Nonlinear model predictive control for the industrial BioPower 5 CHP plant

In the operation of a biopower plant, a crucial role is played by the residual oxygen content in the flue gas. The flue gas oxygen content, depending on the total air supply and on the fuel composition, provides the information needed to estimate the power developed by the combustion. Therefore, in control systems that operate power plants, the flue gas oxygen content is directly measured and represents a key feedback variable. The novel nonlinear model predictive control developed is based on the model of the BioPower 5 CHP plant which also includes the nonlinear model of the flue gas oxygen content. In addition, the fast response is achieved by regulating primary air flow. To verify the model, experiments were performed at a biopower plant, which utilizes BioGrate combustion technology to enable the use of wet biomass fuels with a moisture content as high as 65%. Then the nonlinear model predictive control was tested in the simulated environment. Finally, the results are presented, analyzed, and discussed.