Abstract
ABSTRACT The inherent variability of renewable energy sources, pump storage plants and combined cycle gas turbines implies that coal-fired plants designed for continuous base load generation in South Africa must now be used for variable load. This has a negative effect on the overall efficiency and life expectancy of these plants. The challenge is, therefore, to balance the network demands with the power station operation, its thermal efficiency, availability and extended plant life expectancy. The focus of the current research is to monitor and optimise the efficiency of the boiler operation and control through modelling of the boiler subsystems during transient states. Flownex® Simulation Environment was used to model a generic boiler and a boiler control system in order to simulate thermo-fluid processes and critical boiler controllers. The developed model was evaluated based on plant data and optimised afterwards by means of PID controllers and Machine Learning algorithms. The process parameters obtained from the Machine Learning algorithms outperform that of the PID controllers for the selected controllers, such as: boiler load control and steam pressure control. Additional keywords: Power generation, boiler control, boiler modelling.
Highlights
Steam generation is a critical parameter in coal-fired power plants
In order to evaluate the performance of boiler sub-systems, in this research, a thermo-fluid model was modelled in accordance to the mechanical and process characteristics of an existing power plant
The model consists of a boiler steam drum, evaporator, superheater, attemperator, high pressure and low-pressure turbines
Summary
Steam generation is a critical parameter in coal-fired power plants. the control of critical parameters associated with a boiler system is imperative due to constant load changes, which is a common occurrence in the current electrical industry [1]. In the boiler-following mode, the MW load demand signal is referred directly to the control of the turbine governing valve, which is modulated to meet the MW load demand, figure 1 This action allows for fast responses to changes in MW load as the stored steam energy in the boiler is utilised. Boiler-following control mode results in less stable pressure control as there is a lag between the turbine and boiler responses This in turn creates undershoots or overshoots in the steam pressure set point. The efficiency of the boiler, which depends on the performance of the controllers and the executing systems, is determined by the critical process parameters, such as: MW load, steam pressure, steam temperature, furnace pressure, boiler drum level, residual oxygen (O2) in the furnace, coal flow, air flow etc. The focus is on two critical parameters and the corresponding controllers: the boiler load and the steam parameters
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