Abstract
In future energy markets, traditional thermal power plants are expected to cycle more to adapt their operation to the intermittent power generation of renewable energy sources. Gas turbine load ramps and stresses in thick-walled equipment of the steam cycle are arguably the main limitations in the flexible operation of natural gas combined cycles. This work proposes a control strategy based on model predictive control with stress monitoring to overcome both limitations and enhance the flexible operation of thermal power plants. The linear and nonlinear formulation of the problem included in the model predictive control strategy are described, and two different modelling approaches for the stresses in the high pressure drum and steam turbine rotor are presented. The results demonstrate that the proposed control strategy is capable of computing optimal control sequences without exceeding the maximum allowable stress in critical components and the ramp rates of the gas turbine. The comparison between the linear and nonlinear formulations shows the superior performance of linear model predictive control and suggests that the nonlinear formulation should only be used when the stress models can not be expressed as a linear system of equations.
Highlights
Atmospheric concentrations of greenhouse gases are increasing as a result of the anthropogenic emissions since the industrial revolution [1]
The linear and nonlinear formulation of the problem included in the model predictive control strategy are described, and two different modelling approaches for the stresses in the high pressure drum and steam turbine rotor are presented
The computational performance of the quadratic programming (QP) and nonlinear programming (NLP) optimisation problems is crucial for the utilization of Model predictive control (MPC) as control strategy due to the limited time to carry out the dynamic online optimisation
Summary
Atmospheric concentrations of greenhouse gases are increasing as a result of the anthropogenic emissions since the industrial revolution [1]. The stresses arising on the walls of the power plant equipment depend mainly on temperature gradients, inner and outer pressures, and centrifugal forces These stresses can be limited by an adequate control strategy [15]. MPC leads to better temperature, pressure and level control than traditional PID controllers or control strategies based on single dynamic problems [25,26,27,28,29]. Linear MPC is not suitable and nonlinear formulations of the optimal control problem with stress monitoring are necessary to ensure a safe yet efficient operation of thermal power plants. A comparison between the computational performance of the linear and nonlinear MPC formulations is presented in Section 4 with a case study that demonstrates the capability of the proposed control methodology to limit the stress development in the NGCC.
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