초록 ▼

A method for optimizing a generation of an output level over a selected operating period by a power block, wherein the power block comprises multiple gas turbines for collectively generating the output level. The control method may include: receiving current state data regarding measured operating p

A method for optimizing a generation of an output level over a selected operating period by a power block, wherein the power block comprises multiple gas turbines for collectively generating the output level. The control method may include: receiving current state data regarding measured operating parameters for each of the gas turbines of the power block; based on the current state data, defining competing operating modes for the power block; based on each of the competing operating modes, deriving a predicted value for a performance parameter regarding the operation of the power block over the selected operating period; determining a cost function and, pursuant thereto, evaluating the operation of the power block based on the predicted value of the performance parameter so to determine a projected cost; and comparing the projected costs from each of the optimized operating modes so to select therefrom an optimized operating mode.

대표청구항 ▼

1. A computer-implemented method for optimizing a generation of an output level over a selected operating period by a power block, wherein the power block comprises multiple gas turbines for collectively generating the output level, the control method including the steps of: receiving current state

1. A computer-implemented method for optimizing a generation of an output level over a selected operating period by a power block, wherein the power block comprises multiple gas turbines for collectively generating the output level, the control method including the steps of: receiving current state data regarding measured operating parameters for each of the gas turbines of the power block;wherein the measured operating parameters comprise clearance data for each of the multiple gas turbines, wherein the clearance data comprises measured distances between rotating and stationary components positioned along a hot gas path of the gas turbines;wherein the measured operating parameters comprise a rotor speed and a surge margin for a compressor of each of the gas turbines;based on the current state data, defining competing operating modes for the power block, wherein each of the competing operating modes comprises a unique generating configuration for the power block;based on the generating configurations of each of the competing operating modes, deriving a predicted value for a performance parameter regarding the operation of the power block over the selected operating period;determining a cost function and, pursuant thereto, evaluating the operation of the power block based on the predicted value of the performance parameter so to determine a projected cost;comparing the projected costs from each of the competing operating modes so to select therefrom an optimized operating mode;actuating one or more mechanical control devices at the multiple gas turbines so to affect control of the multiple gas turbines pursuant to the optimized operating mode;wherein the control method is implemented by a block controller communicatively linked to each of the multiple gas turbines;storing the current state data for retrieval by an analytics component of the block controller, and designating the stored current state data as historical state data;wherein the measured operating parameters of the current and the historical state data comprise a record of process inputs versus process outputs for each of the multiple gas turbines; andwherein the block controller comprises a model-free adaptive controller inclusive of a neural network, the model-free adaptive controller being configured to correlate the measured process inputs to the measured process outputs of the record. 2. The computer-implemented method according to claim 1, wherein at least a plurality of the multiple gas turbines of the power block comprise a remote location relative to the block controller; and wherein the selected operating period comprises a future market period; andwherein the control method is implemented by a processor of the block controller pursuant to instructions stored in a memory of the block controller. 3. The computer-implemented method according to claim 1, wherein the unique generating configuration comprises a power-sharing arrangement between the multiple gas turbines. 4. The computer-implemented method according to claim 3, wherein the power-sharing arrangement comprises an apportionment schedule of the output level among the multiple gas turbines of the power block. 5. The computer-implemented method according to claim 3, wherein the unique generating configuration further comprises a modulated coolant flow within a hot gas path of at least one of the multiple gas turbines. 6. The computer-implemented method according to claim 3, wherein the unique generating configuration comprises a modulated IGV setting within a compressor of at least one of the multiple gas turbines. 7. The computer-implemented method according to claim 1, wherein the competing operating modes include varying a value of an operating parameter over a range. 8. The computer-implemented method according to claim 1, further comprising the step of determining from the current state data a degree of degradation for each of the multiple gas turbines; wherein the step of defining the competing operating modes for the power block is based on the degree of degradation determined for each of the multiple gas turbines. 9. The computer-implemented method according to claim 8, wherein the model-free adaptive controller is configured to correlate the process inputs to the process outputs so to determine the degree of degradation of each of the multiple gas turbines. 10. The computer-implemented method according to claim 9, wherein the process inputs comprise at least one of a number of startups and a number of hours of operation for the gas turbines, and the process outputs comprise at least one of a heat rate for the gas turbines. 11. The computer-implemented method according to claim 9, wherein the degree of degradation for the gas turbines is used to define the competing operating modes such that the gas turbines judged to have higher degrees of degradation are biased toward receiving lower apportionments of the output level, and the gas turbines judged to have lower degrees of degradation are biased toward receiving higher apportionments of the output level. 12. The computer-implemented method according to claim 9, wherein the degree of degradation comprises a clearance threshold and a surge margin threshold; wherein the degree of degradation for the gas turbines is used to define the competing operating modes such that the gas turbines determined to exceed either one of the clearance and the surge margin thresholds are biased towards receiving lower apportionments of the output level. 13. The computer-implemented method according to claim 9, wherein the degree of degradation comprises a clearance threshold and a surge margin threshold; wherein the degree of degradation for the gas turbines is used to define the competing operating modes such that the gas turbines determined to exceed either one of the clearance and the surge margin thresholds are biased towards receiving at least one of: a modulated coolant flow within a hot gas path; and a modulated IGV setting within a compressor of at least one of the multiple gas turbines. 14. The computer-implemented method according to claim 9, wherein the optimized operating mode comprises a generating configuration in which one or more of the multiple gas turbines operates at a peak load and one or more of the multiple gas turbines operate at a turndown load so to affect a more balanced power sharing across the gas turbines of the power block. 15. The computer-implemented method according to claim 14, wherein the cost function comprises a summation of losses across the power block for the selected operating period; and wherein the losses comprise costs associated performance degradation, expended useful part-life, and fuel consumption.