Dynamic modeling for simulation and control of a circulating fluidized bed combustor

Circulating fluidized bed (CFB) technology has been recognized by industry as a viable gas/solid contacting process with applications including combustion for power generation and waste incineration, pyrolysis, calcining, and catalysis. One important and growing use of circulating fluidized beds is as utility boilers. In this application, the combustor spends most of its life under transient conditions, following the demand of the steam-side. This, in addition to stricter emission requirements, has led to the increasing importance of understanding the transient nature of the circulating fluidized bed combustion (CFBC) process, specifically for control system design and development. In response to this need, the work in this thesis was carried out to investigate the dynamic behaviour of a circulating fluidized bed combustor. A dynamic model has been developed which predicts the transient behaviour of the combustion temperature, rate of heat removal by the in-bed heat exchanger, and the flue gas oxygen concentration for a circulating fluidized bed combustor. These three factors fully define the combustor at any time. The model was incorporated into a simulator to provide an environment for the reproduction of the combustion process on computer. The simulator predicts the behaviour of the combustor under either manual or automatic control. In order to accommodate the chemical kinetic behaviour of various fuels, separate tests were carried out in a bench scale fluid bed combustor to provide order-of-magnitude estimates of the kinetic parameters to approximate the reactivity of these fuels in the combustor. To obtain an estimate of the solids circulation rate, experiments were performed to measure this rate as a function of gas velocity, P/S air ratio, and average riser solids loading. These tests were carried out using a novel time-of-descent method referred to as “line-and-sinker” in which a cage immersed in the moving packed bed descends attached to a chain which passes through a sealed port to the outside of the upper region of the standpipe. Validation of the model is provided through comparison with step response tests carried out on the UBC pilot CFB combustor. Discrepancies are attributed to unmodelled disturbances rather than from basic model concepts. Further validation, necessary to ensure the applicability of the simulator to control development, is provided through a comparison of control models identified experimentally on the pilot CFB to those obtained by simulation. Favourable comparison leads to the conclusion that the dynamic model is suitable for use in control simulation. In parallel with the modeling work, advanced control methods were applied to the pilot CFB combustor. This included process identification through open-loop PRBS testing and time series analysis, application of single loop Generalized Predictive Control (GPC) control of combustor temperature, and multivariable control of the combustor to meet heat removal, flue gas oxygen concentration, and combustion temperature specifications. The identification methods tended to provide higher order control models than probably necessary. This was due to operational limitations of the pilot plant leading to the inability to collect sufficient data, and is not expected to be a problem on an industrial scale. Although model order is not minimal, since the controller may well operate under conditions of changing fuel type, where knowledge of the model for the new fuel is lacking, it would be advantageous to employ an over-parameterized model in order to be able to account for changing dead-time and possible inverse responses. Finally, the applicability of GPC within a CFB combustor framework is demonstrated. The complete control structure takes advantage of the differing time constants of the various parameters within the system. The water outlet temperature control setpoint can be realized in the order of a few seconds with solids circulation rate; flue gas oxygen (notwithstanding optimization), can be maintained within ± 1% with a detuned PD controller adjusting the total air flow based on this measurement; and a GPC controller adjusts the rotary valve control signal in order to maintain combustion temperature requirements with fuel feedrate.Applied Science, Faculty ofChemical and Biological Engineering, Department ofGraduat