Journals Proceedings

Abstract

A multi-objective optimization scheme is proposed for energy saving control of both chillers and air handling units (AHUs). The control scheme also maintains rack intake temperature within a specified range. The non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-objective optimization problem. In order for every chromosome of NSGA-II to calculate the fitness functions which are both total power of chillers and deviations of AHU outlet cold air temperature from specified range, neural network models are used to model the power consumptions of chillers and AHUs as well as the AHU outlet cold air temperature.