W7UP7

W7UP7 – Developing a dynamic model to estimate whole building heat loss which requires minimal input measurements
18th October 2016 Frances Hollick

Developing a dynamic model to estimate whole building heat loss which requires minimal input measurements

Frances Hollick, UCL Energy Institute


Overview

Greenhouse gas emissions from domestic buildings contribute significantly to the emissions total, and therefore must be reduced in order to combat serious effects of climate change. Many improvements are being made to homes, both by retrofitting the existing stock and in the designs of new buildings, with the aim of increasing their energy efficiency and reducing heat loss, however their effect on the energy use is often far less than predicted. This is referred to as the performance gap.

To address the issue of the performance gap there must exist a method of assessing the as-built and occupied performance of dwellings, and if this method requires minimal time and expense then it is more likely to be quickly adopted. Existing methods to achieve this include coheating tests, which require an unoccupied property, or models requiring large amounts of inputs. Often these methods cannot take into account occupant behaviour, which can clearly have a dramatic effect on the energy use of a house. Knowledge of the real energy use of buildings would then allow interventions intending to close the performance gap.

This research aims to produce a series of dynamic models of whole dwelling heat loss which require varying numbers of measurements as inputs. The model will be based upon a combination of physical laws and data collected (both by the researcher and from secondary sources) from several domestic buildings, including an end-of terrace, recently retrofitted house and two flats in a large block. It is envisaged that this model will provide estimates for several thermophysical properties of the dwellings it is applied to, and that the effects on the accuracy of the varying numbers of input measurements will be known.

 

Project Team

Student
Frances Hollick

Supervisors
Cliff Elwell & Robert Lowe

Outputs


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