A Hierarchical Algorithm for Integrated Scheduling and Control With Applications to Power Systems

作者：Sokoler Leo Emil; Dinesen Peter Juhler; Jorgensen John Bagterp

来源：IEEE Transactions on Control Systems Technology, 2017, 25(2): 590-599.

DOI：10.1109/TCST.2016.2565382

• Hybrid power systems
• mixed-integer linear programming (MILP)
• model predictive control (MPC)
• production scheduling

The contribution of this paper is a hierarchical algorithm for integrated scheduling and control via model predictive control of hybrid systems. The controlled system is a linear system composed of continuous control, state, and output variables. Binary variables occur as scheduling decisions in the optimal control problem (OCP). The scheduling decisions are made on a slow time scale compared with the system dynamics. This gives rise to a temporal separation of the scheduling and control variables in the OCP. Accordingly, the proposed hierarchical algorithm consists of two optimization levels. The upper level (scheduling level) solves a mixed-integer linear program (MILP) with a low frequency. The lower level (control level) solves an LP with a high frequency. The main advantage of the proposed approach is that it requires online solution of an LP rather than an MILP. Simulations based on a power portfolio case study show that the hierarchical algorithm reduces the computation to solve the OCP by several orders of magnitude. The improvement in computation time is achieved without a significant increase in the overall cost of operation.

• 出版日期2017-3