期刊
ENERGY AND BUILDINGS
卷 253, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2021.111451
关键词
Condensing Boiler; Natural Gas; Modelica; Building Systems; Space Heating
资金
- Research Foundation-Flanders [FWO.SBO.2017.0003.03]
Despite being considered outdated, gas-fired heating boiler units remain a common source for residential heating energy demand. Current energy performance assessments for residential buildings lack detailed information and a consistent approach. This research aims to determine the necessary level of modeling detail to predict the performance of gas-fired condensing boilers accurately.
Despite being seen as an extinguishing technology, gas-fired heating boiler units are still one of the most common sources for meeting the space heating energy demand of residential dwellings. Current energy performance assessment calculations for residential buildings are often based on insufficient details with thermodynamically ambiguous assumptions and lacking of a consistent approach. However, more detailed methodologies usually require a large set of scarcely available input data which vastly limit the (re)usability of these more refined methods. Following the limited availability of design parameters provided by manufacturers, the goal of this research is to determine the necessary level of the modelling detail to reliably predict the performance of gas-fired condensing boilers. A thermodynamically consis-tent model of a gas-fired condensing boiler unit is developed and discussed through its application in numerical simulations. Calibration is done by using publicly available data and standardised measure-ment points are used for verification of the results. The values of the exhaust gas temperature and flow rate of the formed condensate are available in the standardised experimental reports of these units. This work suggests that these values should be included in public documents given by the manufactures. (c) 2021 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据