Green Methanol Economy and Optimal Operation by Algorithmic Scheduling: A Case Study

Abstract Green methanol production is a key component of decarbonizing industry, as it provides a sustainable, low-carbon alternative to fossil-derived fuels and feedstocks while enabling the transition to a circular, renewable energy economy. This study investigates the levelized cost of methanol (LCOM) from water electrolysis and carbon dioxide based on an hourly green power supply from hybrid PV-wind renewables. Then, LCOM of green methanol is evaluated and assessed for various component replacement and oxygen selling scenarios. Moreover, flexible operation of a grid-connected green methanol case study is addressed to enable the system to react optimally to electricity price fluctuations. The optimal operation of the electrolyzer unit and hydrogen/carbon dioxide storage with their limitations are considered in the proposed optimization method. The optimization tools schedule each unit’s operation time, based on the hourly electricity price and total methanol demand to reduce operational costs which is applicable for day-ahead predictions. Most of the simulations are performed in the MATLAB environment in view of the local data that are obtained at Esbjerg, Denmark.