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.

Abstract: A method implemented using at least one processor includes receiving a plurality of measured operational parameters of a turbo machine having a rotor and a stator. The plurality of measured operational parameters includes a plurality of real-time operational parameters and a plurality of stored operational parameters. The method further includes generating a finite element model of the turbo machine and generating a plurality of snapshots based on the finite element model and the plurality of stored operational parameters. The method further includes generating a reduced order model based on the plurality of snapshots. The method also includes determining an estimated clearance between the rotor and the stator during operation of the turbo machine, based on the reduced order model and the plurality of real-time operational parameters.

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.

Abstract: A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.

Abstract: A method for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site information is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.

Abstract: A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.