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

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.