Understanding the performance gap in energy retrofitting: Measured input data for adjusting building simulation models

This paper focuses on exploring methods for reducing the gap between the expected and actual building energy performance by using simulation tools. The study has two purposes. The first is to quantify the relative effect of the different building parameters measured on the energy heating and cooling...

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Detalhes bibliográficos
Autores: Cuerda Barcaiztegui, Elena, Guerra-Santin, Olivia, Sendra, Juan J., Neila González, Francisco Javier
Formato: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2020
País:España
Recursos:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/150692
Acesso em linha:https://hdl.handle.net/11441/150692
https://doi.org/10.1016/j.enbuild.2019.109688
Access Level:acceso abierto
Palavra-chave:Residential buildings
Performance gap
Monitoring
Occupancy patterns
Building energy modelling
Descrição
Resumo:This paper focuses on exploring methods for reducing the gap between the expected and actual building energy performance by using simulation tools. The study has two purposes. The first is to quantify the relative effect of the different building parameters measured on the energy heating and cooling consumption compared with standard parameters through the adjustment of simulation models. The second is to develop an approach, based on three methods, for monitoring residential buildings, while also testing and calibrating methodologies for the simulation software. The approach developed is applied and tested in two real case studies (two apartments in two identically constructed buildings, one refurbished and the other not) in the city of Madrid, Spain. The analysis of the case studies shows that there is a four-fold difference in potential savings in energy for heating between models adjusted with standard and actual parameters. Moreover, the results reveal the significant impact of the use of actual weather data and users’ behaviour in the adjustment of simulation models and demonstrate the utility of the application of these methods.