Hierarchical model predictive control for resource distribution

This paper deals with hierarchical model predictive control (MPC) of distributed systems. A three-level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or consuming units can be exploited in a smart-grid solution. The objective is to accommodate load variations on the grid, arising from varying consumption and natural variations in power production, e.g. from wind turbines. The approach presented is based on quadratic optimisation and has low algorithmic complexity as well as good scalability. In particular, the proposed design methodology facilitates plug-and-play addition of subsystems without controller redesign. The method is verified by simulating a three-level smart-grid power control system for a small isolated power grid.