Energy consumption of supermarket depends more on temperature than humidity. Multiple regression analysis is a flexible tool to consider for energy use prediction. Results show dramatic reduction in gas use and modest increase in electricity use. a r t i c l e i n f o  The change in climate has led to an interest in how this will affect the energy consumption in buildings. Most of the work in the literature relates to offices and homes. However, this paper investigates a supermarket in northern England by means of a multiple regression analysis based on gas and electricity data for 2012. The equations obtained in this analysis use the humidity ratio derived from the dry-bulb temperature and the relative humidity in conjunction with the actual dry-bulb temperature. These equations are used to estimate the consumption for the base year period and for the predicted climate period 2030-2059. The findings indicate that electricity use will increase by 2.1% whereas gas consumption will drop by about 13% for the central future estimate. The research further suggests that the year 2012 is comparable in temperature to the future climate, but the relative humidity is lower. Further research should include adaptation/mitigation measures and an evaluation of their usefulness.
In another work, Braun et al. REF performed multiple regression analysis on gas and electricity usage in order to study how the change in the climate affects the energy consumption in buildings.
Using regression analysis to predict the future energy consumption of a supermarket in the UK
Applied Energy
Engineering