Reduced overall energy costs
Maximized economic performance of the cogeneration unit
Setpoints always aligned with prices and actual demand
Higher operational efficiency
Less waste, less rigidity, more value
Value-oriented intelligent control
Cogeneration plants often operate with:
Result:
Uncontrolled energy costs and undervaluation of CHP assets
Plants
Implemented Measures
Optimisation of energy generation
BASELINE
Results
Annual savings
Energy generation costs
Plants
Implemented Measures
Optimisation of energy generation.
BASELINE
Results
Energy generation costs
Plants
Implemented Measures
BASELINE
Results
Plants
Implemented Measures
Optimisation of energy generation.
BASELINE
Results
Frequently asked questions on
Predictive Optimization of Cogeneration (CHP)
Intelligent cogeneration optimization transforms static management of cogeneration units (CHP) into a dynamic, predictive system.
Through BRAINWATT®, this approach uses Artificial Intelligence algorithms and Digital Twin models to analyze thermal and electrical demand in real time. By correlating this data with economic variables such as gas prices and the PUN (National Single Price), the platform adjusts setpoints to consistently ensure the minimum total energy cost.
Unlike control strategies based on fixed machine parameters, dynamic setpoints allow plant operation to adapt to the hourly economic conditions of the market.
BRAINWATT® software continuously evaluates whether it is more cost-effective to produce energy on-site, purchase it from the grid, or integrate photovoltaic generation. This operational flexibility maximizes the economic benefits of CHP and reduces waste by aligning production with actual costs.
No, adding a higher-level intelligence layer does not replace existing control systems such as PLCs or SCADA, but integrates with them.
BRAINWATT® interfaces with the site’s automation infrastructure to send optimal setpoints while preserving all safety logic and operational constraints of the equipment. This ensures performance improvement without compromising operational continuity or plant safety.
Effective predictive control requires analysis of multiple energy and environmental factors.
The BRAINWATT® platform processes hourly forecasts based on the facility’s electrical and thermal demand, system thermal inertia, and renewable energy production. By integrating this information with updated energy costs and the actual efficiency curves of the cogeneration unit, the system generates a proactive control plan to balance energy procurement and on-site generation.
Yes, dynamic management systems are designed to respond to opportunities in balancing and ancillary service markets.
BRAINWATT® allows the integration of specific parameters to support participation in UVAM schemes (Mixed Enabled Virtual Units), interruptibility programs, or load-following strategies. This capability transforms the technical asset into a financial instrument that can promptly respond to changes in the energy market.
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