System and method for improved frequency rate ride-through in power systems

Abstract

This application provides methods and systems for rapid load support in response to transient events in the power grid frequency spectrum. An exemplary power system may include a turbine, a generator coupled to the turbine, and a controller, wherein the generator is configured to supply power to the power grid, and the controller is configured to detect a power grid event, determine a rate of change of frequency (RCD) value, determine a predicted governor setpoint based on the RCD value, and initiate changes to at least one turbine operating parameter based on the predicted governor setpoint.

Description

Technical Field

[0001] This application and the resulting patents relate generally to power systems, and more specifically to improved frequency change rate crossing in gas turbine power systems. Background Technology

[0002] Many known power systems include several types of generating units, such as synchronous generating units and / or asynchronous generating units. A synchronous generating unit is one in which the output voltage waveform generated during operation is synchronized with the rotation of components within the generating unit (e.g., a prime mover). Synchronous generating units typically include rotating blocks that rotate within the generating unit to produce output power. Asynchronous generating units are those in which the output voltage waveform generated during operation does not necessarily have to be synchronized with the rotation of blocks within the generating unit, as asynchronous generating units may, for example, not include such rotating blocks. Examples of asynchronous generating units include solar or wind power generating units. At least some conventional power systems have adequately tolerated losses from one or more generating units or loads within the power system due to the presence of a large number of synchronous generating units distributed throughout the system.

[0003] More specifically, because synchronous generating units can include rotating blocks (e.g., prime movers and generators), losses or load losses in generating units within a larger power grid can be compensated by distributing insufficient or excessive power within the system to the remaining number of generating units that rotate with an inertia sufficient to absorb or “cross over” the losses (although the rotating blocks within each synchronous generating unit may rotate more slowly). However, in some cases, particularly for smaller grids, crossover may fail when large-frequency transient events occur because the operating state cannot be properly determined after the transient event has completed. For smaller grids, such as those providing approximately 500 megawatts (MW) of load capacity, the negative impacts of transient events such as sudden changes in grid frequency are amplified. Smaller grids are generally less stable than larger grids because the same amount of load change will result in a larger frequency change. Therefore, smaller grids tend to experience frequency changes more frequently than larger grids. This lack of stability can lead to grid outages and / or power losses. Therefore, systems and methods are needed to improve the power stability of the grid by enhancing the rate of frequency change crossover. Summary of the Invention

[0004] This application and the resulting patent provide an improved rate of change crossover in a gas turbine electric system. The system may include a turbine, a generator coupled to the turbine, and a controller, wherein the generator is configured to supply power to the grid, and the controller is configured to detect grid events, determine a rate of change (RCD) value, determine a predicted governor setpoint based on the RCD value, and initiate a change to at least one turbine operating parameter based on the predicted governor setpoint.

[0005] This application and the resulting patent also provide a method for a gas turbine to pass through an electrical grid event. The method may include detecting the electrical grid event by a controller, determining a frequency change rate value, determining a predicted governor setpoint based on the frequency change rate value, and initiating a change to at least one turbine operating parameter of the gas turbine based on the predicted governor setpoint.

[0006] This application and the resulting patent also provide a system for a gas turbine traversing an electrical grid event. The system may include a gas turbine, a generator coupled to the gas turbine, and a controller, wherein the generator is configured to supply power to the electrical grid, and the controller is configured to detect the electrical grid event, determine a frequency change rate value, determine an estimate of the electrical grid event based on the frequency change rate value, determine a predicted governor setpoint after the electrical grid event based on the estimated value of the electrical grid event, determine a target combustion mode using the predicted governor setpoint after the electrical grid event, and initiate a change in the air / fuel ratio based on the target mode.

[0007] These and other features and improvements of this application and the resulting patent will become apparent to those skilled in the art upon reading the following detailed description in conjunction with the accompanying drawings and claims. Attached Figure Description

[0008] Figure 1 This is a schematic diagram of an exemplary power system.

[0009] Figure 2 This is an exemplary processing flow for improved frequency change rate crossing, as may be described herein.

[0010] Figures 3 to 4 This is a schematic diagram showing various graphs related to determining factors used to improve the rate of change of frequency, as may be described in this article.

[0011] Figure 5 This is a schematic diagram illustrating the determination of the target strategy after detecting a transient event in the power grid frequency, as may be described in this article. Detailed Implementation

[0012] Referring now to the accompanying drawings, in which similar numbers in several views refer to similar elements. Figure 1 This is a schematic diagram of an power system 100. The power system 100 may include multiple generation units and multiple electrical loads connected to the generation units. It may include any number of generation units, loads, and other common power system components.

[0013] The power system 100 may include one or more electrical system components, such as a first electrical load 102a, a second electrical load 102b, and / or a third electrical load 102c. The power system 100 may also include one or more power generation units, such as a first power generation unit 104a, a second power generation unit 104b, and / or a third power generation unit 104c. In an illustrated embodiment, power generation units 104a-104c may be synchronously connected gas turbine power generation units. However, in other embodiments, power generation units 104a-104c may be any power generation unit including a rotating prime mover, such as a steam turbine power generation unit, a reciprocating engine power generation unit, a water turbine power generation unit, etc. In some embodiments, the power system 100 may include at least one power transmission and distribution system component 106, such as, for example, one or more transmission lines, one or more distribution lines, one or more transformers, one or more voltage regulators, etc. Thus, interconnected power transmission and distribution system components 106 facilitate the supply of power from power generation units 104a-104c to one or more electrical loads 102a-102c.

[0014] The power system 100 may optionally include an asynchronous power source 112, such as a wind and / or solar power system. The asynchronous power source 112 may be connected to the power transmission and distribution system component 106 via a power line such as an asynchronous power line 113, and may supply electrical energy to one or more electrical loads 102a-102c via the power transmission and distribution system component 106.

[0015] Some or all of the power generation units 104a-104c may include at least one controller and / or at least one sensor. For example, power generation unit 104a may include controller 114a and sensor 116a, power generation unit 104b may include controller 114b and sensor 116b, and power generation unit 104c may include controller 114c and sensor 116c. Each controller 114a-114c may include a processor and a non-transitory computer-readable storage communicatively coupled to the processor.

[0016] The power system 100 may include multiple event estimators 120a, 120b, and 120c. In various embodiments, each event estimator 120a-120c may include at least one processor and may be installed within a specific power generation unit 104a-104c. In some embodiments, each event estimator 120a-120c is not a separate hardware component, but rather embodied as software executing on a corresponding controller 114a-114c of each power generation unit 104a-104c. Furthermore, in some embodiments, each event estimator 120a-120c may be implemented on a separate computing device communicatively coupled to the corresponding controller 114a-114c of the corresponding power generation unit 104a-104c.

[0017] The power system 100 may include a network estimator 118. In various embodiments, the network estimator 118 may include at least one processor 152 coupled to at least one non-transitory computer-readable storage device 154. In some embodiments, the network estimator 118 may be implemented on a computing device such as a workstation computer, a personal computer, a tablet computer, or a smartphone.

[0018] Network estimator 118 can be communicatively coupled (e.g., via a communication network such as the Internet) to one or more data sources 150, such as one or more databases and / or database servers. Data source 150 can be online and / or offline data sources and may include or store various information associated with the power system 100, such as various status information. Network estimator 118 can also be communicatively coupled to each event estimator 120a-120c.

[0019] The status information received by the network estimator 118 via the data source 150 may include any status information associated with the power system 100, such as location information, timing information, and / or maintenance activity information, such as planned outage information for at least one of the generation units 104a-104c, electrical loads 102a-102c, power transmission and distribution system components 106, and / or asynchronous power sources 112. The status information may also include information describing the moment of inertia associated with each generation unit 104a-104c, the total moment of inertia associated with the generation units 104a-104c within the power system 100, and / or the proportion of power generated by the asynchronous power source 112 in the power system 100 at any given time. This status information may be transmitted over a computer network via at least one grid signal 122.

[0020] Status information can also be detected by one or more sensors within the power system 100, such as, for example, sensors 116a-116c, which can detect the operating status of each generator unit 104a-104c, such as rotational speed, temperature, output voltage, output current, output frequency, valve position, system identifier (e.g., serial number), and / or the fuel type of generator unit 104a-104c. Similarly, sensors (not shown) connected to the power transmission and distribution system component 106 can detect one or more of its characteristics, such as, for example, at least one of the following: fault type, location, occurrence time, and severity; voltage; current; frequency; and system identifier. Likewise, one or more sensors (not shown) connected to the electrical loads 102a-102c can detect their characteristics, such as, for example, at least one of the following: fault type, location, occurrence time, and severity; voltage; current; frequency; location; and / or system identifier.

[0021] The state information detected by one or more sensors (such as sensors 116a-116c) of the power system 100 can also be used by controllers 114a-114c to detect the occurrence of frequency change rate events and / or grid events within the power system 100. For example, if sensors 116a-116c detect a significant increase or decrease in the frequency or speed of the corresponding power generation unit 104a-104c, the corresponding controllers 114a-114c can determine that a frequency change rate event has occurred.

[0022] Therefore, network estimator 118 receives state information via grid signal 122 and determines or obtains at least one network characteristic representing the operating state of power system 100, such as, for example, at least one frequency characteristic of power system 100. More specifically, network estimator 118 uses the state information to generate at least one model of power system 100. For example, network estimator 118 may analyze the state information to generate a model of power system 100, such as a lookup table that associates multiple frequency change rate values ​​with one or more power system characteristics (such as one or more frequency characteristics). The model may therefore include and / or describe one or more characteristics of power system 100 and may represent one or more interactions between elements connected to power system 100, such as the interactions between generating units 104a-104c and electrical loads 102a-102c. Furthermore, network estimator 118 may send all or part of the model of power system 100, such as a model lookup table, to each event estimator 120a-120c.

[0023] The model of power system 100 can identify one or more characteristics of power system 100 and / or generation units 104a-104c, such as stable frequency, stable power, frequency peak, and / or frequency minimum. These characteristics can be based on the analysis of state information associated with power system 100. To this end, the model provided to each event estimator 120a-120c may include a lookup table that cross-references multiple frequency change rate values ​​with multiple characteristics, such as multiple stable frequencies, multiple stable power, multiple frequency peaks, and / or multiple frequency minimums. Typically, stable frequency and stable power are the “calm” or stable speed or frequency and output power of generation units 104a-104c after a grid event occurs and / or after the deployment of a master response to the frequency event and / or grid event change rate within power system 100. Similarly, a frequency minimum is the lowest output power frequency that occurs due to a grid event, while a frequency peak is the highest output power frequency that occurs due to a grid event. In an exemplary embodiment, the model can be transmitted to each event estimator 120a-120c via network signal 124, and each event estimator 120a-120c can store the model (including associated features) in memory, such as, for example, in a non-transitory computer-readable memory.

[0024] Network estimator 118 may periodically (e.g., every fifteen minutes, etc.) receive and / or collect state information to update the model of power system 100. The updated model may include updated characteristics associated with power system 100 and may be transmitted to one or more event estimators 120a-120c for storage. In various embodiments, network estimator 118 may receive feedback from one or more event estimators 120a-120c, such as feedback on estimated characteristics compared to actual or measured characteristics. For example, a particular event estimator 120a-120c may use a lookup table to estimate a particular frequency minimum based on a measured or sensed rate of change value. The particular event estimator 120a-120c may receive the actual frequency minimum occurring due to the rate of change of frequency events from sensors 116a-116c and may return the error or difference between the estimated frequency minimum and the actual frequency minimum as an error value to network estimator 118. Similarly, the actual lowest frequency point (instead of the error value, or something other than the error value) can be returned to the network estimator 118.

[0025] As used herein, the phrase "grid event" refers to a sudden change in the total electrical power consumed and / or generated by the power system. For example, a grid event can be associated with a sudden decrease in total generation or load within the power system due to, for example, the loss (or tripping) of one or more generating units, one or more asynchronous sources, and / or one or more loads. Similarly, as used herein, a "source suppression grid event" is a sudden change in the total electrical power generated by the power system, such as due to, for example, the loss of one or more generating units. Likewise, as used herein, a "load suppression event" is a sudden change in the total electrical power consumed by the power system, such as due to, for example, the loss of one or more loads.

[0026] These grid events can affect the power output of one or more generating units, such as, for example, one or more rotating gas turbine generating units connected to the power system. For example, during a source suppression grid event, one or more generating units still connected to the power system may initially experience a decrease in rotational speed as each unit attempts to compensate for the power loss within the power system. Similarly, during a load shedding event, the power output from the prime mover of a generating unit connected to the power system may exceed the power required by the total electrical load on the power system, which may lead to an increase in the rotational speed associated with one or more generating units. As the rotational speed of the generating units within the power system increases and decreases, the frequency of the alternating current and / or voltage generated by the generating units within the power system may fluctuate rapidly. For convenience, these frequency fluctuations may be referred to herein as frequency rate of change events (or “frequency change rate”) events. Some machines may also trip in response to frequency changes. Therefore, frequency rate of change events occur due to one or more grid events and, as described herein, may lead to losses in one or more other generating units on the power system, which in turn may lead to instability in the entire power system. Furthermore, as described herein, frequency change rate events are associated with frequency change rate values, such as those ranging from 0 Hz / sec to 2 Hz / sec. In some implementations, the frequency change rate value can indicate the severity of the associated frequency change rate event.

[0027] When a large-frequency transient occurs in a small power grid, embodiments of this disclosure can be configured to enhance the dry low-NOx mode in the gas turbine. Some embodiments can calculate the approximate minimum / peak change of the frequency magnitude within the first 200 to 300 milliseconds after the transient. For example, a network estimator or other computer system associated with the power system can be configured to measure or otherwise determine the rate of frequency change immediately after the onset of the grid event. Instead of acceleration-based dry low-NOx mode switching / fuel management, the gas turbine control unit can adjust the air-fuel ratio, the dry low-NOx mode, different fuel splits at the combustion nozzles, and / or other response actions that can avoid transient instability of the gas turbine. In some embodiments, early electrical detection can be used to identify the onset of the grid event, which can then trigger the calculation of the average frequency (e.g., a weighted averaging technique using unit inertia, operating point on unit capacity, and / or available megawatt margin) and the Δ change in operating machine. This calculation can be provided as feedforward control parameters to the turbine controller to readjust the air / fuel split and avoid unnecessary changes in operating parameters. Therefore, the implementation plan can enhance flame stability and overall gas turbine transient stability.

[0028] The systems and methods described herein facilitate the traversal of one or more generating units connected to a power system in response to the occurrence of high-frequency rate-of-change events within the power system. More specifically, the systems and methods described herein provide a substantially real-time control scheme for generating units and enable rapid and effective corrective action for generating units traversing high-frequency rate-of-change events in the power system.

[0029] Figure 2 This is an exemplary processing flow 200 for improved frequency change rate crossing, as may be described herein. Compared to... Figure 2 Compared to the operations discussed in the example shown, other implementations may have additional, fewer, and / or different operations.

[0030] Processing flow 200 can be executed, for example, by one or more controllers associated with the power system. For instance, processing flow 200 can be executed by a network estimator by executing computer-executable instructions using one or more computer processors.

[0031] In block 210, the controller can detect grid events. For example, a controller associated with a power system can be configured to detect grid events, which may be frequency transient events. Detection can be performed using early electrical detection procedures or other suitable methods. In some embodiments, the controller can determine an estimated system inertia before detecting a grid event. In some embodiments, the controller can be configured to detect a frequency drop in the grid as a potential disturbance. For example, the controller can be configured to monitor one or more characteristics or electrical properties of the grid, such as the frequency, voltage, current, power, or power factor associated with the grid. Based on changes in grid characteristics or electrical properties, the controller can determine whether a transient event exists on the grid. For example, if one or more of the frequency, voltage, current, power, or power factor associated with the grid increases or decreases beyond a threshold, the controller can determine that a transient event is occurring or is otherwise about to occur. In one example, the controller can sense the rate of change of electrical frequency at the generator terminals and can determine the rate of change of shaft acceleration (where the rate of change is one of the electrical properties monitored by the controller) to determine whether a transient event is occurring. When a transient event is detected, the controller can send a notification of the transient event to the turbine controller. Because the controller can be connected to the generator and exciter, it can detect grid events faster and more reliably than speed measurement technology.

[0032] In box 220, the frequency change rate value can be determined. For example, to determine the frequency change rate value, the controller can perform a calculation using the following formula:

[0033] ΔP x =-(M / f0)(f t0 )

[0034] Where M is the kinetic energy stored in all rotating blocks, f is the rate of change of frequency (RoCoF), f0 is the rated frequency, and k p It is the composite droop of all generators, and k pi It is the droop of the i-th generator.

[0035] By determining the estimated system inertia before detecting a grid event to ascertain the rate of frequency change, the controller can determine a weighted average of the estimated system inertia, the turbine's operating point, and the available megawatt margin of the power system. The magnitude of the disturbance can be a function of the system inertia (H) or kinetic energy (M) at t=0 and the rate of frequency change.

[0036] In an implementation where the power grid event is a frequency transient event, the controller can be configured to determine the rate of change of frequency within approximately 200 milliseconds or approximately 300 milliseconds after the power grid event is detected.

[0037] In some implementations, the controller can be configured to use the rate of change of frequency values ​​to determine the estimated minimum point, the estimated high minimum point value, and the estimated low minimum point value. The controller can optionally determine an updated minimum point estimate after a threshold length of time has elapsed. Furthermore, in some implementations, the controller can be configured to determine feedforward controller parameters based on the rate of change of frequency values. These feedforward controller parameters can be used by other controllers to adjust operating parameters of electrical system components, such as fuel flow in a gas turbine combustor.

[0038] In box 230, the governor setpoint after a predicted grid event can be determined based on the frequency change rate value. For example, to determine the predicted governor setpoint after a grid event, the controller can perform the calculation using the following formula:

[0039] ΔP pi∞ =(k pi / k p )(ΔP x )

[0040] In some implementations, the controller can determine an estimate of a grid event based on the rate of change of frequency. In this case, the predicted governor setpoint after the grid event can therefore be a function of the droop and the estimate of the grid event.

[0041] In box 240, a change to at least one turbine operating parameter can be initiated based on a predicted grid event following a governor setpoint. For example, the controller can be configured to initiate a change to one or more turbine operating parameters based on a predicted grid event following a governor setpoint. Examples of changes to turbine operating parameters may include changes to at least one of the air / fuel ratio, dry low-NOx mode, or fuel splitting at the combustion nozzle.

[0042] In optional box 250, the controller can be configured to determine that the combustion chamber is in a target mode selected based on a change in at least one turbine operating parameter. For example, in some embodiments, the controller can be configured to determine the target combustion mode using a predicted governor setpoint after a grid event. The target mode could be the expected end state or steady-state of the gas turbine after the grid event has occurred, such as relative to... Figure 5 As described above. In some embodiments, a change in at least one turbine operating parameter causes the turbine to switch to a transition mode at a first time and to a target mode at a second time. The target mode can be selected from a set of available target modes with different combustion configurations. The turbine can transition from the default mode to the transition mode, from the transition mode to the transition recovery mode, and from the transition recovery mode to the target mode within approximately two seconds of a power grid event. Thus, the gas turbine of the power system, and more specifically, the power system's gas turbine, can be configured to traverse frequency change rates up to 2 Hz per second.

[0043] Figures 3 to 4 This is a schematic diagram showing various graphs related to factors used to improve the rate of change of frequency, as may be described in this article.

[0044] exist Figure 3 In the diagram, the first graph 300 shows the frequency measured over time, where the rate of change 310 is determined at or near the start of a grid event (e.g., just before or just after). The first graph 300 can depict a qualitative curve of the frequency response without secondary control. The initial rate of frequency change is determined by the system inertia and the load / generation change. The lowest point or low point of the measured frequency can be detected within approximately 5 to 10 seconds, and the frequency stabilizes after approximately 20 to 30 seconds. The amount of disturbance power can be determined from the rate of frequency change and the kinetic energy stored in the rotating block in the synchronization region, which can be calculated using formulas such as:

[0045] (S rG T G +S rM T M (f / f0)=ΔP p +ΔP s -K I Δf-ΔP x

[0046] ΔP x =-(M / f0)(f t0 )

[0047] Wherein: S rG T represents the rated total power of the generator. G For the mechanical start-up time of all generators (T0 = 2H0), S rM T is the total rated power of the motor. M Mechanical start-up time (T) for all electric motors M =2H M );as well as

[0048] M is the kinetic energy stored in all the rotating blocks, f is the rate of change of frequency (RoCoF), f0 is the rated frequency, and k p It is the combined droop of all generators, and k pi It is the droop of the i-th generator.

[0049] Figure 3The second curve 320 shows the power over time, where peak power 330 occurs at approximately the same time as the low-frequency point, and where steady power 340 occurs shortly thereafter. The second curve 320 can depict a qualitative curve of the primary control power in the absence of secondary control. Therefore, the governor setpoint can be set to match the predicted steady power 340 before the grid event completes. The contribution of the i-th generator to the total steady primary control power from disturbance power, the combined droop of all generators, and the droop of the i-th generator can be determined using formulas such as the following:

[0050] ΔP pi∞ =-((k) pi *M) / (k L +k p f0))(f t0 )

[0051] Where: M is the kinetic energy stored in all rotating blocks, f is the rate of change of frequency (RoCoF), f0 is the rated frequency, and k L It is the load damping constant, k p It is the combined droop of all generators, k pi It is the droop of the i-th generator, and ΔP pi∞ It is the contribution of the i-th generator.

[0052] Therefore, the implementation scheme can predict the governor setpoint after disturbance to increase the system's rate of change capability to approximately 2 Hz / s. The rate of change value can be determined within 200 to 300 milliseconds, and the magnitude of the power disturbance can be estimated. The stable power of the gas turbine can be estimated based on the estimated magnitude of the power disturbance, and turbine parameters and / or target modes can be selected based on the estimated stable power.

[0053] Figure 4 A third graph 400 depicting the sampled system frequency during a transient event is shown. The initial rate of frequency change 410 can be determined at a first time point using system inertia and load / generation changes. The minimum point 420 can be detected at a second time point. The steady-state power 430 can be determined at a third time point. Primary frequency control can occur between the initial rate of frequency change 410 and the steady-state power 430. The minimum point 420 can be estimated 300 milliseconds or less after a grid event. The estimated steady-state power can be determined approximately 2 seconds after a grid event.

[0054] Figure 4 The fourth curve, 440, depicts the mechanical frequency measured over time, where the rate of frequency change varies from 0 to 300 to 500, and then stabilizes at a steady frequency, 442, before secondary control initialization. Figure 4The fifth curve, 450, depicts the algorithm input data over time, in which six samples (or another suitable quantity) of mechanical frequency, power, and voltage are collected and used to measure and / or determine the minimum point and steady-state power. Figure 4 The sixth curve 460 depicts the algorithm output data over time, where the best guessed minimum point and the highest / lowest minimum point values ​​are output at the first time point 462 (e.g., 250 ms, etc.), the updated minimum point estimate is output at the second time point 464 (e.g., 325 ms, etc.) after collecting samples in the fifth curve 450, the expected stable power is output at the third time point 466 (e.g., 500 ms, etc.), and the updated equivalent inertia, the combined droop of all generators, and the load damping constant are output at the fourth time point 468.

[0055] Figure 5 This is a schematic diagram illustrating the determination of the target strategy 500 after detecting a transient event in the power grid frequency, as may be described in this document. (Compared to...) Figure 5 Compared to those examples discussed, other implementations may have additional, fewer, and / or different components or configurations.

[0056] exist Figure 5 In this configuration, the first mode 510 can be a start-up mode or a combustion chamber mode in case of a power grid event. Some circuits may be supplied with fuel, while others may not.

[0057] The second mode 520 can be a transitional start-up mode, during which internal recovery can be emphasized by supplying fuel to certain loops. For example, fuel can be biased towards a particular loop to avoid lean-burn shutdown. The implementation can be configured to avoid or reduce the number of times the turbine enters a transitional mode (e.g., the second mode 520). Following a grid event, the time for switching between the first mode 510 and the second mode 520 can be less than approximately 0.3 seconds. To determine when a mode switch will occur, an estimated minimum point value can be used.

[0058] The third group of modes, 530, 550, and 570, can be various transition recovery modes with different fuel flow rates and configurations. Each fuel flow rate may include different branching methods and can be determined using a lookup table.

[0059] The fourth group of modes 540, 560, and 580 can be various target modes with different fuel flow rates and configurations corresponding to different stable power levels. The target mode selected by the controller can be locked until the speed transient subsides. The rate of frequency change across the entire system may not be equal. The transition from the transition start-up mode to the target mode can occur within approximately 2 seconds after the event, thus minimizing the time spent in any of the second mode 520 and the third group of modes 530, 550, and 570. The estimated stable power can be used to select the appropriate target mode.

[0060] In some implementations, the controller associated with the power system may use the governor setpoint after a predicted grid event to determine the target combustion mode, wherein the target mode is selected from a set of available target modes with different combustion configurations, such as the fourth set of modes 540, 560, and 580.

[0061] Therefore, the aforementioned systems and methods facilitate the traversal of one or more generating units connected to the power system in response to the occurrence of frequency change rate events within the power system. More specifically, the systems and methods described herein provide a substantially real-time generating unit control scheme and are capable of taking rapid and effective corrective measures for generating units traversing frequency change rate events in the power system.

[0062] It should be apparent that the foregoing only relates to certain embodiments of this application and the resulting patent. Many changes and modifications can be made herein by those skilled in the art without departing from the general spirit and scope of the invention as defined by the appended claims and their equivalents.

Claims

1. An electric power system, the electric power system comprising: turbine; A generator connected to the turbine, wherein the generator is configured to supply power to the grid; as well as The controller is configured to: Detecting power grid events; Determine the rate of change of frequency; The governor setpoint is determined based on the predicted power grid event value. The target combustion mode is determined using the governor setpoint after the predicted power grid event. as well as Based on the predicted grid event, the governor setpoint initiates a change to at least one turbine operating parameter. The change in the operating parameter of the at least one turbine causes the turbine to switch to a transition mode at a first time and to switch to the target mode at a second time.

2. The power system according to claim 1, wherein the controller is further configured to: The feedforward controller parameters are determined based on the frequency change rate value.

3. The power system according to claim 1, wherein the controller is further configured to: The estimated value of the power grid event is determined based on the frequency change rate value.

4. The power system of claim 3, wherein the predicted governor setpoint after a grid event is a function of the droop and the estimated value of the grid event.

5. The power system according to claim 1, wherein the controller is further configured to: The estimated minimum, estimated high, and estimated low values ​​are determined using the frequency change rate values.

6. The power system according to claim 5, wherein the controller is further configured to: The updated minimum point estimate is determined after a time period of the threshold length has elapsed.

7. The power system of claim 1, wherein the target mode is selected from a set of available target modes with different combustion configurations.

8. The power system of claim 7, wherein the turbine switches from a default mode to a transition mode, from the transition mode to a transition recovery mode, and from the transition recovery mode to the target mode within 2 seconds of the grid event.

9. The power system of claim 1, wherein the controller is further configured to: The estimated system inertia is determined before the power grid event is detected.

10. The power system of claim 9, wherein, in order to determine the frequency change rate value, the controller is configured to: Determine the weighted average of the estimated system inertia, the operating point of the turbine, and the available megawatt margin of the power system.

11. The power system of claim 1, wherein the turbine is configured to traverse a frequency change rate of up to 2 Hz per second.

12. The power system of claim 1, wherein the change to the at least one turbine operating parameter is a change to at least one of the air / fuel ratio, dry low-NOx mode, or fuel splitting at the combustion nozzle.

13. The power system of claim 1, wherein the grid event is a frequency transient event, and wherein the frequency change rate value is determined within 300 milliseconds after the grid event is detected.

14. A method for a gas turbine crossing an electrical grid event, the method comprising: Power grid events are detected by the controller; Determine the rate of change of frequency; The governor setpoint is determined based on the predicted power grid event value. The target combustion mode is determined using the governor setpoint after the predicted power grid event. as well as Based on the predicted grid event, the governor setpoint initiates a change to at least one turbine operating parameter of the gas turbine. The change in the operating parameter of the at least one turbine causes the turbine to switch to a transition mode at a first time and to switch to the target mode at a second time.

15. A system for a gas turbine crossing an electrical grid event, the system comprising: Gas turbine; A generator connected to the gas turbine, wherein the generator is configured to supply power to the grid; as well as The controller is configured to: Detecting power grid events; Determine the rate of change of frequency; The estimated value of the power grid event is determined based on the frequency change rate value; The predicted governor setpoint after the power grid event is determined based on the estimated value of the power grid event. The target combustion mode is determined using the governor setpoint after the predicted power grid event. as well as Based on the target mode, the change in air / fuel ratio is initiated. The change in the air / fuel ratio causes the turbine to switch to a transition mode at a first time and to switch to the target mode at a second time.

16. The system of claim 15, wherein the controller is further configured to: The estimated minimum, estimated high, and estimated low values ​​are determined using the frequency change rate values.

17. The system of claim 16, wherein the controller is further configured to: The updated minimum point estimate is determined after a time period of the threshold length has elapsed.

18. The system of claim 15, wherein the predicted governor setpoint after the grid event is a function of the droop and the estimated value of the grid event.

19. The system of claim 15, wherein the target mode is selected from a set of available target modes having different combustion configurations.

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