Method and system for controlling a turbine engine

Abstract

Methods and systems are provided for controlling a turbine engine. An optimization target is selected for the engine (412). A power factor is determined based on the optimization target (410). The command sets a power level based on the power factor (414). Virtual data generated in real-time by a dynamic model (420) of the engine is processed. The virtual data is indicative of a response of the engine to the power level. A life factor of at least one component of the engine dependent on the power level is determined (416). A remaining useful life of the engine component is determined in real time based on the determined life factor and the processed virtual data (428). The method allows the operation of the engine to be controlled in real-time to meet the selected optimization goal in view of varying load conditions of the engine and a desired life goal of engine components.

Description

Background Art

[0001] The disclosed embodiments relate generally to the field of turbomachinery, such as turbine engines, and more particularly to methods and systems for controlling turbine engines.

[0002] Turbine machinery performance typically degrades over time. A control system provides functionality that allows for control and analysis of a turbine engine. For example, a control system may include sensors, controllers, computer devices, and the like that combine to acquire, process, and store data for controlling the turbine engine. The following are examples of patent documents that disclose certain known control systems related to turbine engines: WO2013 / 014202A1, “Gas Turbine Life Prediction and Optimization Device and Method”; WO2014 / 143187A1, “Lifing and Performance Optimization Limit Management for TurbineEngine”; and US10,452,041B2, “Gas TurbineDispatch Optimizer Real-Time Command and Operations”. Summary of the Invention

[0003] In one aspect, a computer-implemented method for controlling the operation of a turbine engine is provided. The method allows selection of an optimization objective from a menu of predetermined optimization objectives for the turbine engine, for example, via a user interface. Based on the selected optimization objective for the turbine engine, a power factor is determined for the turbine engine. A power command is issued to the turbine engine, wherein the power command sets a power level for operating the turbine engine, and wherein the power level is based on the determined power factor. Virtual data generated in real time by a dynamic model of the turbine engine is processed. The virtual data indicates a response of the turbine engine to the power level setting of the turbine engine. A life factor of at least one component of the turbine engine that is dependent on the power level setting of the turbine engine is determined. Based on the determined life factor and the processed virtual data, a remaining useful life of at least one component of the turbine engine that is dependent on the power level setting of the turbine engine is determined in real time. The method further allows real-time control of the operation of the turbine engine, for example, via a computer processor. The control is configured to meet the selected optimization objective in light of varying load conditions of the turbine engine and further in light of a desired life target for the at least one component of the turbine engine.

[0004] In another aspect, a system includes a turbine engine. A user interface is configured to select an optimization objective from a menu of predetermined optimization objectives for the turbine engine. The system also includes a dynamic model of the turbine engine and a control system comprising a computer processor. The control system is operably coupled to the user interface and the dynamic model of the turbine engine. The computer processor is configured to: determine a power factor for the turbine engine based on the optimization objective selected for the turbine engine; issue a power command to the turbine engine, the power command setting a power level for operating the turbine engine based on the determined power factor; process virtual data generated by the dynamic model of the turbine engine, the virtual data indicating a response of the turbine engine to the power level setting of the turbine engine; determine a life factor for at least one component of the turbine engine that is dependent on the power level setting of the turbine engine; determine, in real time, a remaining useful life of at least one component of the turbine engine that is dependent on the power level setting of the turbine engine based on the determined life factor and the processed virtual data; and control operation of the turbine engine in real time, the control being configured to meet the selected optimization objective in view of varying load conditions of the turbine engine and further in view of an expected useful life target for the at least one component of the turbine engine.

[0005] In yet another aspect, a computer-implemented method for controlling a turbine engine is provided. The method includes a non-transitory computer-readable medium programmed with computer-readable code such that, when a computer processor executes the computer-readable code, the computer processor performs the following steps: determining a power factor for the turbine engine based on an optimization objective selected for the turbine engine, the optimization objective selected from a menu of predetermined optimization objectives for the turbine engine; issuing a power command to the turbine engine, the power command setting a power level for operating the turbine engine, the power level based on the determined power factor; processing virtual data generated in real time by a dynamic model of the turbine engine, the virtual data indicating a response of the turbine engine to the power level setting of the turbine engine; determining in real time a remaining useful life of at least one component of the turbine engine dependent on the power level setting of the turbine engine based on the determined life factor and the processed virtual data; and controlling, by the computer processor, operation of the turbine engine in real time, the control being configured to meet the selected optimization objective in view of varying load conditions of the turbine engine and further in view of an expected useful life target for the at least one component of the turbine engine.

[0006] The foregoing has generally outlined some of the technical features of the present disclosure so that those skilled in the art may better understand the detailed description below. Other features and advantages of the present disclosure that form the subject matter of the claims will be described below. Those skilled in the art will understand that they can easily use the disclosed concepts and specific embodiments as a basis to modify or design other structures for achieving the same purpose of the present disclosure. Those skilled in the art will also recognize that such equivalent constructions do not depart from the spirit and scope of the broadest form of the present disclosure.

[0007] Furthermore, before describing the following detailed description, it should be understood that various definitions of certain words and phrases are provided throughout this patent document, and those of ordinary skill in the art will understand that these definitions apply in many, if not most, instances to prior as well as future uses of these defined words and phrases. Although some terms can include a wide variety of embodiments, the appended claims may expressly limit these terms to specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a schematic diagram of one example of a turbomachine, such as a turbine engine, that may benefit from the disclosed embodiments of methods and systems for controlling a turbine engine.

[0009] Figure 2 is a flow chart illustrating example steps associated with one example embodiment of the disclosed method.

[0010] Figure 3 is a block diagram illustrating control concepts that may be embodied in the disclosed embodiments.

[0011] Figure 4 is a partial block diagram representation of exemplary structural and / or operational relationships that may be involved in the disclosed embodiments.

[0012] Figure 5 is an example graph of life optimization and engine power level within a range of turbine temperature extremes ΔT.

[0013] Figure 6 yes Figure 5 An example diagram of life optimization and engine power level is shown, and also shows how the optimization space varies with ambient atmospheric conditions (such as ambient temperature, etc.).

[0014] Figure 7 The variation of turbine engine relative power with ambient temperature is shown for various example cases of corresponding percentages of rated load. DETAILED DESCRIPTION

[0015] Turbine engine components may degrade during their operating life due to a variety of factors. The present inventors have recognized that today's turbine engines are often required to operate under widely varying load conditions, and therefore conventional methods for performing life analysis of engine components (e.g., utilizing predefined duty cycle curves) are becoming increasingly unrepresentative.

[0016] Health models (e.g., which can indicate damage accumulation) and life models have been used to predict the cumulative damage and operational service life of such components. Typically, the output of the health model is used ex post (after an event has occurred) to attempt to characterize the cumulative damage associated with the components of the turbine engine so that maintenance, repairs, and / or overhauls can be appropriately planned. That is, traditionally, the real-time output of such health models or life models has not been used to control the turbine engine in real time. The inventors have recognized that utilizing virtual data generated in real time facilitates real-time control of the turbine engine so that, for example, component service life can be appropriately maximized and, in turn, component damage can be appropriately minimized despite the widely varying load conditions to which the turbine engine may be subjected.

[0017] In light of at least the foregoing considerations, the present inventors have disclosed embodiments of systems and methods for controlling turbine engines that, for example, take into account actual environmental and actual operating conditions (which can vary significantly depending on the application and, even for the same application, such as power generation, mechanical drive, etc., can vary significantly depending on the customer). Consequently, the disclosed embodiments can more accurately and consistently estimate the consumed life of, for example, turbine engine components exposed to thermomechanical loads. Furthermore, the disclosed embodiments can perform life estimation and subsequent prediction of remaining useful life for turbine engine components in real time, which in turn facilitates implementation of real-time optimization methods that can provide users with more confident decisions regarding the utilization of their turbomachinery assets.

[0018] Before explaining the disclosed embodiments in detail, it should be understood that the disclosed embodiments are not limited in their application to the details of construction and arrangement of components set forth in this specification or illustrated in the following drawings. The disclosed embodiments can be practiced or carried out in various ways. Furthermore, it should be understood that the phraseology and terminology used herein are for descriptive purposes only and should not be construed as limiting.

[0019] Various techniques related to the disclosed embodiments will now be described with reference to the accompanying drawings, in which the same reference numerals represent the same elements throughout. The drawings discussed below and the various embodiments used to describe the principles of the present disclosure in this patent document are intended to be illustrative only and should not be construed in any way to limit the scope of the present disclosure. Those skilled in the art will appreciate that the principles of the present disclosure can be implemented in any suitably arranged device. It should be understood that the functions described as being performed by certain system elements can be performed by multiple elements. Similarly, for example, an element can be configured to perform the functions described as being performed by multiple elements. Multiple innovative teachings of the present application will be described with reference to exemplary, non-limiting embodiments.

[0020] It should be understood that, unless expressly limited in some examples, the words or phrases used in the present invention should be interpreted broadly. For example, the terms "include", "have" and "include" and their derivatives are meant to include without limitation. The singular forms "a", "an" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. In addition, the term "and / or" used in the present invention refers to and covers any and all possible combinations of one or more of the relevant listed items. The term "or" is inclusive, meaning and / or, unless the context clearly indicates otherwise. The phrases "associated with..." and "associated with it" and their derivatives may mean including, included within, interconnected with, including, included within, connected to or connected with, connected to or connected with, communicable with, collaborate with, interlaced, juxtaposed, close to, bound to or bound with, having, having the characteristics of, etc. In addition, although multiple embodiments or configurations may be described herein, any features, methods, steps, components, etc. described with respect to one embodiment are equally applicable to other embodiments without specific statements to the contrary.

[0021] In addition, although the terms "first," "second," "third," etc. may be used to refer to various elements, information, functions, or actions in the present invention, these elements, information, functions, or actions should not be limited by these terms. Instead, these numerical adjectives are used to distinguish between different elements, information, functions, or actions. For example, a first element, information, function, or action may be referred to as a second element, information, function, or action, and similarly, a second element, information, function, or action may be referred to as a first element, information, function, or action without departing from the scope of this disclosure.

[0022] Additionally, unless the context clearly indicates otherwise, the term "adjacent" can refer to an element being relatively close to another element, but not in contact with it, or that the element is in contact with another part. Furthermore, unless otherwise clearly indicated, the phrase "based on" is intended to mean "based at least in part on." The terms "about" or "substantially" or similar terms are intended to encompass variations in value that are within normal industry manufacturing tolerances for that dimension. If no industry standard is available, a variation of 20% is considered within the meaning of these terms unless otherwise indicated.

[0023] Note that while the present disclosure includes descriptions in the context of fully functional systems and / or series of actions, those skilled in the art will appreciate that at least portions of the mechanisms of the present disclosure and / or described actions can be distributed in the form of computer / processor executable instructions (e.g., software / firmware applications) contained within a storage device corresponding to any form of non-transitory machine-usable, computer-usable, or computer-readable media in various forms (e.g., flash memory, SSD, hard drive). Computer / processor executable instructions can include routines, subroutines, programs, applications, modules, libraries, and the like. Furthermore, it should be understood that computer / processor executable instructions can correspond to, and / or be generated by, source code, byte code, runtime code, machine code, assembly, Java, Javascript, Python, Rust, Swift, Go, C, C#, C++, or any other form of code that can be programmed / configured to cause at least one processor to perform the actions and features described herein. Furthermore, the results of the described / claimed processes or functions can be stored in a computer-readable medium, displayed on a display device, and the like.

[0024] It should be understood that the actions associated with the above-described methods, features, and functions (in addition to any manual actions described) can be performed by one or more data processing systems via operation of one or more processors. Thus, it should be understood that when reference is made to a data processing system or control system, the system can be implemented across several data processing systems organized in a distributed system that communicate with each other directly or via a network.

[0025] As used herein, a processor or processor module corresponds to any electronic device configured to process data via hardware circuitry, software, and / or firmware. For example, the processor described herein may correspond to one or more (or a combination of) a microprocessor, a CPU, or any other integrated circuit (IC), or other type of circuit capable of processing data in a data processing system. As previously discussed, a processor described or claimed as configured to perform a particular described / claimed process or function may correspond to a CPU that executes computer / processor-executable instructions stored in a memory in the form of software to implement the described / claimed process or function. However, it should also be understood that such a processor may correspond to an IC that is hardwired with processing circuitry (e.g., an FPGA or ASIC IC) to perform the described / claimed process or function. Furthermore, it should be understood that references to a processor may include multiple physical processors or cores configured to perform the functions described herein. Furthermore, it should be understood that a data processing system and / or processor may correspond to a controller, including a programmable logic controller (PLC), that is operably configured to control at least one operation.

[0026] Furthermore, it should be understood that a processor or processor module described or claimed as being configured to perform a particular described / claimed process or function may correspond to a combination of a processor and executable instructions (e.g., software / firmware applications) loaded / installed into a described memory (volatile and / or non-volatile), said executable instructions being currently executed by the processor and / or available for execution by the processor to cause the processor to perform the described / claimed process or function. Thus, a processor that is powered off or is executing other software but has said software loaded / stored in a storage device (e.g., flash memory, SSD, or hard drive) operatively connected thereto in a manner that can be executed by the processor (when activated by a user, hardware, and / or other software) may also correspond to a described / claimed processor that is operatively configured to perform the particular processes and functions described / claimed herein.

[0027] Those skilled in the art will appreciate that the hardware and software described in conjunction with the disclosed embodiments may vary for specific implementations. The examples described are provided for illustrative purposes only and are not meant to imply architectural limitations regarding the present disclosure. Furthermore, those skilled in the art will recognize that, for the sake of simplicity and clarity, the present invention does not depict or describe the entire structure and operation of all data processing systems applicable to the present disclosure. On the contrary, only data processing systems that are unique to the present disclosure or necessary for understanding the present disclosure are depicted and described. The remaining structure and operation of the data processing system may conform to any of the various current implementations and practices known in the art.

[0028] Figure 1A non-limiting example of a turbomachine, such as a turbine engine 100, is shown that can benefit from the disclosed embodiments for controlling a turbine engine. It should be understood that the disclosed embodiments are not limited to any particular type of turbomachine. The turbine engine 100 includes an inlet 12, a compressor 101, a combustor 102, and a turbine 103 arranged in series flow path, which are generally arranged in series flow path and generally arranged along a longitudinal or rotational axis 20. The turbine engine 100 also includes a shaft 22 that is rotatable about the rotational axis 20 and extends longitudinally through the turbine engine 100. The shaft 22 drivingly connects the turbine 103 to the compressor 101.

[0029] Unless otherwise indicated, the terms upstream and downstream refer to the direction of flow of air and / or working gas through the engine. The terms "forward" and "rearward" refer to the overall gas flow through the engine. The terms axial, radial, and circumferential are with reference to the engine's axis of rotation 20.

[0030] During operation of turbine engine 100, air flow 24 entering through air inlet 12 is compressed by compressor 101 and delivered to combustor 102, which includes combustor section 16. Combustor section 16 includes a combustor plenum 26, one or more combustion chambers 28, which may be defined by a double-walled tank 27, and at least one combustor 30 secured to each combustion chamber 28. Combustion chamber 28 and combustor 30 are located within combustor plenum 26. Compressed air passing through compressor 12 enters diffuser 32 and is discharged from diffuser 32 into combustor plenum 26. A portion of the air from combustor plenum 26 enters combustor 30 and mixes with gaseous or liquid fuel. The air / fuel mixture is then combusted, and combustion gases 34, or working gases from the combustion, are directed to turbine 103 via transition duct 35.

[0031] Turbine 103 includes a plurality of blade-carrying disks 36 attached to shaft 22. In this example, two disks 36 each carry an annular array of turbine blades 38. However, the number of blade-carrying disks may vary, for example, only one disk or more than two disks. Furthermore, guide vanes 40, which are fixed to a stator 42 of turbine engine 100, are disposed between turbine blades 38. Inlet guide vanes 44 are disposed between the outlet of combustion chamber 28 and the forward turbine blades 38.

[0032] Combustion gases from combustion chamber 28 enter turbine 103 and drive turbine blades 38, which in turn rotate shaft 22. Guide vanes 40, 44 are used to optimize the angle at which the combustion or working gas impinges on turbine blades 38. Compressor 101 includes a series of axial guide vane stages 46 and rotor blade stages 48.

[0033] Figure 1The non-limiting example of a turbomachinery machine shown also includes a controller or control system 110 operatively coupled to the turbine engine 100. The control system 110 includes one or more processors or processing units 102, a memory 104, and computer-readable media, such as non-transitory machine-usable media. The control system 110 constitutes a computing system that executes programs and operations to control the operation of the turbine engine 100 using sensor inputs, scheduling algorithms, control models, and / or commands from a human operator. The programs and functions performed by the control system 110 may include sensing and / or modeling operating parameters, operating boundaries, applying operating boundary models, applying scheduling algorithms, and applying boundary control logic, among other items.

[0034] Figure 2 Flowchart 200 depicts example steps (e.g., involving structural and / or operational relationships) associated with an example embodiment of the disclosed computer-implemented method for controlling operation of a turbine engine. Following a start step 202, step 204 allows for selecting an optimization objective from a menu of predetermined optimization objectives for the turbine engine, for example, via a user interface. Step 206 allows for determining a power factor of the turbine engine based on the selected optimization objective for the turbine engine. Step 208 allows for issuing a power command to the turbine engine, wherein the power command sets a power level for operating the turbine engine, and wherein the power level is based on the determined power factor. Step 210 allows for processing virtual data generated in real time by a dynamic model of the turbine engine. The virtual data indicates a response of the turbine engine to the power level setting of the turbine engine. The response may include a transient response of the turbine engine. Step 212 allows for determining a life factor of at least one component of the turbine engine that is dependent on the power level setting of the turbine engine. Based on the determined life factor and the processed virtual data, step 214 allows for determining in real time a remaining useful life of at least one component of the turbine engine that is dependent on the power level setting of the turbine engine. Step 216 allows for real-time control of the operation of the turbine engine, for example by a computer processor, before returning to step 218. The control is configured to meet the selected optimization objective in view of varying load conditions of the turbine engine and further in view of the expected life objective of the at least one component of the turbine engine.

[0035] In one non-limiting embodiment, the predetermined optimization objectives may include maximization of the power generated by the turbine engine, maximization of the remaining useful life of at least one component of the turbine engine, and a mixed optimization of the power generated by the turbine engine and the remaining useful life of at least one component of the turbine engine.

[0036] In one non-limiting embodiment, the method includes processing data indicative of ambient atmospheric conditions (eg, ambient temperature, altitude, and relative humidity), and wherein determining the power factor of the turbine engine is further based on the data indicative of the ambient atmospheric conditions.

[0037] In one non-limiting embodiment, controlling operation of a turbine engine in real time via a computer processor includes determining a temperature limit offset relative to a temperature limit set point, the temperature limit offset based on ambient atmospheric conditions and a selected optimization objective.

[0038] In one non-limiting embodiment, controlling operation of a turbine engine in real time via a computer processor includes iteratively issuing a series of power commands to the turbine engine. The series of power commands can be configured to set respective power levels that are adjusted in view of varying load conditions of the turbine engine and further in view of a desired life target of at least one component of the turbine engine to meet a selected optimization objective.

[0039] Figure 3 302 is a block diagram illustrating an exemplary control concept in the disclosed embodiments. As described above, the disclosed embodiments are useful for optimizing component life versus turbine engine power, for example, when turbine engine operation may be limited by operating temperature (e.g., due to high ambient temperatures, etc.). For example, when a turbine engine is operating at high ambient temperatures, turbine engine power may be limited by a turbine limit temperature (TLT) setpoint (block 302). For example, to generate power exceeding a specified control limit, the turbine engine may be overfired by a certain amount (ΔTLT) relative to the TLT setpoint. That is, ΔTLT generally represents a difference relative to the TLT setpoint.

[0040] In the disclosed embodiments, as described above, an operator of a given turbine engine may selectively operate the turbine engine by selecting a corresponding one of predetermined optimization objectives, such as any one of: maximization of the power generated by the turbine engine; maximization of the remaining useful life of at least one component of the turbine engine; and a mixed optimization of the power generated by the turbine engine and the remaining useful life of at least one component of the turbine engine.

[0041] For each optimization objective, there is a unique functional relationship with ΔTLT. Because the typical engine rating curve (power characteristics) of a turbine engine is generally inversely proportional to the ambient temperature (e.g., as the ambient temperature increases, the power decreases), in addition to defining an appropriate ΔTLT functional relationship for each optimization objective, the optimization space can also take into account ambient atmospheric conditions, such as ambient temperature, etc. As an example, the optimization space can be represented in 2D matrix form. Figure 3In the block diagram shown, the TLT offset (block 304) represents an adjustment relative to the TLT setpoint, characterized as a function of ambient atmospheric conditions and a corresponding optimization objective selected by the operator. To implement the optimization process, the estimated TLT offset is introduced into a temperature limiter control loop 306 to, for example, generate (e.g., via a proportional-integral (PI) control module 305) an appropriate fuel flow demand (FFDEM) for the turbine engine (TE). That is, in addition to the selected optimization objective (e.g., power increase versus life extension), the optimization process can also be configured to determine an appropriate TLT offset based on ambient atmospheric conditions.

[0042] Figure 4 It is a block diagram representation of exemplary structural and / or operational relationships involved in the disclosed embodiments. Figure 4 The block 400 in FIG. 1 represents a block configured to implement the above Figure 2 4. In the context of FIG. 4, block 400 represents a control system subcomponent of a method described herein. That is, block 400 represents a component that is part of a larger component of a control system for a turbine engine. Hereinafter, the block is simply referred to as control system 400, with the understanding that the block represents only a portion of the control system for the turbine engine. In an example embodiment, control system 400 includes a power factor processor module 410 configured to determine a power factor for the turbine engine based on an optimization objective that can be selected by an operator of the turbine engine via a user interface 412. The determined power factor is provided to a power command processor module 414 configured to issue a power command to set a power level for operating the turbine engine, wherein the power level is based on the power factor determined by power factor processor module 410. A life factor processor module 416 is configured to determine a life factor (K) of at least one component of the turbine engine that is set depending on the power level of the turbine engine.

[0043] The determined power factor is further provided to an optimizer processor module 418 along with data indicative of ambient atmospheric conditions (block 415), which is configured to estimate the power factor above in the Figure 3 The TLT offset discussed in the context of FIG. 3 (ie, in the context of the temperature limiter control loop 306 ).

[0044] Continuing with the discussion of control system 400, in one example embodiment, control system 400 includes a real-time dynamic model 420 of a turbine engine. As will be appreciated by those skilled in the art, a dynamic model can provide a simplified representation of a real-world entity (e.g., a turbine engine) by utilizing functional relationships, such as computer code, and can be used to assess the time-varying behavior of the turbine engine. As will be further appreciated by those skilled in the art, various operations in a computational or other process are described in real time or instantaneously, ensuring responses within a specified time (e.g., on a time scale of milliseconds) in order to, for example, appropriately analyze and react to the time-varying behavior of the turbine engine.

[0045] In one example embodiment, real-time dynamic model 420 can be configured to generate virtual data indicating the response of the turbine engine to a power level setting. The virtual data generated by real-time dynamic model 420 can be processed in a life counter (e.g., which can be configured in processor module 422) to determine an effective basic hour (EBH) count for at least one component of the turbine engine. The EBH count calculated by life counter 422 is in turn processed by a remaining equivalent basic hour (REBH) counter (e.g., which can be configured in processor module 424). The REBH count represents the difference between the design basic hour (DBH) count and the EBH count obtained from storage module 426. Processor module 428 calculates the remaining useful life (RUL) of at least one component of the turbine engine by calculating the product of the life factor (K) and the REBH count.

[0046] Figure 5 Corresponding example curves for life optimization 502 within a range of turbine temperature limits ΔT and power level optimization 504 within a range of turbine temperature limits ΔT are shown. These graphs allow visualization of an exemplary interaction between life optimization and power level optimization within a range of turbine temperature limits ΔT. For example, over the range ΔT, there exists a value ΔT_min, as indicated by the point labeled life_max, at which the operational life of a given component can be maximized. Conversely, over the range ΔT, there exists a value ΔT_max, as indicated by the point labeled power_max, at which the power level generated by the turbine engine is maximized. In this example, the intersection of the two curves 502 and 504 at ΔT_optimum represents a point indicating a mixed optimization of both component life and the power level generated by the turbine engine. That is, a unique point where both component life and power level are mutually optimized.

[0047] Figure 6 Built on Figure 5 The concept shown is based on the above and the influence of ambient atmospheric conditions (eg ambient temperature) on the interaction of life optimization and power level optimization within the range ΔT of turbine temperature limits is introduced into the optimization space. Figure 6 As will be appreciated from the preceding text, the optimization space can be represented by a 2D matrix to take into account ambient atmospheric conditions (e.g., ambient temperature). This allows for consideration of the fact that a turbine engine will generally experience a decrease in power as the ambient temperature increases, or conversely, an increase in power as the ambient temperature decreases, as shown in FIG. Figure 7 , which shows the variation of relative turbine engine power with ambient temperature for various example cases of corresponding percentages of rated load.

[0048] In operation, the disclosed embodiments are effective for performing real-time gas turbine optimization, which provides users with more confident decisions regarding the appropriate utilization of their engines considering conflicting objectives (eg, engine power versus component life).

[0049] In operation, the disclosed embodiments are effective for implementing life counting calculations that are readily applicable to a wide range of thermo-mechanical damage modes and various hot gas path components.

[0050] In operation, the disclosed embodiments are effective for real-time execution in the system, taking into account not only non-base load conditions (e.g., partial load under steady-state conditions), but also transient conditions. As such, the disclosed embodiments can provide more accurate lifetime consumption calculations than is possible in certain known implementations.

[0051] In operation, the disclosed embodiments provide, by way of example: superior predictive capabilities based on degradation modeling (e.g., linear models can be augmented with nonlinear regression modeling methods for various degradation modes); allowing users to configure and operate their engines in a more optimal manner, avoiding overly conservative (and more expensive) operation / maintenance techniques.

[0052] In operation, the disclosed embodiments allow for real-time personalized optimization of a fleet of assets by integrating our optimization logic into existing control loops.

[0053] In operation, the disclosed embodiments allow estimation of life consumption during transient operation (e.g., from slow transient to fast transient), making smart use of virtual data such as may be generated by a real-time engine model or a digital twin of the engine.

[0054] Although at least one exemplary embodiment of the present disclosure has been described in detail, those skilled in the art will understand that they can make various changes, substitutions, alterations, and improvements as disclosed herein without departing from the scope of the disclosure in its broadest form.

[0055] Nothing in this application should be construed as implying that any particular element, step, act, or function is essential to the scope of a claim. The scope of patented subject matter is limited only by the allowed claims. Furthermore, unless the specific phrase "means for..." is followed by a participle, these claims are not intended to invoke a means-plus-function claim construction.

Claims

1. A computer-implemented method for controlling operation of a turbine engine, the method comprising: selecting, via a user interface, an optimization objective from a menu of predetermined optimization objectives for the turbine engine; determining a power factor of the turbine engine based on the optimization objective selected for the turbine engine; issuing a power command to the turbine engine, the power command setting a power level for operating the turbine engine, the power level being based on the determined power factor; processing virtual data generated in real time by a dynamic model of the turbine engine, the virtual data indicating a response of the turbine engine to a power level setting of the turbine engine; determining a life factor of at least one component of the turbine engine that is set in dependence on a power level of the turbine engine; determining, in real time, a remaining useful life of at least one component of the turbine engine depending on a power level setting of the turbine engine based on the determined life factor and the processed virtual data; as well as Operation of the turbine engine is controlled in real time by a computer processor, the control being configured to meet a selected optimization objective in view of varying load conditions of the turbine engine and further in view of an expected life objective of the at least one component of the turbine engine.

2. The method according to claim 1, wherein The predetermined optimization objective is selected from the group consisting of: maximization of the power generated by the turbine engine; maximization of the remaining useful life of the at least one component of the turbine engine; and a mixed optimization of the power generated by the turbine engine and the remaining useful life of the at least one component of the turbine engine.

3. The method of claim 1 or claim 2, further comprising processing data indicative of ambient atmospheric conditions, and wherein Determining the power factor of the turbine engine is also based on data indicative of the ambient atmospheric conditions.

4. The method according to claim 1 or 3, wherein The data indicative of the ambient atmospheric condition is selected from the group consisting of: ambient temperature, altitude, and relative humidity.

5. The method according to claim 1 or claim 3, wherein: Controlling operation of the turbine engine in real time via the computer processor includes determining a temperature limit offset relative to a temperature limit set point, the temperature limit offset being based on the ambient atmospheric conditions and a selected optimization objective.

6. The method according to claim 1 or claim 3, wherein: The virtual data indicative of a response of the turbine engine includes a transient response of the turbine engine.

7. The method according to claim 1 or claim 3, wherein: Real-time control of the operation of the turbine engine by the computer processor includes iteratively issuing a series of power commands to the turbine engine, the series of power commands setting respective power levels, the respective power levels being adjusted in view of the changing load conditions of the turbine engine and further in view of the expected life target of the at least one component of the turbine engine to meet a selected optimization target.

8. A system comprising: turbine engines; a user interface configured to select an optimization objective from a menu of predetermined optimization objectives for the turbine engine; a dynamic model of the turbine engine; a control system comprising a computer processor operatively coupled to the user interface and to a dynamic model of the turbine engine, the computer processor configured to: determining a power factor of the turbine engine based on an optimization objective selected for the turbine engine; issuing a power command to the turbine engine, the power command setting a power level for operating the turbine engine based on the determined power factor; processing virtual data generated by the dynamic model of the turbine engine, the virtual data indicative of a response of the turbine engine to the power level setting of the turbine engine; determining a life factor of at least one component of the turbine engine that is set in dependence on a power level of the turbine engine; determining, in real time, a remaining useful life of the at least one component of the turbine engine depending on a power level setting of the turbine engine based on the determined life factor and the processed virtual data; as well as Operation of the turbine engine is controlled in real time, the control being configured to meet a selected optimization objective in view of varying load conditions of the turbine engine and further in view of an expected life objective of the at least one component of the turbine engine.

9. The system according to claim 8, wherein: The optimization objective is selected from the group consisting of: maximization of the power generated by the turbine engine; maximization of the remaining useful life of the at least one component of the turbine engine; and a mixed optimization of the power generated by the turbine engine and the remaining useful life of the at least one component of the turbine engine.

10. A system according to claim 8 or claim 9, wherein: The computer processor is further configured to process data indicative of ambient atmospheric conditions, and wherein the power factor of the turbine engine is further based on the data indicative of the ambient atmospheric conditions.

11. A system according to claim 8 or claim 10, wherein: The data indicative of the ambient atmospheric condition is selected from the group consisting of: ambient temperature, altitude, and relative humidity.

12. A system according to claim 8 or claim 10, wherein: Controlling operation of the turbine engine in real time includes determining a temperature limit offset relative to a temperature limit set point based on the ambient atmospheric conditions and a selected optimization objective.

13. The system of claim 8 or claim 10, wherein: The virtual data indicative of a response of the turbine engine includes a transient response of the turbine engine.

14. The system of claim 8 or claim 10, wherein: Controlling the operation of the turbine engine in real time includes iteratively issuing a series of power commands to the turbine engine, the series of power commands setting respective power levels, the respective power levels being adjusted in view of the changing load conditions of the turbine engine and further in view of the expected life target of the at least one component of the turbine engine to meet a selected optimization target.

15. A computer-implemented method for controlling a turbine engine, the turbine engine comprising a non-transitory computer-readable medium programmed with computer-readable code such that when a computer processor executes the computer-readable code, the computer processor performs the following steps: determining a power factor of the turbine engine based on an optimization objective selected for the turbine engine, the optimization objective being selected from a menu of predetermined optimization objectives for the turbine engine; issuing a power command to the turbine engine, the power command setting a power level for operating the turbine engine, the power level being based on the determined power factor; processing virtual data generated in real time by a dynamic model of the turbine engine, the virtual data indicating a response of the turbine engine to a power level setting of the turbine engine; determining a life factor of at least one component of the turbine engine that is set in dependence on a power level of the turbine engine; determining, in real time, a remaining useful life of the at least one component of the turbine engine depending on a power level setting of the turbine engine based on the determined life factor and the processed virtual data; as well as Operation of the turbine engine is controlled in real time by a computer processor, the control being configured to meet a selected optimization objective in view of varying load conditions of the turbine engine and further in view of an expected life objective of the at least one component of the turbine engine.

16. The computer-implemented method of claim 15, wherein: The optimization objective is selected from the group consisting of: maximization of the power generated by the turbine engine; maximization of the remaining useful life of the at least one component of the turbine engine; and a mixed optimization of the power generated by the turbine engine and the remaining useful life of the at least one component of the turbine engine.

17. A computer-implemented method according to claim 15 or claim 16, wherein: The computer processor is further configured to process data indicative of ambient atmospheric conditions, and wherein the power factor of the turbine engine is further based on the data indicative of the ambient atmospheric conditions.

18. A computer-implemented method according to claim 15 or claim 17, wherein: The data indicative of the ambient atmospheric condition is selected from the group consisting of: ambient temperature, altitude, and relative humidity.

19. The computer-implemented method of claim 15 or claim 17, wherein: Controlling operation of the turbine engine in real time includes determining a temperature limit offset relative to a temperature limit set point, the temperature limit offset being based on the ambient atmospheric conditions and a selected optimization objective.

20. The computer-implemented method of claim 15 or claim 17, wherein: The virtual data indicative of a response of the turbine engine includes a transient response of the turbine engine.

21. The computer-implemented method of claim 15 or claim 17, wherein: Controlling the operation of the turbine engine in real time includes iteratively issuing a series of power commands to the turbine engine, the series of power commands having corresponding power levels, the corresponding power levels being adjusted in view of the changing load conditions of the turbine engine and further in view of the expected life target of the at least one component of the turbine engine to meet a selected optimization target.

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