  Optimal management of thermal and energy grids with fluctuating demand and
prices requires to orchestrate the generation units (GU) among all their
operating modes. A hierarchical approach is proposed to control coupled energy
nonlinear systems. The high level hybrid optimization defines the unit
commitment, with the optimal transition strategy, and best production profiles.
The low level dynamic model predictive control (MPC), receiving the set-points
from the upper layer, safely governs the systems considering process
constraints. To enhance the overall efficiency of the system, a method to
optimal start-up the GU is here presented: a linear parameter varying MPC
computes the optimal trajectory in closed-loop by iteratively linearising the
system along the previous optimal solution. The introduction of an intermediate
equilibrium state as additional decision variable permits the reduction of the
optimization horizon,while a terminal cost term steers the system to the target
set-point. Simulation results show the effectiveness of the proposed approach.
