Energy-efficient HVAC systems: Simulation–empirical modelling and gradient optimization

Abstract

Abstract This paper addresses the energy saving problem of air-cooled central cooling plant systems using the model-based gradient projection optimization method. Theoretical–empirical system models including mechanistic relations between components are developed for operating variables of the system. Experimental data are collected to model an actual air-cooled mini chiller equipped with a ducted fan-coil unit of an office building located in hot and dry climate conditions. Both inputs and outputs are known and measured from field monitoring in one summer month. The development and algorithm resulting from the gradient projection, implemented on a transient simulation software package, are incorporated to solve the minimization problem of energy consumption and predict the system's optimal set-points under transient conditions. The chilled water temperature, supply air temperature and refrigerant mass flow rate are calculated based on the cooling load and ambient dry-bulb temperature profiles by using the proposed approach. The integrated simulation tool is validated by using a wide range of experimentally collected data from the chiller in operation. Simulation results are provided to show possibility of significant energy savings and comfort enhancement using the proposed strategy.