Correlating Supply & Demand of Cooling & Energy between Gas District Cooling Model with Data Center

Abstract

This study is to determine the correlation amongst chilled water temperature supply from Gas District Cooling (GDC) operations and demand for cooling and energy demand from Data Centres (DC) operations. At first, the GDC-DC modelling was proposed by Hitachi Research Team in UTP. This is because, UTP has and advantage of GDC to house the campus region with electrical energy and chilled water for air conditioners in UTP's academic buildings, chancellor complex, and UTP mosque. This paper aims to find contribution of real-time system in optimizing the cloud DC that can impact the cooling demand & energy demand. The studies on the demand of cooling and energy from the operation of DC has been tested on Linux real-time operating systems with AMD FX850 processors with selected job scheduling algorithms. Pearson's r correlation analysis between GDC & DC has shown that there is a significant disparity between the chilled water temperature supply from GDC with cooling demand from DC where $\mathrm{r}=0.130$ which is more than 0.05. Apart from that, Round Robin (RR) algorithm has reduced power consumption in DC but not reducing the cooling demand, while First In First Out (FIFO) algorithm has reduced the cooling demand in DC and the trend is followed by power consumption.