2017 Volume 30 Issue 6 Pages 209-215
In a central-air-conditioning system, a centralized unit cools or heats water before its circulation throughout a building. By using cooled or heated water, each air conditioner cools or heats each room. To control room temperature, the centralized unit needs to create heating value (heat demand) enough to cool or heat all rooms. To satisfy both indoor comfort and energy saving, the centralized unit needs to create the minimum heat demand that is necessary to satisfy indoor comfort. Heat demand is calculated from temperature difference and water flow rate. However, flow sensors are rarely attached because they are expensive. In this work, we developed a soft-sensor for predicting water flow rate. Although linear regression models have been widely used, they cannot always achieve high estimation accuracy because most of the systems are non-linear and changes in system characteristics make models not suitable. Thus, we adopted locally weighted regression, which is a type of Just-In-Time modeling methods, and achieved high estimation performance.