Modeling, simulation and control of a methanol synthesis fixed-bed reactor

In this paper, the dynamic behavior and control of the low pressure methanol synthesis fixed bed reactor have been investigated. For simulation purpose, a heterogeneous one-dimensional model has been developed. First, the reactor simulation is carried out under steady-state condition and the effects of several parameters such as shell temperature, feed composition (especially CO2 concentration) and recycle ratio on the methanol productivity and reactor temperature profile are investigated. Using the steady state model and a trained feedforward neural network that calculates the effectiveness factor, an optimizer which maximizes the reactor yield has been developed. Through the dynamic simulation, the system open loop response has been obtained and the process dynamic is approximated by a simple model. This model is used for the PID controller tuning and the performances of fixed and adaptive PID controllers are compared for load rejection and set point tracking. Finally the proposed optimizer is coupled with a controller for online optimization and hot spot temperature protection.