Hovgaard, Tobias Gybel4; Edlund, Kristian5; Jørgensen, John Bagterp6
1 Scientific Computing, Department of Informatics and Mathematical Modeling, Technical University of Denmark2 Department of Informatics and Mathematical Modeling, Technical University of Denmark3 Center for Energy Resources Engineering, Center, Technical University of Denmark4 Department of Electrical Engineering, Technical University of Denmark5 DONG Energy A/S6 Copenhagen Center for Health Technology, Center, Technical University of Denmark
To increase the amount of green energy (e.g. solar and wind) significantly a new intelligent electrical infrastructure is needed. We must not only control the production of electricity but also the consumption in an efficient and proactive manner. This future intelligent grid is in Europe known as the SmartGrid. In this paper we demonstrate the use of Economic Model Predictive Control to operate a portfolio of power generators and consumers such that the cost of producing the required power is minimized. With conventional coal and gas fired power generators representing the controllable power production and a significant share of renewable energy, such as parks of wind turbines, representing the uncontrollable power generators we have demonstrated how the addition of controllable consumers, such as large cold rooms or supermarkets with a thermal capacity, can infuse the desired flexibility of the grid for utilization of more green energy and also lower the total cost. We formulate the supply-demand constraint as a probabilistic constraint, thereby robustifying the solution against uncertainties in power demand. We use small conceptual examples for simulations.
Computer-aided Chemical Engineering, 2011, p. 1839-1843
Main Research Area:
Computer - Aided Chemical Engineering
21st European Symposium on Computer Aided Process Engineering, 2011