Modelling thermal loads for a non-domestic building stock: associating a priori probability with building form and construction - using building control laws and regulations.

Smith, Stefan Thor (2009) Modelling thermal loads for a non-domestic building stock: associating a priori probability with building form and construction - using building control laws and regulations. PhD thesis, University of Nottingham.

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Abstract

Building Energy Assessment at stock level is an important task in identifying the best strategies for achieving a more energy efficient and low carbon society. Non-domestic buildings are identified to make up 17% of total energy consumption in England and Wales and 19% of CO2 emissions. To understand the energy requirement of the non-domestic stock, large scale (empirically based) energy surveying has been carried out namely in the Non-Domestic Building Stock project and Carbon Reductions in Buildings project.

It is recognised that building energy surveys are difficult to carry out; expensive on time, technical resources, and metered energy use is (on a large scale) necessarily crude.

With improving computer ability, dynamic energy modelling tools allow for detailed assessment of building energy use and comfort performance. Using Monte Carlo simulation a method of assessing the probable variability in non-domestic building thermal energy loads was developed. The method was developed to capture the heterogeneity in non-domestic buildings at national stock level and determine how stock level physical form variations impact thermal loading.

Non-domestic building form and surrounding topography are considered to be influenced by building control laws and building regulations. Control documentation often stipulates guidelines and best practice - hence building heterogeneity. As such, historical regulations were used to develop basic probability distributions of potential physical characteristics associated with non-domestic buildings.

Stating that form and site characteristics are randomly determined from the defined probability distributions, a stochastic modelling process to represent thermal variation in a building stock was developed. This provided potential for categorising building thermal performance by period of construction. The model utilised a dynamic simulation model as a 'black-box' for predicting base thermal loads.

Item Type:Thesis (PhD)
Supervisors:Wu, S.
Riffat, S.
Uncontrolled Keywords:thermal loads, architecture, building
Faculties/Schools:UK Campuses > Faculty of Engineering > Built Environment
ID Code:895
Deposited By:Mr Stefan Thor Smith
Deposited On:02 Jun 2010 11:55
Last Modified:02 Jun 2010 11:55

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