A key to success: Improved statistics on energy end use in buildings

Agneta Persson, WSP Environmental, Sweden
Monica Gullberg, ÅF-Process AB, Sweden
Heini-Marja Suvilehto, Swedish National Energy Agency
Anders Göransson, Profu AB. Sweden

Keywords

improved energy statistics, end-use, modelling

Abstract

Detailed statistics on energy end-use patterns in buildings is a prerequisite for structured energy and facility management and successful creation, impact prediction, implementation and monitoring of energy policies and proposed actions for reduced GHG-emissions from the building stock. Moreover, lack of evaluation significance is often used as an argument against energy-efficiency actions. The quality of national building energy statistics has during recent years declined, resulting in an increasingly difficult situation for policy makers and energy-efficiency advocates. To improve this situation the Swedish National Energy Agency has launched a new programme, including one project dealing with improved energy statistics in non-residential buildings.

The project runs in six year cycles, and step-wise covers all categories of tertiary buildings. End use will be mapped out in approximately 1 000 buildings during each six-year period. High priority is given to electricity, and its allocation between different end use categories (heating, cooling, lighting, ventilation, etc), although total energy end use is noted as well. The first audits were carried out in 2005, including 123 offices and administration buildings. The second year audits include school buildings and were performed during 2006.

The first-year results provide highly interesting detailed information. Findings from the 2005 audits are e.g. that energy end-use varies with a factor four between buildings, and, contrary to common assumptions, total average electricity consumption in office buildings has decreased. This paper will describe the findings of the two first years of audits; furthermore it will elaborate on the rational behind improved building energy statistics, including important applications of such data.