Dynamic modeling and fuzzy augmented PI control of a high-rise building hot water heating system

Energy consumption of hot water heating (HWH) systems in high-rise buildings is a topic of considerable economic interest. In this study a dynamic model of a HWH system was developed and an intelligent fuzzy logic operating strategy was designed to improve energy efficiency of the system. Dynamic responses of temperature and water mass flow rate in the system were studied. Two types of boiler temperature set-point strategies, one based on average outdoor air temperature method and the other using a fuzzy augmented system, were explored and their performance was compared. From the simulation results it is shown that the strategy based on the fuzzy inference system saved boiler fuel consumption by about 10%.