Abstract

Most of the current domestic hot water tanks store heat in sensible form. They use electrical heaters which have low efficiency of energy utilization. Latent heat storage systems have become popular recently, and they seem to be more efficient than existing storage systems. High latent heat of phase change materials and their compactness are the main reasons for their popularity in the thermal storage industry.
This thesis reports the outcomes of implementing PCM in a standard domestic hot water tank, on energy consumption and the discharge period and suggests a method for optimization of the tanks regarding their discharge time. Geometrical aspects of PCM containers and the amount of PCM inside the tank were design parameters of this study. TRNSYS was used to simulate the behavior of the tank. The results of 900 simulations were used to create an initial database for training an artificial neural network in order to find a correlation between design parameters of the tank and the discharge time. Genetic Algorithm was then used in order to find the optimum amount of PCM needed for a desired discharge time.
Finally, a comparison between an optimized tank and a regular water tank was done. It was concluded that an optimized tank is able to provide hot water while consuming less energy compared to a hot water tank without PCM. Furthermore, by placing a certain amount of PCM at the top part of the tank, electrical energy consumption could be shifted completely to off peak periods characterized by less power demand.