We formulate scheduling problems to determine the optimal load profile of each sub-process. In this study, syngas is chosen as a target product of an eCO 2 R process. Since the syngas production rate and power requirement are represented as nonlinear functions of the current density, we solve nonlinear scheduling problems. In order to reduce the computational cost, we apply our recently proposed algorithm based on wavelet transform . We conduct a sensitivity analysis that perturbs the maximum ramping speed of each subprocess to see how much it influences the electricity cost savings. Recent studies on electrochemical CO 2 reduction have reported per-pass conversion of CO 2 below 35% . Thus, the significant amount of unreacted CO 2 remains in the cathode effluent streams and has to be separated by a CO 2 separation unit(s). In this study, we introduce N identical CO 2 separation units connected to N CO 2 -electrolyzer stacks to treat the respective cathode effluent.