EnOB: DataFEE - Data mining, machine learning, feedback, and feedforward - energy efficiency through user-centric building systems

  • Contact:

    Prof. Andreas Wagner

  • Funding:


  • Partner:

    Fraunhofer IBP

    RWTH Aachen

    ABB AG


  • Start Date:


  • End Date:


Project Description

Numerous studies on building energy performance show the significant influence of the occupants on energy use. Simultaneously, there is a large discrepancy between predicted energy use in the design phase and observed energy use during operation due to insufficient knowledge of occupant behaviour. The objective of this joint project is the reduction of this performance gap by means of systematical exploitation and optimization of the processes of data usage. Such reduction will allow reliable predictions for the operation of buildings, while guaranteeing a high level of energy efficiency. This sub-project focusses on the feedforward user-information system and its effect on comfort and energy use.