1 Department of Electrical Engineering, Technical University of Denmark2 Center for Electric Power and Energy, Department of Electrical Engineering, Technical University of Denmark3 Intelligent Energy Systems Programme, Risø National Laboratory for Sustainable Energy, Technical University of Denmark
This paper presents a model predictive controller developed in order to minimize the cost of grid energy consumption and maximize the amount of energy consumed from a local photovoltaic (PV) installation. The usage of as much locally produced renewable energy sources (RES) as possible, diminishes the effects of their large penetration in the distribution grid and reduces overloading the grid capacity, which is an increasing problem for the power system. The controller uses 24 hour prediction data for the ambient temperature, the solar irradiance, and for the PV output power. Simulation results of a thermostatic controller, a MPC with grid price optimization, and the proposed MPC are presented and discussed.
Simultech 2012 - Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications, 2012, p. 431-436
Costs; Energy utilization; Heat storage; Heating; Heating equipment; Model predictive control; Optimization; Renewable energy resources; Predictive control systems
Main Research Area:
2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications 2012 (SIMULTECH)Simulation and Modeling Methodologies, Technologies and Applications