Model predictive control of a large fleet of thermal loads and electric power generators, with an assessment for the Netherlands

In this paper we propose a novel control architecture to manage a large fleet of thermal loads and adjust traditional power plant generation setpoints for reference tracking and production costs minimization. The time scales considered are determined by sampling times of a few seconds and control horizons of a few minutes. The control architecture consists in a model predictive controller (MPC) combined with a block called index generator. The index generator receives aggregated control signals from the MPC and splits these among individual loads while satisfying temperature and switching constraints of the controlled appliances. It then computes an updated estimate of the aggregated controllability of the loads and provides this to the MPC for setpoint calculations. This control architecture facilitates handling very large numbers of single thermal appliances and tens of traditional generation units with very small computational efforts. We assess the added value of controlling thermal loads by implementing our control architecture within a simulation framework which accurately represents the Dutch power system.