building VAV settings for improved energy efficiency\",\"authors\":\"P. Gallagher, Stefan Gunnsteinsson, Alan Morse, M. Gevelber\",\"doi\":\"10.1109/ACC.2015.7170748\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a system identification method that can determine individual room air change rates in commercial building HVAC systems. This is achieved by utilizing a combined low order model based on the room's thermal dynamics and experimental approach. The low order model is shown to capture the dominant dynamics of the room air temperature response. This method can help enable significant building energy use reduction by reassessing the air flow rates needed for each room in a building.\",\"PeriodicalId\":223665,\"journal\":{\"name\":\"2015 American Control Conference (ACC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 American Control Conference (ACC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACC.2015.7170748\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2015.7170748","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Airflow system identification analysis for optimizing commercial building VAV settings for improved energy efficiency
The paper presents a system identification method that can determine individual room air change rates in commercial building HVAC systems. This is achieved by utilizing a combined low order model based on the room's thermal dynamics and experimental approach. The low order model is shown to capture the dominant dynamics of the room air temperature response. This method can help enable significant building energy use reduction by reassessing the air flow rates needed for each room in a building.