Chiller plant optimization - an integrated optimization approach for chiller sequencing and control

Abstract

We present an integrated approach for optimizing the set-points and sequencing multiple chillers in a centrifugal chiller plant. For a certain duration of time where the cooling load can be predicted, we use the predicted values as an input to determine the optimal choice of the various set-points in the chiller plant model, together with finding a sequencing strategy by taking into account the minimum up-time/down-time constraints. We model the mass and energy balance in the various components of the chiller plant, including the condenser, compressor, evaporator and fans, and use this model for the underlying set-point optimization. We use a graph based minimum path algorithm for determining the optimal sequencing strategy. Simulation results show the proposed algorithm achieves approximately 25% savings in cost of operation when compared to the default chiller sequencing strategy. At the same time, the proposed sequencing and control strategy satisfies the daily cooling demand curve during the entire cycle.