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1. 发明申请

WO2009064111A2 METHOD FOR PREDICTING COOLING LOAD 审中-公开
标题翻译：预测冷却负荷的方法
公开(公告)号：WO2009064111A2
公开(公告)日：2009-05-22
申请号：PCT/KR2008006668
申请日：2008-11-12
申请人： IAC IN NAT UNIV CHUNGNAM , GAGYOTECH CO LTD , YOO SEONG-YEON , LEE JE-MYO , HAN KYU-HYUN
发明人： YOO SEONG-YEON , LEE JE-MYO , HAN KYU-HYUN
IPC分类号： F24F11/02
CPC分类号： F24F11/30 , F24F2110/00 , F24F2130/00 , F24F2130/10
摘要： Disclosed is a method for predicting the cooling load for efficient operation of a heat accumulation system by obtaining a prediction function regarding outdoor air temperature and specific humidity from meteorological office data, predicting the outdoor air temperature and specific humidity by using the prediction function and the highest and lowest temperatures of the weather forecast, and predicting the cooling load based on the sensible heat load coefficient, outdoor air coefficient, sensible heat load constant, and latent heat load constant, which are obtained from the building design data. The cooling load can be predicted without using a complicated mathematical model and with no reference to past operation data regarding the target building, but solely based on four air-conditioning design values of the building and the highest and lowest temperatures of the next day, which can be easily obtained from the weather forecast of the meteorological office.
摘要翻译：公开了一种通过从气象办公室数据获得关于室外空气温度和比湿度的预测函数，通过使用预测函数和最高的预测函数来预测室外空气温度和比湿度来预测用于蓄热系统的有效操作的冷却负荷的方法天气预报的最低温度，并根据建筑设计数据获得的显热负荷系数，室外空气系数，显热负荷常数和潜热负荷常数来预测冷负荷。可以预测冷却负荷，而不需要使用复杂的数学模型，而不考虑过去关于目标建筑物的操作数据，而仅仅基于建筑物的四个空调设计值和第二天的最高和最低温度可以从气象局的天气预报中轻松获得。

2. 发明申请

WO2009064111A3 METHOD FOR PREDICTING COOLING LOAD 审中-公开
公开(公告)号：WO2009064111A3
公开(公告)日：2009-05-22
申请号：PCT/KR2008/006668
申请日：2008-11-12
申请人： THE INDUSTRY & ACADEMIC COOPERATION IN CHUNGNAM NATIONAL UNIVERSITY , GAGYOTECH CO., LTD. , YOO, Seong-Yeon , LEE, Je-Myo , HAN, Kyu-Hyun
发明人： YOO, Seong-Yeon , LEE, Je-Myo , HAN, Kyu-Hyun
IPC分类号： F24F11/02
摘要： Disclosed is a method for predicting the cooling load for efficient operation of a heat accumulation system by obtaining a prediction function regarding outdoor air temperature and specific humidity from meteorological office data, predicting the outdoor air temperature and specific humidity by using the prediction function and the highest and lowest temperatures of the weather forecast, and predicting the cooling load based on the sensible heat load coefficient, outdoor air coefficient, sensible heat load constant, and latent heat load constant, which are obtained from the building design data. The cooling load can be predicted without using a complicated mathematical model and with no reference to past operation data regarding the target building, but solely based on four air-conditioning design values of the building and the highest and lowest temperatures of the next day, which can be easily obtained from the weather forecast of the meteorological office.

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