The extensive growth of installed wind energy plants in Denmark leads to increasing balancing problems in the power grid due to the nature of wind fields and variations in consumption. One way to overcome these problems is to move consumption to times where wind power otherwise cause overproduction. A part of a solution can be to take advantage of floor heat capacity in single-family houses using heat pumps. This large heat capacity makes it possible to move consumption without compromising the comfort of house residents. In a Danish research project a virtual power plant using centralized control of a large number of houses with heat pumps is established. In order to make the control algorithm a vital part is a dynamic model of each house. The model predicts the house indoor temperature when heat pump power and outdoor temperature is known. The model must be able to describe a large variety of heat pumps and houses. In the paper a house model and a method to identify the model is presented. The Kalman observer models are optimized using measurements from real houses.
['Palle Andersen', 'Tom Søndergaard Pedersen', 'Kirsten Mølgaard Nielsen']
Observer based model identification of heat pumps in a smart grid