I saw a tweet from Control magazine editor-in-chief Walt Boyes, which alerted me to a presentation that I needed to get my hands on.
A fellow member of the industrial energy team, Scott Pettigrew, gave the presentation, Control Technology for Optimizing Combustion Process Performance, at the Advances in Process Control 9 (APC9) in York, UK. Scott noted that combustion control can be a challenge due to normal steam demand variations and the fact that waste and alternate fuels are being used more widely. Addressing these challenges require a holistic approach that builds from the process up and includes solid measurement and final element actuation.
Establishing this solid foundation allows reliable and robust optimization to be built. Cost reductions are then possible by maximizing waste and alternate fuel use and applying economic dispatching. Scott also made the point that controlling a boiler with math and good engineering principals is superior to empirical boiler curves. Instead of boiler curves, air demand can be calculated base on load, stoichiometric air/fuel ratio, and oxygen (O2) setpoint.
For a boiler unit process, a holistic approach begins with a performance audit. It is followed by combustion trials, fuel-handling modifications if needed, air system upgrades as required, airflow measurement and control changes as necessary, and an optimized combustion strategy. After installing improved instrumentation and actuation and modifying standard operating procedures to realize better boiler performance, the cycle can repeat over time for additional gains.
More and more boilers are designed to operate with multiple fuel sources to adapt to changing energy costs. Scott highlighted innovations in combustion control to address multiple fuel sources. The control design is based on total calories and the airflow is controlled in engineering units. Calorific demand stoichiometrically determines the total airflow required plus desired excess O2 for all air systems relative to the fuel consumed. Waste fuels and fossil fuels have different heat release characteristics, but are normalized based on calories.
With optimization at the sensor, final element, and process control level, Scott described how model predictive control with a linear programming (LP) Optimizer can be used to find the best cost solution in real time for control of multiple boilers. The model uses real-time cost information to arrive at the best solution. It also factors in the constraints of the individual boilers and includes gain compensation so that the response is correct regardless of the number of boilers in service.
Based on a model of continuous improvement, energy consumption can be minimized to improve overall operating efficiency.