Abstract:
A dispatch optimization system leverages ambient and market forecast data as well as asset performance and parts-life models to generate recommended operating schedules for gas turbines or other power-generating plant assets that substantially maximize profit while satisfying parts-life constraints. The system generates operating profiles that balance optimal peak fire opportunities with optimal cold part-load opportunities within a maintenance interval or other operating horizon. During real-time operation of the assets, the optimization system can update the operating schedule based on actual market, ambient, and operating data. The system provides information that can assist operators in determining suitable conditions in which to cold part-load or peak-fire the assets in an optimally profitable manner without violating target life constraints.
Abstract:
In accordance with one aspect of the present technique, a method is disclosed. The method includes modifying one or more operational parameters of a gas turbine (GT) to increase an exhaust gas temperature above a standard start-up temperature. The method also includes receiving at least one of GT operational data, heat recovery steam generator (HRSG) operational data, and steam turbine (ST) operational data from a plurality of sensors. The method further includes predicting a ST roll-off time based on at least one of the GT operational data, the HRSG operational data, and the ST operational data. The method further includes modifying the one or more operational parameters of the GT to satisfy one or more ST roll-off permissives at the predicted ST roll-off time.