Robust Optimal Operation for Building HVAC Systems with Uncertainty in Demand Prediction

Abstract

To promote more effective use of the thermal storage systems, optimal operation scheduling of heat source facilities with thermal load prediction is indispensable. Although conventional scheduling method considered the predicted load as a true value, load prediction error is inescapable and could lead to deterioration of actual operational cost. In this paper we propose a robust optimal operation method to reduce negative effect of the prediction uncertainty. The effectiveness of the proposed method is evaluated with the simulation model describing the actual building HVAC (Heating, Ventilating and Air-Conditioning) systems.