A comparison of algorithms for controlling DSRs in a control by price context using hardware-in-the-loop simulation

With future increasing of electric energy production from fluctuating sources, the need for regulating power will rise and conventional power plants - that today provide all power system ancillary services - could not have the capability and the flexibility of providing it. Demand Side Resource, DSRs, are electric loads whose power consumption can be shifted without having a big impact on the primary services they are supplying and they are suitable for being controlled according the needs of regulating power in the electric power system. In this paper the performances and the aggregate responses provided by three algorithms for controlling electric space heating through a broadcasted price signal are compared. The algorithms have been tested in a software platform with a population of buildings using a hardware-in-the-loop approach that allows to feedback into the simulation the thermal response of a real office building; the experimental results of using a model predictive controller for heating a real building in a variable price context are also presented. This study is part of the Flexpower project whose aim is investigating the possibility of creating an electric market for regulating power with a big participation of DSRs and small scale generation units.