Deterministic Global Optimization of Mechanical Vapor Recompression for Brine Concentration in Chlor-Alkali Electrolysis

The growing share of renewables in the electricity mix requires flexible consumption patterns and motivates electrification. Therefore, the flexibility of chlor-alkali electrolysis (CAE) as one of the largest industrial electricity consumers is of high interest. However, flexibility is limited due to the high utilization rates and low storage capacities for chlorine. We investigate the electrification of the brine pretreatment. In particular, we consider concentrating a hypersaline waste stream to near salt saturation for subsequent use as a feed to the CAE via mechanical vapor recompression (MVR). We optimize the design and nominal steady-state operation of the MVR, using a hybrid model that combines mechanistic mass and energy balances with artificial neural network (ANN)-based surrogate models trained on high-fidelity thermodynamic data. We consider 16 different layouts and solve them to global optimality with MAiNGO v0.8.1. The results indicate that thermally integrated single-effect one-compressor configurations are favored, with material selection critically impacting economics. Titanium-based systems are economically infeasible, while those using nickel alloys have potential for economic viability.