nDimensional technology is used to help optimize the operations at two combined cycle power plants, where the total capacity of the gas turbine and steam turbine, including additional power generated from duct firing, is bid into the energy market. The goal is to determine the most efficient possible firing regime (i.e. loading across combustion turbines, HRSGs, duct burners, and steam turbines) while meeting the maximum capacity and load-following commitments bid into the Regulation Ancillary Services Market.
Solution: Prediction models are estimating the near-term plant demand and available generating capacity given grid and ambient weather conditions along with a plant equipment response model. These inputs are then used in real-time by optimization models to determine duct burner operation. The optimizer has been allocating fuel across plant blocks and sub-systems to minimize fuel costs while meeting capacity and ramp-rate commitments. It is estimated that leveraging the optimizer to more closely follow predicted demand saves between $875,000 and $1.2 million in fuel costs per year. The models integrated in the new control applications have resulted in more efficient dispatch of duct burners and an overall fuel savings.To ensure the proper balance of cleaning, prediction models are being used. The prediction models estimate the heat duty and cleanliness factor of each heat transfer surface in the boiler (as calculated using a series of performance calculations) and optimization models determine the best sootblower action in real-time. The goal of the optimization scheme is to improve boiler performance while guaranteeing that constraints on blower activation are not violated. On average, across the dozens of optimizers installed, overall sootblower activations have been reduced by 20%, with a steam temperature improvement of 7 degrees, resulting in an overall fuel efficiency improvement of 1%. To ensure the proper fuel-to-air mixture, prediction models are being used to estimate the NOx and CO levels at the stack (as measured by upstream sensors) along with the overall fuel efficiency (a detailed engineering calculation) based on the burner and air port settings. Optimization models then determine the best settings to lower NOx and increase fuel efficiency within CO constraints. On average, across the hundreds of combustion optimizer already installed, NOx emissions have been lowered by 10-25% and fuel efficiency has increased by 0.5-0.75%.