介绍了瑞尔森大学（RU）86%校园建筑能耗的建模与仿真。为瑞尔森大学的16座主要建筑开发了能量模拟模型。商用软件用于预测能源使用。在建模和仿真中，考虑了建筑物中所有可能的能源来源和使用。模拟结果表明，26%的总能量用于照明，19%的总能量用于插头负载，4%的总能量用于其他设备。其余51%的能源用于取暖、通风和通风- 空调（HVAC）系统。此外，普林斯顿记分法（Princeton Scoreserving method，PRISM）是节能研究中常用的方法，已被用于分析相同的RU建筑，以进行比较和验证。将基本案例模拟结果和普林斯顿记分法的结果与校园规划中瑞尔森校园的电力、蒸汽和深湖水冷却（DLWC）需求的实际使用账单进行了比较。模拟结果预测用电量低5.7%，蒸汽消耗低6.3%，而普林斯顿记分法预测用电量低2%。 7%，蒸汽消耗量预测过高6%。Ryerson校区86%的总面积的平均能量强度为1.04 GJ/m²（91576 Btu/ft²）。灵敏度分析是通过（1）增加热回收系统和（2）减少照明计划进行的。因此，前一种分析预测冷负荷和热负荷的年节能率分别为5.6%和76%，而后一种分析预测冷负荷和电力需求的年节能率分别为10%和21%，而热负荷则增加了14%。引文:2015年年度会议，佐治亚州亚特兰大，2015年交易，第121卷。 2

Modeling and simulation of energy consumption in 86%of the Ryerson University (RU) campus buildings is presented.Energy simulation models were developed for 16 major RyersonUniversity buildings. Commercially available softwarewas used for the prediction of energy use. All of the possiblesources and uses of energy in the buildings were accounted forin the modeling and simulation. Simulation result showed that26% of total energy was used by lighting, 19% of total energyused by plug load, and 4% of total energy was used by miscellaneousequipment. The remaining 51% of energy use was forheating, ventilation and air-conditioning (HVAC) systems. Inaddition, the Princeton scorekeeping method (PRISM), awidely used method in energy conservation studies, has beenused to analyze the same RU buildings for comparison andverification.The base case simulation result and the Princeton scorekeepingmethod result were compared with the Campus Planningactual use bills for electricity, steam and deep lake watercooling (DLWC) demand for the Ryerson campus. The simulationresult underpredicted electricity use by 5.7% and steamconsumption by 6.3%, while the Princeton scorekeepingmethod underpredicted electricity use by 2.7%, and overpredictedsteam consumption by 6%.The average energy intensitywas determined as 1.04 GJ/m2(91,576 Btu/ft2) for the 86% ofthe total area of Ryerson campus. Sensitivity analysis wasconducted by (1) adding a heat recovery system and (2) reducinglighting schedule.As a result, the former analysis predictedan annual energy saving of 5.6% for cooling load and 76% forthe heating load, while the latter analysis predicted an annualenergy savings of 10% for cooling load and 21% for electricitydemand, while the heating load increased by 14%.