Integer and combinatorial optimization
Integer and combinatorial optimization
Automatic Symbolic Verification of Embedded Systems
IEEE Transactions on Software Engineering
Controllers for reachability specifications for hybrid systems
Automatica (Journal of IFAC)
Control of systems integrating logic, dynamics, and constraints
Automatica (Journal of IFAC)
Dynamic programming for constrained optimal control of discrete-time linear hybrid systems
Automatica (Journal of IFAC)
HPN modeling, optimization and control law extraction for continuous steel processing
Proceedings of the Winter Simulation Conference
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In this paper the optimization of a combined cycle power plant is accomplished by exploiting hybrid systems, i.e. systems evolving according to continuous dynamics, discrete dynamics, and logic rules. The possibility of turning on/off the gas and steam turbine, the operating constraints (minimum up and down times) and the different types of start up of the turbines characterize the hybrid behavior of a combined cycle power plant. In order to model both the continuous/discrete dynamics and the switching between different operating conditions we use the framework of Mixed Logic Dynamical systems. Next, we recast the economic optimization problem as a Model Predictive Control (MPC) problem, that allows us to optimize the plant operations by taking into account the time variability of both prices and electricity/steam demands. Because of the presence of integer variables, the MPC scheme is formulated as a mixed integer linear program that can be solved in an efficient way by using commercial solvers.