Energy-saving estimation model for hypermarket HVAC systems applications

Abstract

Energy saving estimation model (ESEM) use normal distribution (Gaussian) probability theory to predict potential savings for previously determined system improvements. Those improvements are low/high cost investments based on data gathered during one year monitoring of typical hypermarket facility HVAC system. The consumption of electrical energy and natural gas has been monitored and system segments with largest amount of energy consumption have been marked. Gathered data pointed out to fan units as the biggest energy consumers and suggested that system energy-saving improvement must be focused on fans energy consumption control. This paper deals with ESEM inputs and outputs in order to provide correct financial estimation of specific investment.