There is widespread acceptance of the need to reduce energy consumption within the built environment. Despite this, there are often large discrepancies between the energy performance aspiration and operational reality of modern buildings. The application of existing mitigation measures appears to be piecemeal and lacks a whole-system approach to the problem. This Engineering Doctorate aims to identify common reasons for performance discrepancies and develop a methodology for risk mitigation. Existing literature was reviewed in detail to identify individual factors contributing to the risk of a building failing to meet performance aspirations. Risk factors thus identified were assembled into a taxonomy that forms the basis of a methodology for identifying and evaluating performance risk. A detailed case study was used to investigate performance at whole-building and sub-system levels. A probabilistic approach to estimating system energy consumption was also developed to provide a simple and workable improvement to industry best practice. Analysis of monitoring data revealed that, even after accounting for the absence of unregulated loads in the design estimates, annual operational energy consumption was over twice the design figure. A significant part of this discrepancy was due to the space heating sub-system, which used more than four times its estimated energy consumption, and the domestic hot water sub-system, which used more than twice. These discrepancies were the result of whole-system lifecycle risk factors ranging from design decisions and construction project management to occupant behaviour and staff training. Application of the probabilistic technique to the estimate of domestic hot water consumption revealed that the discrepancies observed could be predicted given the uncertainties in the design assumptions. The risk taxonomy was used to identify factors present in the results of the qualitative case study evaluation. This work has built on practical building evaluation techniques to develop a new way of evaluating both the uncertainty in energy performance estimates and the presence of lifecycle performance risks. These techniques form a risk management methodology that can be applied usefully throughout the project lifecycle.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:658297 |
| Date | January 2015 |
| Creators | Doylend, Nicholas |
| Publisher | Loughborough University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://dspace.lboro.ac.uk/2134/18022 |
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