Abstract
In this work, we propose an optimal control strategy as the unit control for combined-cycle power generation units. Using the same optimal control, we propose to optimize other internal control structures. Data-Enabled Predictive Control is chosen as the optimal control problem formulation, as it does not require a parametric state-space representation of the system. This bypasses the challenging and expensive-To-solve issue of parametric modeling and linearization for highly nonlinear systems. The performance of the controller is investigated in several critical operational scenarios, such as load-following for frequency control and disturbance rejection. Simulation results in Apros®, which is an environment dedicated to advanced process simulation, are presented.
Original language | English |
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Pages (from-to) | 91-96 |
Number of pages | 6 |
Journal | IFAC Proceedings Volumes (IFAC-PapersOnline) |
Volume | 55 |
Issue number | 13 |
DOIs | |
State | Published - 2022 |
Event | 9th IFAC Conference on Networked Systems, NECSYS 2022 - Zurich, Switzerland Duration: 5 Jul 2022 → 7 Jul 2022 |
Keywords
- Data-Enabled Predictive Control
- Flexibility
- Frequency Control
- Load Cycling
- Power Networks
- Power Plant Control