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Diagnosis and Reduction of Electricity Consumption Exceedance in Public University Buildings

Higher education costs per graduating student are globally increasing to unsustainable levels, taking into account the worldwide economy problems. Electricity consumption is an essential part of university building operation costs. Thus, many universities struggle to reduce them. To succeed in the reduction of electricity consumption in public buildings, it is essential to detect, identify and classify different kinds of consumption exceedance modes in the electricity consumption time series as early as possible. Intelligent diagnosis and prognosis has already become an important field of interest in engineering. This paper presents a diagnosis methodology that we developed and applied in the University of Thessaly, aiming to find cases of unnecessary high consumption. The methodology is based on the analysis of hourly electricity consumption data from seven university building complexes with separate medium voltage substations. The follow-up measures adopted are also presented, along with the overall effect on the evolution of electricity consumption.