Hyto Energy’s AI-driven microgrid solutions optimize energy distribution across renewable generation, hydrogen storage, and end-use loads. Machine learning models predict energy demand patterns and weather conditions to allocate power efficiently between electrolyzers, fuel cells, and grid interaction. For example, the HPS Picea system uses AI to prioritize hydrogen production during peak solar hours while ensuring sufficient stored energy for winter heating. AI also balances power flow in decentralized grids, minimizing reliance on fossil fuel backups. Hyto’s intelligent controls dynamically adjust setpoints for electrolyzers and fuel cells, enhancing system resilience and reducing operational costs. For microgrid optimization projects, contact us for a tailored AI-driven solution.