Spray water control of a boiler superheater outlet temperature

Gadinger, Hans-Jürgen (2019-04)

Thesis (MEng)--Stellenbosch University, 2019.

Thesis

ENGLISH ABSTRACT: This thesis investigates Fuzzy and MPC control techniques for use in superheated steam temperature control through spray water quenching. The techniques are evaluated against the PID controller currently in operation on a specific generating unit at Komati Power Station. These techniques are specifically developed to compensate for plant non-linearity associated with the large thermal inertia that varies with changes in the steam throughput of the superheater. An MPC controller is constructed based on minimising a cost function of the system’s modelled response. It is further developed and shown that, by using a variable sample time in the discrete controller, the model dependency on the steam flow rate can be reduced. The Takagi-Sugeno-Kang Fuzzy control architecture is also developed to compensate for operations at the extreme ends of the operating envelope. The steam flow rate and acceleration are used to construct the rule base for the controller while operating at a fixed sample time. The two controllers are evaluated through the simulation of the controller and the plant model and comparing the results to that of the actual PID controller currently in operation. The simulation indicated a significant improvement in response with both Fuzzy and MPC based controllers over the PID controller, with the Fuzzy controller showing the best result. The MPC controller succeeded in preventing the two trip scenarios simulated. In general, The MPC controller reduced the standard temperature deviation from setpoint to 46 %, and reduces the peak positive transient responses to as little as 51 % of the PID controlled response. The Fuzzy controller performed even better by reducing the standard deviation to 43 % of the PID controller’s deviation and reducing the peak positive transient response to as little as 50 %. The controllers were also tested on an independent operations training simulator commissioned for the station. Although the emulated plant model is perturbed compared to the specific unit used for simulation and modelling, it provides a good validation of the controllers’ robustness. The MPC controller performed on par with the PID controller on the operations simulator while the Fuzzy controller continued to provide a significant performance increase despite the perturbation. It is recommended that the Fuzzy controller be field tested to assist with higher efficiency in operating the generating unit, as well as reducing component wear and fatigue due to temperature excursions.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/106200
This item appears in the following collections: