Develop smart real-time systems that predict performance, emissions under differing conditions and fuels, perform sensor validation to assure compliance, understand and forecast demand, enhance efficiency and return on assets, and reduce capital and operating costs.
Use model-predictive control to determine setpoints for power generation by modeling the relationships between fuels, demand and unit configurations vs. power and efficiency.
Understand what drives demand and forecast in real-time a blend of consumer and industrial demand. There's no limit to the number of factors, obviously handling time of day, day of week but any other quantifiable factors.
Develop smarter sensors that estimate stack gases accurately and stay accurate using autonomous self-maintaining technologies.
Compare your virtual sensors to physical sensors and become aware when they deviate, indicating that your stack sensors may be failing or your process is behaving abnormally.