Proposal of a simple heat transmission model to predict heat demand for operating heat source of air conditioning using computational fluid dynamics

Abstract

It is important that the logical and economical control of air conditioning of a large building with heat source using the combined system of BEMS (Building Energy Management System) and AI. In this study, we propose a new estimating method of heat source for building air conditioning to use the AI system. The method easily estimates the heat demand of buildings through computational fluid dynamics and a basic unsteady heat conductivity model. The fundamental estimating model and implementation factor are determined by actual data of the building B of Fukuoka Institute of Technology. The applicability of this method to another building is investigated, which are not obvious their thermodynamic and structural material data. Consequently, the present method can reasonably estimate heat demand of a building.