An XGBoost Based Prediction Model for Electrochemical Characteristics of Hydrogen Production by Water Electrolysis

With the increasing proportion of renewable generation in the power system, the hydrogen storage is expected to play an important role in the future power system for its clean and efficient characteristics. As an important source of hydrogen storage, the electrochemical characteristics of hydrogen production from water electrolysis have a crucial impact on hydrogen production efficiency. In this paper, an XGBoost based prediction model is proposed for electrochemical characteristics of hydrogen production by water electrolysis under different operation conditions. Firstly, the over potential and impedance characteristics of electrolysis process were investigated through experiments under different temperature and concentration. Then, a performance prediction model of electrolysis hydrogen production is developed based on XGBoost. Test results show that the proposed prediction model is more practical compared with traditional machine learning methods for the analysis of electrochemical process of hydrogen production.