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Der sommerliche Wärmeschutz von Schulgebäuden im Oberrheingraben und die Bereitstellung von Kühlenergie wurden bereits untersucht und finden Aufnahme im Leitfaden „Natürliche Gebäudeklimatisierung in Klassenzimmern des südlichen Oberrheins“. Im Rahmen der Arbeiten zur Minderung der sommerlichen Überhitzung wurde durch den Einbau und die damit verbundene kontinuierliche Aufzeichnung der CO2‐Konzentrationen der Raumluft festgestellt, dass besonders im Winterhalbjahr eine Verbesserung der Luftqualität erreicht werden muss.
The uncertain and time-variant nature of renewable energy results in the need to deal with peaks in the production of energy. One approach is to achieve a load shift and thereby help balancing the grid by using thermally Activated Building Systems (TABS). Control systems currently in place do not exploit the full potential of TABS. This paper reviews how Model Predictive Control can possibly reduce the fluctuations of the demand and supply of (renewable) energy as it enables the TABS to react to the dynamics of weather and its impact on the grid at any time.
There is a growing trend for the use of thermo-active building systems (TABS) for the heating and cooling of buildings, because these systems are known to be very economical and efficient. However, their control is complicated due to the large thermal inertia, and their parameterization is time-consuming. With conventional TABS-control strategies, the required thermal comfort in buildings can often not be maintained, particularly if the internal heat sources are suddenly changed. This paper shows measurement results and evaluations of the operation of a novel adaptive and predictive calculation method, based on a multiple linear regression (AMLR) for the control of TABS. The measurement results are compared with the standard TABS strategy. The results show that the electrical pump energy could be reduced by more than 86%. Including the weather adjustment, it could be demonstrated that thermal energy savings of over 41% could be reached. In addition, the thermal comfort could be improved due to the possibility to specify mean room set-point temperatures. With the AMLR, comfort category I of the comfort norms ISO 7730 and DIN EN 15251 are observed in about 95% of occasions. With the standard TABS strategy, only about 24% are within category I.
Adaptive predictive control of thermo-active building systems (TABS) based on a multiple regression algorithm: First practical test. Available from: https://www.researchgate.net/publication/305903009_Adaptive_predictive_control_of_thermo-active_building_systems_TABS_based_on_a_multiple_regression_algorithm_First_practical_test [accessed Jul 7, 2017].