Real options and artificial intelligence in decision support for hydrogen-based investments
DOI:
https://doi.org/10.14267/VEZTUD.2026.03.04Keywords:
hydrogen, energy systems, real options, uncertainty, artificial intelligence, bibliometric analysisAbstract
Global decarbonization goals and the rapid pace of the energy transition are changing technological and economic decision-making. Hydrogen is a promising pillar of sustainable energy. Its widespread deployment is hindered by high capital and operational costs, infrastructure constraints, and regulatory uncertainties. These factors complicate investment timing and feasibility decisions. This study seeks to identify research trends and methods for hydrogen investment planning. The authors use bibliometric analysis of keyword co-occurrence, regional distribution, and author networks. Real options theory for incorporating uncertainty and flexibility into investment decisions and the emerging role of AI and ML in optimizing complex energy systems are highlighted. The findings show that most decision-theoretic research focuses on energy system optimization, uncertainty management, and renewables integration, rather than hydrogen. The paper identifies research gaps and suggests ways to explicitly embed hydrogen into economic evaluation frameworks and decision-support systems that use financial models and AI-driven tools.
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