Energy saving of the domestic housing stocks: application development as a plug-in for energy simulation software. (18th December 2017)

• Record Type: Journal Article
• Authors: Shi, Wei; Abdalla, Hassan; Elsharkawy, Heba; Chandler, Alan
• Is Part Of: International journal of parallel, emergent and distributed systems. Volume 32(2017)Supplement 1
• Page Start: S114
• Page End: S132
• Publication Date: 2017-12-18
• Subjects: Energy simulation software -- Post-Occupancy Evaluation (POE) -- domestic building -- occupants' behaviour; Parallel computers -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Computer algorithms -- Periodicals; 004.35
• DOI: 10.1080/17445760.2017.1390104
• Languages: English
• ISSNs: 1744-5760

Abstract

Abstract: The research investigates energy conservation in the UK domestic housing sector by focusing on the future of energy simulation software and its impacts on the successful delivery of low-carbon retrofit projects with respect to the concept of 'Parallelism'. During Post-Occupancy Evaluations stage, the simulated energy performance result does not reflect the reality. It is widely recognised that home energy performance is not only subject to physical improvements, but is also related to occupants' socio-economic and behavioral issues. The solution could be the development of an innovative 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 fulfill the research aim, modelling have been created to examine the impacts of people's lifestyle patterns, age groups, ethnic groups, etc., towards energy simulation result. A detailed questionnaire will be implemented into the research design. The expected findings will include that people with different backgrounds will differently operate the dwellings. The collected data will be analysed in order to find the correlations between energy performance and the above-mentioned social, financial and behavioral variables. The data analyses will be conducted by implementing Statistical Product and Service Solutions (SPSS). Abstract : The framework of 'low-carbon retrofit' market.