Mathematical-Programming-Based Optimization of Alkaline Water Electrolyzer for Green Hydrogen Production

Abstract

Hydrogen plays a crucial role in the energy sector toward sustainability and is essential for decarbonizing various sectors of national and international economics. Water electrolysis powered by renewable sources is an environmentally friendly way to produce hydrogen. However, there is room for improvement in the components’ design, dimensions, materials, and electrolysis system. This article focuses on model-based simultaneous optimization of geometric dimensions and operating conditions, such as cell temperature, electrolyte concentration, applied electrolyte pressure, and current density, in an alkaline water electrolysis process. A nonlinear mathematical programming optimization model has been developed. After successful validation against experimental results from the literature, the model was employed for optimization purposes using a gradient-based deterministic optimization approach. The study identifies the operating conditions and geometric dimensions that lead to maximizing cell efficiency and explores the impact of critical operating variables on the optimal solution. The model is implemented in gams software and solved using CONOPT.