Halvgaard, Rasmus4; Poulsen, Niels Kjølstad2; Madsen, Henrik2; Jørgensen, John Bagterp5
1 Center for Energy Resources Engineering, Center, Technical University of Denmark2 Department of Applied Mathematics and Computer Science, Technical University of Denmark3 Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark4 Scientific Computing, Department of Applied Mathematics and Computer Science, Technical University of Denmark5 Copenhagen Center for Health Technology, Center, Technical University of Denmark
The method described in this paper balances power production and consumption with a large number of thermal loads. Linear controllers are used for the loads to track a temperature set point, while Model Predictive Control (MPC) and model estimation of the load behavior are used for coordination. The total power consumption of all loads is controlled indirectly through a real-time price. The MPC incorporates forecasts of the power production and disturbances that influence the loads, e.g. time-varying weather forecasts, in order to react ahead of time. A simulation scenario demonstrates that the method allows for the integration of flexible thermal loads in a smart energy system in which consumption follows the changing production.
2013 European Control Conference (ecc), 2013, p. 2567-2572
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12th European Control Conference (ECC 2013)European Control Conference