Assessment of energy performance using bottom-up method

Autor: Khadidja El-Bahdja Djebbar, Abderrahmane Mokhtari, Souria Salem
Rok vydání: 2019
Předmět:
Zdroj: International Journal of Building Pathology and Adaptation. 38:192-216
ISSN: 2398-4708
DOI: 10.1108/ijbpa-11-2017-0056
Popis: Purpose The purpose of this paper is to analyze energy performance of the multi-storey buildings built in the city of Tlemcen between 1872 and 2016. Design/methodology/approach A diagnosis based on a bottom-up methodology, using statistical techniques and engineering, has been developed and applied. To do this, demand condition analysis was conducted using a data collection survey on a sample of 100 case studies. Physical characteristics of the buildings have been determined through the archetype by period. This serves to define the strengths and weaknesses of buildings as energy consumers. Findings The obtained results showed that dwellings built between 1872 and 1920 offer better energy performance with a consumption index close to 130kWh/m2/year and this compared to the five periods considered. For dwellings built between 1974 and 1989, energy consumption is higher with an index approaching 300kWh/m2/year, thus qualifying the buildings of this period as energy intensive. Originality/value A database is established to collect physical information on the existing housing stock and thus allow their classification vis-à-vis of the energy label. This study is part of a research project aimed at evaluating and determining optimal measures for energy rehabilitation of multi-family buildings in Tlemcen. Thermal rehabilitation solutions are proposed using thermal simulations, in the following studies, to improve thermal performance of existing buildings. This study constitutes the first step of a roadmap applicable to other cities constituting climatic zones in Algeria. This helps to enrich the Algerian thermal regulation in thermal rehabilitation of existing residential buildings and conception of new ones, in urban areas with a similar climate.
Databáze: OpenAIRE