Abstract
The study aimed to show in a systematic way possible energy efficiency measures that would decrease the total energy use at the university campus in Trondheim, Norway. The entire study was developed in close collaboration with the NTNU Property and Technical Management divisions, meaning that suggested energy efficiency scenarios and other assumptions were highly relevant. Currently, the campus floor area is about 300 000 m2 and consists of buildings combining offices, lecturing halls, study halls, and laboratories. The campus building stock has been built from 1910 to 2002. To perform this study, building performance simulation and the dynamic segmented modeling were combined. A dynamic neighborhood building stock model was utilized to aggregate the outputs from the building simulation and evaluate global effects of energy efficiency measures. Reference building models for each university cohort were developed based on the methodology for defining the reference buildings. The results of the single reference building analyses showed that a decrease of up to 50% in heating energy use might be achieved by increasing efficiency of the ventilation system and by decreasing the temperature of the heating system. The results showed that in spite of building stock growth, the estimated energy use would decrease from 2017 to 2050 by 10% for the standard renovation, and by 26% for the combination of ambitious renovation and technical improvements.
Highlights
Energy planning of the building stock is a highly important topic and highly relevant for energy policy, requirements, and standards development
The study aimed to show in a systematic way possible energy efficiency measures that would decrease the total energy use at the university campus in Trondheim, Norway
The results of the single reference building analyses showed that a decrease of up to 50% in heating energy use might be achieved by increasing efficiency of the ventilation system and by decreasing the temperature of the heating system
Summary
Energy planning of the building stock is a highly important topic and highly relevant for energy policy, requirements, and standards development. Regardless of its importance, this research topic is still in its infancy. Different tools have been developed, but they have only partially succeeded due to sectional and particular interests when developing the tools [1, 2]. There are several reasons for this, such as a fragmented building industry, complex building ownership, divergent interests regarding energy use and supply
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