Model predictive control of demand response for large scale production lines and networks

Utilizing demand response (DR) in industries reduces the need for expensive utilities like storage or backup plants and renders the electricity market more flexible for industrial sites. This paper proposes an MPC-based approach for such sites to respond online to ancillary service requests and participate in DR by controlling optimally the machine speeds of a production line. The optimization program we define can cope with a large number of machines within a line and run therefore efficiently online at a network level without requiring high-power computational resources. We demonstrate the significance of our approach on a beverage production line consisting of a filling machine, two labelers, one shrink packer, and several conveying belts connecting the production machines.