Energy Saving of the Domestic Housing Stocks: Application Development as a Plug-In for Energy Simulation Software

Article


Shi, W., Abdalla, H., Elsharkawy, Heba and Chandler, A. 2017. Energy Saving of the Domestic Housing Stocks: Application Development as a Plug-In for Energy Simulation Software. International Journal of Parallel, Emergent and Distributed Systems. 32 (Sup 1), pp. S114-S132.
AuthorsShi, W., Abdalla, H., Elsharkawy, Heba and Chandler, A.
Abstract

The research investigates energy conservation in the UK domestic housing sectors. The UK government has been dedicated to saving energies from domestic sectors through the implementation of low-carbon retrofit schemes. The paper focuses on the future of energy simulation software and its impacts on a more successful delivery of low-carbon retrofit with respect to the concept of ‘Parallelism’. An obvious problem in the current market is that, for Post-Occupancy Evaluations (POE), the simulated energy performance result does not reflect the actual energy performance. It is widely recognized that the energy conservation of the domestic stock is not only subject to housing physical improvements, but is also related to a series of social, financial and behavioural issues. Among those factors, occupants’ behaviour has the most significant impacts on housing energy performance. The overestimations of those issues decrease the efficiency of low-carbon retrofit in the UK. The solution could be the development of an application that addresses all/most aspects concerned with energy performance variables as a plug-in within a conventional energy simulation software – Standard Assessment Procedure (SAP).
To fulfil the research aim, Modelling has been created to examine the impacts of people’s lifestyle patterns, age groups, ethnic groups, etc., towards energy simulation results. A detailed questionnaire will be implemented into the research design. With the collaborations of Newham Council, survey questionnaires are expected to be carried out towards occupants’ behaviour, household profiles and housing conditions. The expected findings will conclude that people with different backgrounds will differently operate the dwellings differently. The collected data will be analysed in order to find the correlations between energy performance and the abovementioned social, financial and behavioural variables. The data analyses will be conducted by implementing Statistical Product and Service Solutions (SPSS).

JournalInternational Journal of Parallel, Emergent and Distributed Systems
Journal citation32 (Sup 1), pp. S114-S132
ISSN1744-5760
Year2017
PublisherTaylor & Francis
Accepted author manuscript
Digital Object Identifier (DOI)doi:10.1080/17445760.2017.1390104
Publication dates
Online30 Oct 2017
Publication process dates
Deposited10 Oct 2017
Accepted06 Oct 2017
Accepted06 Oct 2017
Copyright informationThis is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Parallel, Emergent and Distributed Systems on 30/10/2017, available online: http://www.tandfonline.com/10.1080/17445760.2017.1390104
LicenseAll rights reserved
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