Development of an MCTS Model for Hydrogen Production Optimisation

Hydrogen has the potential to revolutionize energy industry due its clean-burning and versatile properties. It is most abundant element in universe can be produced through a variety of methods, including electrolysis. The widespread adoption hydrogen faces various challenges, high cost production; thus, it important optimise production processes. This research focuses on development models for optimisation based external factors parameters. Models electricity prices are developed compared between different market situations. To run more effectively, required use renewable sources process. Adding solar power component economic evaluation model outcome positive. Monte Carlo tree search (MCTS) algorithm adapted effectively control electrolysis MCTS schedule optimization was performed 24 h time horizon applying two time-resolution settings—1 15 min. results demonstrate finding good schedules water electrolyser devices by taking into account variable environmental factors. Whereas with min resolution ensures mathematically better results, requires computational solve decision tree.