Model-based optimization of alkaline electrolysis systems for hydrogen production

Abstract

Hydrogen plays a crucial role in the sustainable transformation of the energy systems. Water electrolysis using electricity generated from renewable energy sources is among the most environmentally friendly hydrogen production processes. In this paper, model-based simultaneous optimization of the geometric dimensions and operating conditions of an alkaline water electrolyzer is addressed. To this end, a nonlinear mathematical programming (NLP) optimization model, based on first principles, is developed. Gradient-based deterministic optimization is performed. The model is firstly validated using two reference cases reported in the literature. Then, the values of operating conditions and geometric dimensions that maximize cell efficiency are simultaneously optimized. Regarding computational aspects, the model is implemented in General Algebraic Modeling System (GAMS) software and solved using CONOPT solver.