Abstract: A non-transitory computer readable storage medium storing one or more processor-executable instructions wherein the one or more instructions when executed by a processor of a controller, cause acts to be performed is provided. The acts to be performed include controlling a fuel split to a combustor of a gas turbine utilizing automatic tuning and switching control of the fuel split to the combustor of the gas turbine to utilizing an adjusted fixed fuel split schedule instead of automatic tuning. The adjusted fixed fuel split schedule includes a fixed fuel split schedule adjusted via a biasing value, and the biasing value is based on both the fixed fuel split schedule and an automatic tuning based fuel split.

Abstract: A non-transitory computer readable storage medium storing one or more processor-executable instructions wherein the one or more instructions when executed by a processor of a controller, cause acts to be performed is provided. The acts to be performed include controlling a fuel split to a combustor of a gas turbine utilizing automatic tuning and switching control of the fuel split to the combustor of the gas turbine to utilizing an adjusted fixed fuel split schedule instead of automatic tuning. The adjusted fixed fuel split schedule includes a fixed fuel split schedule adjusted via a biasing value, and the biasing value is based on both the fixed fuel split schedule and an automatic tuning based fuel split.

Abstract: A system may include a gas turbine system. The gas turbine system may include a compressor, such that the gas turbine system may produce exhaust gas in an exhaust outlet when generating electricity. The system may also include a heat recovery steam generator (HRSG) that may use the exhaust gas to create steam, a manifold system configured to couple compressed air in the compressor to the exhaust outlet, and a controller configured to send a command to the manifold system to couple the compressed air to the exhaust outlet when a temperature of the exhaust gas is above a threshold.

Abstract: A method and system for transferring between combustion modes in a gas turbine engine is provided. A processor generates data representative of an initial set of splits for providing at least one of fuel and air to at least one combustor in the gas turbine engine. A gas turbine engine model module generates data representative of at least one engine operating condition. A first split calculation module generates data representative of at least one set of active control splits to control the engine in a first combustion mode, using as an input the initial split data. A second split calculation module generates data representative of at least one set of passive control splits to control the engine in at least a second combustion mode. Transfer between combustion modes may be accomplished via use of at least one of the active control splits and the passive control splits.

Abstract: A method and system for transferring between combustion modes in a gas turbine engine is provided. A processor generates data representative of an initial set of splits for providing at least one of fuel and air to at least one combustor in the gas turbine engine. A gas turbine engine model module generates data representative of at least one engine operating condition. A first split calculation module generates data representative of at least one set of active control splits to control the engine in a first combustion mode, using as an input the initial split data. A second split calculation module generates data representative of at least one set of passive control splits to control the engine in at least a second combustion mode. Transfer between combustion modes may be accomplished via use of at least one of the active control splits and the passive control splits.

Abstract: A neural network-based system for monitoring a turbine compressor. In various embodiments, the neural network-based system includes: at least one computing device configured to monitor a turbine compressor by performing actions including: comparing a monitoring output from a first artificial neural network (ANN) about the turbine compressor to a monitoring output from a second, distinct ANN about the turbine compressor; and predicting a probability of a malfunction in the turbine compressor based upon the comparison of the monitoring outputs from the first ANN and the second, distinct ANN.