首页> 外文会议>ASME International Mechanical Engineering Congress and Exposition >A CONVENIENT LOW ORDER THERMAL MODEL FOR HEAT TRANSFER CHARACTERISTICS OF SINGLE FLOORED LOW-RISE RESIDENTIAL BUILDINGS
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A CONVENIENT LOW ORDER THERMAL MODEL FOR HEAT TRANSFER CHARACTERISTICS OF SINGLE FLOORED LOW-RISE RESIDENTIAL BUILDINGS

机译:一种方便的低阶热模型,用于单层低层住宅楼的热传递特性

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A low order thermal model is introduced to determine the thermal characteristics of a Low-Rise Residential (LRR) building and then predict the energy usage by its Heating Ventilation & Air Conditioning (HVAC) system according to future weather conditions. The LRR buildings are treated as a simple lump and the model is derived using the lumped capacitance model for transient heat transfer from bodies. Most contemporary HVAC systems have a thermostat control, which has an offset temperature, and user defined set point temperatures, which defines when the HVAC system will switch on and off. The aim is to predict, with minimal error, the inside air temperature, which is used to determine the switching on and off, of the HVAC system. To validate this lumped capacitance model we have used the EnergyPlus simulation engine, which simulates the thermal behavior of buildings with considerable accuracy. We have predicted using the low order model the inside air temperature of a single family house located in three different climate zones (Detroit, Raleigh & Austin) and different orientations for summer and winter seasons. The prediction error between the model and EnergyPlus is less than 10% for almost all the cases with the exception of Austin in summer. Possible factors responsible for error in prediction are also noted in this work, paving way for future research.
机译:低阶热模型被引入到确定的热特性的低层住宅(LRR)构建,然后根据未来的天气条件下通过其供暖通风和空调(HVAC)系统预测的能量使用。 LRR结构建筑物都被视为简单的块,并使用用于从身体的瞬时热传递的集总电容模型推导模型。最现代的HVAC系统有一个恒温器控制,其具有偏移的温度,和用户定义的设置点温度,这定义了当HVAC系统将切换开和关。其目的是预测,以最小的误差,内部空气温度,这被用来确定接通和断开所述开关,所述HVAC系统的。为了验证这一集中电容模型中,我们已经使用了的EnergyPlus仿真引擎,它模拟相当准确建筑物的热性能。我们采用低阶模型位于三个不同气候区(底特律,罗利和奥斯汀)和夏季和冬季不同方向的单一家庭住宅的内部空气温度预测。该模型与EnergyPlus的之间的预测误差小于10%,几乎所有与奥斯汀的夏天异常的情况。负责错误预测的因素可能也注意到了这项工作,为今后的研究铺平了道路。

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