Paper Conference

Proceedings of BauSim Conference 2020: 8th Conference of IBPSA-Germany and Austria

     

SYSTEMATIC RECOGNITION OF DATATYPES AND RESOLUTIONS FOR DEFINING THE DEPTH OF DISTRICT AND BUILDING LEVEL RETROFITS

A. Malhotra, S. Zuhaib, J. Frisch, Treeck C. van

DOI: https://doi.org/10.3217/978-3-85125-786-1-20
Abstract: With the upsurge in the energy demand in Europe, the challenge to improve the existing building stock’s energetic performance calls out for a district and building level intervention through retrofitting measures. Often the amount and type of data required for the retrofit interventions are unclear, and it leaves the decision-makers in a dilemma within the development of low to high quality models based on its value as perceived by stakeholders. There exists a lack of robust indicators that could guide the EU member states to channelise their resources in reducing energy consumption based on the input data for simulation at district and building level. In this paper a QFD (Quality Function Deployment) model is developed to study the relationships between the stakeholder interests as outputs and different input datatypes and requirements, based on the level of detail, for simulation (physical, operational, environmental, geometrical and contextual data) that could impact the optimal model development. Keeping in mind the inadequacy of coherent computational models and informing the users about the implications of acquiring different data, here, the input datatypes, their interaction and collection are simplified to a greater extent through the proposed approach.
Pages: 178 - 185
Paper:
bausim2020_20