Title :
Distributed MPC Strategies With Application to Power System Automatic Generation Control
Author :
Venkat, Aswin N. ; Hiskens, Ian A. ; Rawlings, James B. ; Wright, Stephen J.
Author_Institution :
Dept. of Chem. & Biol. Eng., Univ. of Wisconsin, Madison, WI
Abstract :
A distributed model predictive control (MPC) framework, suitable for controlling large-scale networked systems such as power systems, is presented. The overall system is decomposed into subsystems, each with its own MPC controller. These subsystem-based MPCs work iteratively and cooperatively towards satisfying systemwide control objectives. If available computational time allows convergence, the proposed distributed MPC framework achieves performance equivalent to centralized MPC. Furthermore, the distributed MPC algorithm is feasible and closed-loop stable under intermediate termination. Automatic generation control (AGC) provides a practical example for illustrating the efficacy of the proposed distributed MPC framework.
Keywords :
closed loop systems; control engineering computing; distributed algorithms; distributed control; iterative methods; large-scale systems; power generation control; predictive control; centralized model predictive control; closed-loop stability; distributed MPC algorithm; distributed model predictive control; intermediate termination; iterative method; large-scale networked control system; power system automatic generation control; Automatic generation control; distributed model predictive control; power system control;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2008.919414