Abstract
The building sector is rising rapidly which is not
only the consequence of the world´s increasing population but also
due to higher requirements with regards to comfort. Buildings
along with HVAC systems to run these buildings account for a
large amount of the world´s global energy consumption. Hence
operating buildings as well as HVAC systems in an energyefficient
way plays the key role in reducing energy consumption
and therefore making the contribution towards mitigation of
the climate change. Studies about advanced control techniques
for buildings and systems to run those have shown promising
results with regards to lower energy consumption and the
optimal use of renewable energy sources. In contrast to the
conventional approaches (e.g.: PID, two-position controller, etc.)
for building and HVAC control, model based concepts take
advantage of the direct knowledge of the system behaviour using
an image of the system. Model based control concepts facilitate
the systematic approach towards the energy-efficient operation of
building and HVAC systems. However, the quality of the model
based controller strictly depends upon the quality of the model
employed to describe the dynamic behaviour of the system being
subject to control. The model-plant mismatch can negatively
impact the energy-efficient control operation.
This paper presents the design of an unscented Kalman filter
(UKF) approach for the purpose of state and parameter estimation
for solar thermal HVAC system control. This UKF concept
incorporates the possibility of model update using measurements
and therefore reduces model-plant mismatch which in turn
improves the control quality and can be regarded an asset with
respect to the energy-efficient control operation.
Originalsprache | Englisch |
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Titel | IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society |
Herausgeber (Verlag) | IEEE Industrial Electronics Society |
Seiten | 2180-2185 |
Seitenumfang | 6 |
Publikationsstatus | Veröffentlicht - 2012 |
Research Field
- Ehemaliges Research Field - Energy