Energy analysis and surrogate modeling for the green methanol production under dynamic operating conditions

Green methanol production, based on intermittent renewable energy sources, requires a more flexible operation mode and close integration with other sections, such as, the electrical grid and electrolysis processes. In this study, methanol synthesis and distillation processes (MSD) for pilot-scale green methanol production (corresponding to 22,236 tons/year) were investigated by dynamic modeling, focusing on energy analysis and dynamic characteristics during load change (LC) operations. The dynamic simulation results with a ramp rate of 50% load / h indicated energy efficiencies of 87.7% (at full-load) and 90.2% (at half-load) for the methanol synthesis process, 86.8% (full-load) and 82.4% (half-load) for the methanol distillation process, and 77.1% (full-load) and 75.4% (half-load) for the MSD process. Relatively small fluctuations were achieved with a ramp time of 1 h for the LC operations. Based on the constructed dynamic model, a surrogate modeling for the MSD process was conducted using the nonlinear autoregressive exogenous model (NARX) model, which exhibited good accuracy with the evaluated performance for the testing data of the root-mean-square error (RMSE) = 3.09 x 10(-5), mean absolute error (MAE) = 2.30 x 10(-4), and R-2 = 1.0. The constructed NARX model can be further integrated with models for other sections of the power-to-methanol process.

Automated summary

This study investigated the methanol synthesis and distillation processes for pilot-scale green methanol production through dynamic modeling, finding differences in energy efficiency during load change operations and relatively small fluctuations achieved with a 1-hour ramp rate. Surrogate modeling for the MSD process using the NARX model exhibited good accuracy and can be further integrated with models for other sections of the power-to-methanol process.