Integrated Non-model-based Adaptive Optimal Control of SCR and APH Systems at Cayuga Unit 1
E. Schuster, C. Romero, Z. Yao, F. Si, R. L. Morey, J. A. Peter and B. N. Liebowitz
ISA/POWID Conference
Chicago, Illinois, May 12-14, 2009
Abstract
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AES Cayuga Unit 1 is a 160 MW unit, equipped with a low-NOx firing
system and an anhydrous ammonia, TiO2/V2O5/WO3 Selective Catalytic
Reduction (SCR) system for NOx emissions control. A Breen Energy
Solutions ammonium bisulfate (ABS) probe was retrofit to the SCR to
monitor ABS formation in real-time. A recently proposed control system
upgrade includes a control strategy provision for the air preheater
(APH) bypass damper. Such control strategy regulates the ABS
deposition location by manipulating the average cold end APH
temperature with the ultimate goal of minimizing APH plugging (ABS
concentration). Extremum Seeking (ES) is an adaptive control method,
usable for optimally tuning both set-points and controller parameters
in regulation problems. It is a non-model based method of adaptive
optimal control, and, as such, it solves, in a rigorous and practical
way, some of the same problems as artificial neural network (ANN) and
other intelligent control techniques. ES is applicable in situations
where there is a nonlinearity in the control problem, and the
nonlinearity has a local minimum or a maximum. The nonlinearity may be
in the plant, as a physical nonlinearity, possibly manifesting itself
through an equilibrium map. Hence, one can use ES for on-line optimal
tuning of a set point to achieve an optimal value of the output. An ES
controller is proposed to regulate the NH3 flow to the SCR system and
the APH bypass damper opening in order to optimally control in real
time and in a coordinated fashion both continuous emissions monitoring
(CEM) NOx and ABS deposition location within the APH, avoiding NH3
slip and minimizing APH heat rate penalty. The effectiveness of the ES
adaptive controller in keeping the system at an optimal operation
point in presence of input disturbances and system changes (unit load,
coal quality, firing system maintenance condition, SCR aging, etc.) is
demonstrated through simulations.