Document Type

Article

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

2. ENGINEERING AND TECHNOLOGY, Civil engineering, Energy and fuels

Publication Details

Energy and Buildings, Volume 65, October 2013.

Available from the publisher here

Abstract

In accordance with national and European policies, the provision of financial assistance to residential energy consumers has led to a greater awareness of and interest in energy retrofit technologies. However, at present Irish energy consumers have no appropriate advice on the future performance of retrofit options available to them. This is a significant limitation to decision making and technology uptake, since this group need to know whether their investment is likely to be worthwhile.

The asset rating methodology developed for the certification of energy performance of buildings is the current industry standard of prediction of energy demand and post retrofit performance. The methodology is tedious and may not be viable for ESCos to send trained assessors to residential dwellings while residential customers do not possess the technical knowledge to complete the survey of their own dwelling.

This research investigates if the asset rating procedure can be simplified to permit development of simpler models, which would allow quicker and easier assessment of the energy performance of residential dwellings.

An asset rating model was created in excel. The Irish housing stock was simulated using a sample data set and Monte Carlo techniques. The model was simplified in stages by systematically removing and parameterising input variables from an initial list of 50.

The results of these test methods are presented and should be consulted by policy makers, ESCos and private bodies who wish to create a simplified asset rating type model with known error margins for the prediction of dwelling energy performance.

DOI

https://doi.org/10.1016/j.enbuild.2013.04.023

Funder

IRCSET/E.S.B - Electric Ireland

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