Using IBM SPSS statistics to identify predictors of electricity consumption in a UK supermarket

摘要: In order to save energy in supermarkets, technical solutions need be supported by appropriate maintenance and operation tools. These tools should provide sufficient information detect unusual levels of consumption. Therefore this paper presents an explorative study on a well sub-metered grocery supermarket the UK Yorkshire Humber region. The data collected for included electricity consumption, footfall data, inside outside climate as settings all relevant building timers. Thereafter meaningfulness these predictors was evaluated with ‘stepwise’ option linear regression section SPSS. results generally show very good fit between mathematical model measured (r > 0.95). only exception refrigeration five days. Upon further investigation it found that current reading one days unusually low (proving effectiveness method abnormalities). Based can argued possible use routinely gathered supermarkets or otherwise easily obtained greater abnormalities thus keep consumption minimum.