Bibliographic info
Building Simulation, 2007, Beijing, China
Weather prediction is considered to be essential for the predictive control of HVAC systems in which dynamic components, such as a thermal storage tank or heavy building envelope, exist. This paper proposes a method for revising the prior prediction of ambient temperature and humidity by combining two additionally available different data sources, i.e., observations at the building site and forecasts from a weather station. The proposed method applies the theory of orthogonal projection employed in the Kalman filter, and the revised predictions are statistically optimal for determining the minimum variance linear estimate.
