Abstract
Modern buildings are equipped with various complex
automation systems that produce vast amounts of data.
The operation of these systems has significant influence on
energy demands and user comfort in the premises. Therefore, an
optimal configuration of the systems to increase energy efficiency
is desired by the operators of the building. An automated
decision-making process that evaluates and analyzes the bulk
of available data can help to achieve these objectives. Hence, this
work introduces a framework for the automatic generation of
recommended configuration changes to increase energy efficiency
and user comfort. The approach makes extensive use of semantic
building information modeling as basis for the selection of
potentially useful measures as well as for their assessment.
Expected consequences of configuration changes are forecasted
via simulation. Additionally, current results of an application of
the proposed solution in an office building are discussed in this
work.
| Original language | English |
|---|---|
| Title of host publication | IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society |
| Pages | 819-825 |
| Number of pages | 7 |
| Publication status | Published - 2018 |
| Event | IECON 2018 - Duration: 21 Oct 2018 → 23 Oct 2018 |
Conference
| Conference | IECON 2018 |
|---|---|
| Period | 21/10/18 → 23/10/18 |
Research Field
- Former Research Field - Digitalisation and HVAC Technologies in Buildings
