(596g) Model Predictive Control for Load-Following of An Integrated Gasification Combined Cycle (IGCC) Plant with CO2 Capture | AIChE

(596g) Model Predictive Control for Load-Following of An Integrated Gasification Combined Cycle (IGCC) Plant with CO2 Capture


Bhattacharyya, D. - Presenter, West Virginia University
Turton, R. - Presenter, West Virginia University
Zitney, S. E. - Presenter, National Energy Technology Laboratory, U.S. Department of Energy

Future integrated gasification combined cycle (IGCC) plants with CO2 capture may have to adjust their power output as demand for electricity from the grid fluctuates over time. Such load-following requirements will become far more challenging as power produced by renewable energy is connected to the grid and where seasonal and diurnal change in the load is expected.  Considering multiple single-loop controllers for load-following, the preferred control strategy from the perspective of the power producers is gas turbine (GT) lead with gasifier follow. In this strategy, the GT controls the load by manipulating its firing rate while the slurry feed flow to the gasifier is manipulated to control the syngas pressure at the GT inlet. However, the syngas pressure control is an integrating process with significant time-delay mainly because of the large piping and equipment volumes between the gasifier and the GT inlet. In addition, with growing concern over environmental emissions, the emission limits must be satisfied in IGCC plants along with the operational constraints.

While operational and environmental constraints are difficult to satisfy with decentralized proportional–integral–derivative (PID) controllers, model predictive controllers (MPC) are very good candidates for such problems. In this work, a linear model predictive controller (LMPC) is implemented in Matlab while the nonlinear IGCC process is simulated in Aspen Plus Dynamics. A multiple-input multiple-output (MIMO) linear model is identified considering various information-theoretic criteria and by comparing various linear polynomial models. The performance of the LMPC is compared with a modified PID controller where the integrating process is converted to an open-loop stable process by implementing an internal feedback loop.  

To study the load-following control strategies described above, a plant-wide dynamic simulation of an IGCC plant with CO2 capture has been developed. The coal slurry-fed gasifier is a single-stage, downward-fired, oxygen-blown, entrained-flow type with a radiant syngas cooler (RSC).  The syngas from the outlet of the RSC goes to a scrubber followed by a two-stage sour shift process with inter-stage cooling. The acid gas removal (AGR) process is a dual-stage physical solvent-based process for selective removal of H2S in the first stage and CO2 in the second stage. Sulfur is recovered using a Claus unit with tail gas recycle to the AGR. The recovered CO2 is compressed by a split-shaft multistage compressor and sent for sequestration after being treated in an absorber with triethylene glycol for dehydration.  The clean syngas is sent to two advanced “F” class GT’s partially integrated with an elevated-pressure air separation unit. A subcritical steam cycle is used for heat recovery steam generation. A treatment unit for the sour water strips off the acid gases for utilization in the Claus unit. A three-phase, top-down, optimization-based approach is taken for designing the IGCC plant with CO2 capture in the steady-state process simulator, Aspen Plus®. The steady-state model is converted to an Aspen Plus Dynamics® simulation with appropriate modifications in the plant configuration for a pressure-driven dynamic simulation and by providing the dynamic data such as equipment sizes, equipment heat transfer, etc.