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

Research output: Research - peer-reviewJournal article – Annual report year: 2017

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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.
Original languageEnglish
JournalIEEE Transactions on Control Systems Technology
Issue number2
Pages (from-to)590-9
StatePublished - 2016
CitationsWeb of Science® Times Cited: 1

    Research areas

  • Power system control, Game theory, Optimisation techniques, Power system management, operation and economics, Control of electric power systems, Linear control systems, Optimal control, Discrete control systems, centralised control, continuous systems, decision theory, discrete systems, hybrid power systems, linear programming, linear systems, optimal control, power generation control, power markets, predictive control, hierarchical algorithm, integrated scheduling and control, model predictive control, linear system, continuous control, output variables, state variables, binary variables, scheduling decisions, optimal control problem, OCP, temporal separation, optimization, mixed-integer linear program, MILP, power portfolio case study, computation time improvement, Control and Systems Engineering, Electrical and Electronic Engineering, Algorithms, Hierarchical systems, Hybrid systems, Integer programming, Linear systems, Model predictive control, Optimal control systems, Optimization, Scheduling, Hierarchical algorithm, Integrated scheduling, Mixed integer linear program, Optimal control problem, Orders of magnitude, Scheduling and controls, Scheduling decisions, Temporal separation, Scheduling algorithms
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