Control and tuning of gas turbine combustion

A system comprising:

• a gas turbine having a combustion system;
• a control system operably connected to the gas turbine for controlling an operation thereof;
• and
• a combustion auto-tuner communicatively linked to the control system, the combustion auto-tuner comprising:
• an optimization system comprising:
• a model, the model comprising an empirical model that models the combustion system via statistically mapping inputs to outputs of an operation of the combustion system so to generate predicted values for the outputs at future times based on the inputs of the combustion system, the model comprising a type of model selected from the following list:
• a neural network, a support vector machine model, a random forest model, a decision trees model, a k-means model, a principal component analysis model, a gradient boost model, and a parametric equation fitting model;
• and
• an optimizer;
• sensors configured to measure the inputs and outputs of the operation of the combustion system, the outputs of the combustion system comprising at least one controlled variable, and the inputs of the combustion system comprising disturbance variables and manipulated variables;
• wherein the model comprises a representation of a relationship between (a) the manipulated variables and the disturbance variables and (b) the at least one controlled variable of the combustion system;
• and
• wherein the optimized control solution for the combustion system comprises a setpoint value for at least one of the manipulated variable;
• a hardware processor;
• and
• a machine-readable storage medium on which is stored instructions that cause the hardware processor to execute a tuning process for tuning the operation of the combustion system, wherein the machine-readable storage medium comprises instructions that cause the hardware processor to execute a model training process;
• wherein the model training process comprises:
• obtaining additional data for inclusion within an original training dataset in order to create a revised training dataset, the additional data comprising measured values of the inputs and outputs by the sensors during a selected period of operation of the combustion system;
• and
• training the model of the optimization system pursuant to the revised training dataset;
• wherein the tuning process comprises the steps of:
• receiving current measurements from the sensors for the inputs and outputs;
• given the current measurements received from the sensors, using the optimization system to calculate an optimized control solution for the combustion system;
• and
• communicating the optimized control solution to the control system;
• and
• wherein the step of obtaining the additional data comprises an automated learning mode that includes:
• analyzing the original training dataset to determine at least one data need;
• generating a design of experiment for acquiring the at least one data need;
• monitoring the operation of the gas turbine for determining an opportunity to gather the at least one data need pursuant to the generated design of experiment;
• and
• communicating a prompt to the gas turbine when the opportunity to gather the at least one data need is determined;
• wherein the prompt describes a change to a first one of the manipulated variables in accordance with the design of experiment.