Hermann Schranzhofer

Test buildings with TABS for MPC-performance evaluation — Comparability and system identification

The research project (MPC-Boxes) deals with the design and construction of two test buildings (Test-Boxes), built for the purpose of performance evaluation of a model predictive controller (MPC) in comparison to a standard controller - for heating and cooling via thermally activated building systems (TABS). The paper introduces the experimental environment, investigates the thermo-physical similarity of the two Test-Boxes, and deals with system identification related aspects. A simple third order state space model (SSM) is derived from first principles. This SSM served as a basis for the derivation of a structured SSM which is facilitated for parameter estimation by means of real measurement data. The performance of the structured SSM is validated with different identification data. The cross-validation performance decreases especially for longer validation intervals, however, within the MPC relevant prediction horizon the performance is still acceptable.

Potential Performance Enhancement of a Solar Combisystem with an Intelligent Controller

Solar thermal systems in residential buildings are generally controlled by two-level controllers, which activate solar thermal or at times with low solar radiation auxiliary energy supply into a thermal storage. Simple controllers do not have any information on actual or expected solar radiation. This leads to interference of auxiliary- and solar heat supply, which reduces the share of solar thermal energy fed into the thermal storage. Increasing accuracy of weather forecast data suggests incorporation of this information in the control algorithm. This work analyzes the maximum potential performance enhancement when applying such an intelligent predictive control. Two solar thermal systems with one auxiliary source respectively are designed in TRNSYS – these systems represent the base case. Further, a number of simulations are conducted with minor variations for the plant parameters – this gives generic results for different system configurations. In addition, each system configuration is altered to mimic the behavior of a plant with intelligent predictive control. Comparison of results indicates an improvement potential up to 10% for annual solar fractions and up to 30% for monthly solar fractions. The performance bound with respect to the annual auxiliary energy savings is approximately 8%.