Next-level adaptive control for maximum efficiency and resilience – with AI operators can trust
Energy Autonomy closes the loop: AI continuously optimizes energy systems – from cooling and ventilation to power generation and storage – adapting in real time to changing conditions. Operators stay in control by defining objectives and boundaries, while autonomy delivers efficiency, resilience, and sustainability.
Trusted by leading data centers, manufacturers, and energy innovators.
Too many assets, too many variables, lack of qualified staff
Industrial energy systems span HVAC, electrical loads, storages, and generation assets – all influenced by environmental conditions, energy markets and operations. Manual control and rule-based strategies can’t keep up – leading to inefficiencies, higher costs, and missed sustainability targets.
How it works – AI optimization and control in real time, from HVAC to microgrids
Energy Autonomy builds on transparency and foresight to close the loop:
For Cooling, Ventilation, Heating, Electrical Systems – from Generation, Storage, Distribution to Consumption – Single assets to combined hybrid & multivalent energy grid
Ability to optimize even the most complex energy systems
Industrial energy infrastructures are rarely simple. They combine HVAC, cooling, heating, electrical systems, storages, generation units, and interconnected hybrid grids. Traditional control strategies fail when faced with thousands of variables and dependencies. Energy Autonomy is built to handle this complexity – optimizing across all assets and flows in real time, without adding operational burden.
Self-optimizing control for complex energy systems
Energy Autonomy continuously adjusts HVAC and energy system operations in real time, efficiency, and resilience. AI handles thousands of variables – from chillers and pumps to ventilation – to reduce energy waste and keep performance stable.
The outcomes:
Optimize energy storages and generation against market signals
Energy Autonomy integrates energy market prices and grid signals to schedule energy storages and generation dynamically. By aligning operations with price and demand peaks, operators reduce costs.
AI-driven microgrid management for stable operations
Autonomy prevents cost-driving load spikes by redistributing or delaying loads in real time. Automated peak management avoids expensive demand charges while maintaining operational reliability.
Optimize energy procurement in real time
Energy Autonomy supports dynamic energy purchasing strategies. By combining forecasts, market data, and flexible scheduling, operators minimize procurement costs while ensuring supply reliability.
A good engineer always stays in control
Energy Autonomy is designed with built-in safeguards and fail-safes. Operators define the degrees of freedom, monitor AI recommendations, and can enable or disable autonomous control at any time. Fallback systems ensure that safety-critical control always remains in your control infrastructure. The result: AI delivers efficiency and resilience, while engineers stay firmly in control
AI optimization delivering measurable impact
Customers using Energy Autonomy have achieved significant reductions in energy use and CO₂ emissions while ensuring resilient, compliant operations. Autonomous optimization empowers operators to focus on strategy instead of manual control.
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Make your energy systems future proof
Take the final step: let AI continuously optimize your systems – reducing costs, cutting CO₂, and improving resilience, all with autonomy you can trust.
