Effects of scenario uncertainty on chiller sizing method

Abstract

Opportunities to save energy in the design and operation of Heating, ventilation and air conditioning (HVAC) systems have come into sharp focus. Lighting intensity, electric equipment load and occupant density have great impact on the peak cooling load of building, which is the basis of the chiller sizing. There is inevitable uncertainty in the determination of the values of these three scenario parameters at the detailed HVAC design stage and thus these uncertainties can considerably impact chiller sizing choice. However, the conventional chiller sizing method does not deal well with these uncertainties. A new chiller sizing method is proposed in this paper taking into account the scenario parameter uncertainty, the discrete spectrum of nominal cooling capacity of available chillers, the difference of chiller cooling capacity under nominal condition and peak cooling load condition. The new approach quantifies the impacts of scenario uncertainty on peak cooling load, chiller life cycle cost (LCC), and also on annual set point unmet hours based on the Monte Carlo method and dynamic simulation. For the case study, compared with conventional sizing method, the new sizing method can greatly reduce chiller nominal cooling capacity and the minimum reduction is 22.51%. The new method can help the HVAC designer to determine the optimal chiller size with the consideration of scenario uncertainty and the balance of chiller LCC and indoor thermal comfort of HVAC system.