AI Cogeneration Dispatch Optimization
Optimizes CHP operating schedules and setpoints against electricity/steam demand and prices to reduce cost and emissions.
The Problem
“Optimize CHP dispatch amid volatile prices and loads”
Organizations face these key challenges:
Coupled heat-and-power constraints make dispatch non-intuitive (steam demand, extraction limits, condenser backpressure, boiler/turbine ramp rates, minimum up/down times).
High volatility in electricity/gas prices and demand forecasts causes frequent suboptimal decisions and missed arbitrage opportunities.
Manual planning and static rules increase risk of reliability events (steam shortfalls), emissions/permit exceedances, and accelerated wear from unnecessary cycling.
Impact When Solved
Real-World Use Cases
Artificial Intelligence for Energy Systems
Think of this as a playbook of AI tricks for running power systems—generation, grids, and consumption—more like a smart thermostat and less like a manual on/off switch. It applies machine learning to decide how much power to produce, when to store it, and how to route it so the overall system is cheaper, cleaner, and more reliable.
AI Grid Congestion Management
This AI helps optimize the layout of power grids to reduce congestion without increasing costs or carbon emissions.