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Comparison between Measured Computer-Predicted Hourly Heating and Cooling Energy Requirements for an Instrumented Wood-Framed Townhouse Subjected to Lab Tests 经过实验室测试的装有仪表的木框架联排别墅的实测计算机预测小时供暖和制冷能源需求之间的比较
随着具有大型内存库的高速计算机的出现,计算受室外天气条件波动、太阳辐射强度变化和内部热量产生变化影响的建筑物每小时热负荷和冷负荷已成为可能。ASHRAE能源需求工作组开发了一套算法(1),用于计算每小时热负荷和冷负荷。它们是在国家标准局和加拿大国家研究委员会的协助下编制的。国家标准局负荷确定程序(NBSLD)(2)是一组利用ASHRAE算法计算任意时间的例行程序- 不同的热负荷和冷负荷或室内温度的变化。NBSLD的使用实际上消除了遗漏建筑物最大负荷的可能性,并使选择供暖和制冷设备的尺寸以匹配建筑物的供暖和制冷负荷成为可能。在使用该计算机程序时,有必要输入室外天气条件、建筑物的施工细节(如逐层描述及其外表面组件的传热面积、方向等),以及设备、照明和占用的建筑物运行计划。 然后,计算机程序的算法对这些输入数据进行运算,从而预测室内空气温度或热负荷和冷负荷。引用:马萨诸塞州波士顿ASHRAE Transactions第81卷第2部分
With the advent of high speed computers with large memory banks, it has become possible to calculate hourly heating and cooling loads for a building as affected by fluctuating outdoor weather conditions, changing solar radiation intensities, and varying internal heat generation to a high degree of sophistication. A set of algorithms (1) has been developed by the ASHRAE Task Group on Energy Requirements for calculating hourly heating and cooling loads. They were prepared with the assistance of the National Bureau of Standards and the National Research Council of Canada.The National Bureau of Standards Load Determination Program (NBSLD) (2) is a group of routines utilizing the ASHRAE algorithms that calculates either time-varying heating and cooling loads or variations of indoor temperature. The use of NBSLD virtually eliminates the possibility of missing the maximum load of a building and makes it possible to select the size of heating and cooling equipment to match the building heating and cooling loads. In using this computer program, it is necessary to provide as input outdoor weather conditions, the construction details of the building (such as a layer-by-layer description and the heat transfer areas of its exterior surface components, its orientation, etc.), and the building operating schedule for equipment, lighting, and occupancy. The algorithms of the computer program then operate on this input data in such a manner as to predict either inside air temperature or heating and cooling loads.
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