Flexible power-to-methanol production via CO 2 hydrogenation using look-up table model predictive control under variable wind and solar energy

The spatiotemporal uncertainty of renewable energy output causes downstream chemical plants to frequently deviate from their design operating conditions. This paper constructs a full-process 8760-h quasi-steady-state simulation model encompassing “wind/solar power generation – alkaline water electrolysis for hydrogen production – MEA-based carbon capture – methanol synthesis”. To address the source-load mismatch issue, a two-layer flexible operation architecture comprising “offline interval optimization + online model predictive control (MPC)” is proposed. The offline layer utilizes a 15 × 15 two-dimensional feature binning partition to delineate the operational boundaries, demonstrating that the maximum production strategy increases output by 64.6% compared to fixed conditions, while the minimum specific energy consumption strategy reduces energy consumption by 39.2%. The online layer develops a fast MPC framework based on a pre-calculated look-up table, incorporating dual buffer tank dynamics, equipment rate hard constraints, and a time-of-use (TOU) electricity pricing mechanism. Simulation results demonstrate that the strategy automatically reduces the reactor setpoint temperature during peak electricity price periods (from 250.0 °C to 243.4 °C). Compared to the unconstrained Reactive benchmark strategy, it reduces the local equivalent operating electricity cost of the methanol synthesis loop by 43.8%, validating the proactive economic dispatch capability of the framework despite the loop’s minor share (∼3%) of total system energy consumption, while sacrificing only 8.1% of production.