A Method and Device for Evaluating the Frequency Regulation Capability of Gas Turbine Units Based on Predicted Model Parameters Using Measured Data

Abstract

This disclosure relates to the field of power generation and operation control technology, and in particular to a method and apparatus for evaluating the frequency regulation capability of gas turbine units based on measured data model parameter prediction. The method includes: acquiring historical measured operating data of the gas turbine unit, including primary frequency regulation response data when the gas turbine unit does not receive AGC commands, and secondary frequency regulation response data when the gas turbine unit receives AGC commands; correcting preset model parameters based on the primary frequency regulation response data, the corrected model parameters indicating the primary frequency regulation capability of the gas turbine unit; and determining a target evaluation index based on the corrected model parameters and the secondary frequency regulation response data, the target evaluation index indicating the secondary frequency regulation capability of the gas turbine unit. The embodiments of this disclosure utilize historical measured operating data of gas turbine units, which can effectively evaluate the frequency regulation capability of gas turbine units, has good versatility, and provides a reference for unit operation planning and power generation control.

Description

Technical Field

[0001] This disclosure relates to the field of power production and operation control technology, and in particular to a method and device for evaluating the frequency regulation capability of gas turbine units based on measured data model parameter prediction. Background Technology

[0002] Gas turbine units have become the main power source for grid frequency regulation due to their rapid start-up and shutdown and flexible adjustment. Frequency regulation capability assessment methods are the basis for quantifying core indicators such as the unit's frequency regulation response speed, adjustment depth, duration, and stability. Only through scientific assessment can the actual support capability of the unit during grid frequency disturbances be clearly defined.

[0003] In actual operation, the frequency regulation characteristics of different types of gas turbine units (simple cycle, combined cycle) and different control systems vary significantly. Evaluation methods can pinpoint shortcomings in the unit's frequency regulation process, such as the "gas-steam side response time difference" in combined cycle units, fuel system regulation bottlenecks, and unreasonable proportional-integral-derivative (PID) parameter tuning. Based on the evaluation results, control strategies can be optimized (e.g., feedforward control superposition, removing temperature control limitations), and equipment parameters can be improved, thereby increasing the unit's frequency regulation compliance rate and integral power, achieving a precise improvement in frequency regulation performance. Current frequency regulation capability evaluation methods, such as frequency disturbance tests and simulation models, often result in inaccurate evaluations due to changes in the unit's operating status after commissioning and discrepancies between experimental and actual conditions. Summary of the Invention

[0004] In view of this, this disclosure proposes a method and device for evaluating the frequency regulation capability of gas turbine units based on measured data model parameter prediction.

[0005] According to one aspect of this disclosure, a method for evaluating the frequency regulation capability of a gas turbine unit based on measured data model parameter prediction is provided, the method comprising:

[0006] Acquire historical measured operating data of the gas turbine unit, including primary frequency regulation response data when the gas turbine unit does not receive Automatic Generation Control (AGC) commands, and secondary frequency regulation response data when the gas turbine unit receives the AGC commands;

[0007] The preset model parameters are corrected based on the primary frequency regulation response data, and the corrected model parameters are used to indicate the primary frequency regulation capability of the gas turbine unit.

[0008] Based on the corrected model parameters and the secondary frequency regulation response data, a target evaluation index is determined, which is used to indicate the secondary frequency regulation capability of the gas turbine unit.

[0009] In one possible implementation, the primary frequency regulation response data includes a parameter deviation curve and a power change curve. The parameter deviation curve is a curve showing the change of time between the actual grid frequency or the actual speed of the gas turbine unit and the standard set value. The power change curve is a curve showing the change of the active power output value of the gas turbine unit over time.

[0010] In another possible implementation, the step of correcting the preset model parameters based on the primary frequency modulation response data further includes:

[0011] Obtain a preset primary frequency control model, wherein the primary frequency control model is a parameterized mathematical model used to convert frequency deviation or speed deviation into primary frequency power adjustment amount;

[0012] The step of correcting the preset model parameters based on the primary frequency modulation response data includes:

[0013] Based on the parameter deviation curve and the power change curve, the model parameters in the primary frequency regulation control model are corrected. The model parameters include the primary frequency regulation dead zone and the droop coefficient. The primary frequency regulation dead zone is the range of frequency deviation or speed deviation in the primary frequency regulation of the gas turbine unit without power adjustment. The droop coefficient is the relative change in system frequency or unit speed of the gas turbine unit from no-load to full-load.

[0014] In another possible implementation, the secondary frequency regulation response data includes a frequency regulation command power curve, an actual power curve, and a real-time parameter curve. The frequency regulation command power curve is the curve showing the change of the command power of the AGC command over time. The actual power curve is the curve showing the change of the actual power generated by the gas turbine unit over time during actual operation. The real-time parameter curve is the curve showing the change of the actual grid frequency or the actual speed of the gas turbine unit over time, which is recorded synchronously with the AGC command and the actual power curve.

[0015] In another possible implementation, determining the target evaluation index based on the corrected model parameters and the secondary frequency modulation response data includes:

[0016] Based on the corrected model parameters, the actual primary frequency regulation characteristic curve is determined. The actual primary frequency regulation characteristic curve is a curve showing the quantitative relationship between the frequency deviation change and the power regulation of the gas turbine unit.

[0017] The regulating power of the primary frequency regulation of the gas turbine unit is calculated based on the primary frequency regulation characteristic curve and the real-time parameter curve.

[0018] The corrected actual power curve is obtained by subtracting the primary frequency modulation adjustment power from the actual power curve.

[0019] The frequency modulation command power curve and the corrected actual power curve are preprocessed to identify the effective evaluation segment for evaluating the secondary frequency modulation capability.

[0020] The target evaluation index is determined within the effective evaluation segment.

[0021] In another possible implementation, the preprocessing of the frequency modulation command power curve and the corrected actual power curve to identify effective evaluation segments for assessing secondary frequency modulation capability includes:

[0022] Based on the estimated value of the secondary frequency regulation response time of the gas turbine unit, the segments in the power curve of the frequency regulation command where the power duration time interval is less than the estimated value are filtered out;

[0023] In the corrected actual power curve, the segment that is in the same time period as the filtered segment of the frequency modulation command power curve is removed to obtain the filtered actual power curve.

[0024] The filtered actual power curve is digitally filtered, and the filtered actual power curve and the corresponding frequency modulation command power curve are segmented according to a fixed power range.

[0025] Based on the segmented actual power curve and the segmented frequency modulation command power curve, the effective evaluation segment for evaluating the secondary frequency modulation capability is identified.

[0026] In another possible implementation, the effective evaluation segment includes:

[0027] The first type of segment corresponds to a first time period in which a single AGC command remains constant, and the actual power output of the gas turbine unit during the first time period satisfies a first preset morphological characteristic; and / or,

[0028] The second type of segment corresponds to the second time period of multiple consecutive AGC commands in the same direction, and the actual power output of the gas turbine unit changes within the second time period satisfies the second preset morphological characteristics.

[0029] In another possible implementation, the target evaluation metrics include at least one of the following metrics:

[0030] The response time is the time difference between the moment when the AGC command changes and the moment when the actual power output of the gas turbine unit begins to show continuous and unidirectional tracking changes.

[0031] Frequency regulation rate, which is the average adjustment speed calculated based on the rate of change of actual power over time within a specific percentage range of the change in the command during the power tracking process of the gas turbine unit responding to the AGC command;

[0032] Frequency modulation error, which is the average absolute value of the deviation between the actual power output and the commanded power output of the gas turbine unit after the gas turbine unit completes the tracking process of a single AGC command until the next command change.

[0033] According to another aspect of this disclosure, a device for evaluating the frequency regulation capability of a gas turbine unit based on measured data model parameter prediction is provided, the device comprising:

[0034] The acquisition module is used to acquire historical measured operating data of the gas turbine unit. The historical measured operating data includes primary frequency regulation response data when the gas turbine unit does not receive the automatic generation control (AGC) command, and secondary frequency regulation response data when the gas turbine unit receives the AGC command.

[0035] The calibration module is used to calibrate the preset model parameters based on the primary frequency regulation response data. The calibrated model parameters are used to indicate the primary frequency regulation capability of the gas turbine unit.

[0036] The determination module is used to determine the target evaluation index based on the corrected model parameters and the secondary frequency regulation response data. The target evaluation index is used to indicate the secondary frequency regulation capability of the gas turbine unit.

[0037] In one possible implementation, the primary frequency regulation response data includes a parameter deviation curve and a power change curve. The parameter deviation curve is a curve showing the change of time between the actual grid frequency or the actual speed of the gas turbine unit and the standard set value. The power change curve is a curve showing the change of the active power output value of the gas turbine unit over time.

[0038] In another possible implementation, the device further includes:

[0039] The acquisition module is also used to acquire a preset primary frequency modulation control model, which is a parameterized mathematical model for converting frequency deviation or speed deviation into primary frequency modulation power adjustment.

[0040] The correction module is further configured to correct the model parameters in the primary frequency control model based on the parameter deviation curve and the power change curve. The model parameters include the primary frequency dead zone and the droop coefficient. The primary frequency dead zone is the range of frequency deviation or speed deviation in the primary frequency control of the gas turbine unit without power adjustment. The droop coefficient is the relative change in system frequency or unit speed of the gas turbine unit from no-load to full-load.

[0041] In another possible implementation, the secondary frequency regulation response data includes a frequency regulation command power curve, an actual power curve, and a real-time parameter curve. The frequency regulation command power curve is the curve showing the change of the command power of the AGC command over time. The actual power curve is the curve showing the change of the actual power generated by the gas turbine unit over time during actual operation. The real-time parameter curve is the curve showing the change of the actual grid frequency or the actual speed of the gas turbine unit over time, which is recorded synchronously with the AGC command and the actual power curve.

[0042] In another possible implementation, the determining module is further configured to:

[0043] Based on the corrected model parameters, the actual primary frequency regulation characteristic curve is determined. The actual primary frequency regulation characteristic curve is a curve showing the quantitative relationship between the frequency deviation change and the power regulation of the gas turbine unit.

[0044] The regulating power of the primary frequency regulation of the gas turbine unit is calculated based on the primary frequency regulation characteristic curve and the real-time parameter curve.

[0045] The corrected actual power curve is obtained by subtracting the primary frequency modulation adjustment power from the actual power curve.

[0046] The frequency modulation command power curve and the corrected actual power curve are preprocessed to identify the effective evaluation segment for evaluating the secondary frequency modulation capability.

[0047] The target evaluation index is determined within the effective evaluation segment.

[0048] In another possible implementation, the determining module is further configured to:

[0049] Based on the estimated value of the secondary frequency regulation response time of the gas turbine unit, the segments in the power curve of the frequency regulation command where the power duration time interval is less than the estimated value are filtered out;

[0050] In the corrected actual power curve, the segment that is in the same time period as the filtered segment of the frequency modulation command power curve is removed to obtain the filtered actual power curve.

[0051] The filtered actual power curve is digitally filtered, and the filtered actual power curve and the corresponding frequency modulation command power curve are segmented according to a fixed power range.

[0052] Based on the segmented actual power curve and the segmented frequency modulation command power curve, the effective evaluation segment for evaluating the secondary frequency modulation capability is identified.

[0053] In another possible implementation, the effective evaluation segment includes:

[0054] The first type of segment corresponds to a first time period in which a single AGC command remains constant, and the actual power output of the gas turbine unit during the first time period satisfies a first preset morphological characteristic; and / or,

[0055] The second type of segment corresponds to the second time period of multiple consecutive AGC commands in the same direction, and the actual power output of the gas turbine unit changes within the second time period satisfies the second preset morphological characteristics.

[0056] In another possible implementation, the target evaluation metrics include at least one of the following metrics:

[0057] The response time is the time difference between the moment when the AGC command changes and the moment when the actual power output of the gas turbine unit begins to show continuous and unidirectional tracking changes.

[0058] Frequency regulation rate, which is the average adjustment speed calculated based on the rate of change of actual power over time within a specific percentage range of the change in the command during the power tracking process of the gas turbine unit responding to the AGC command;

[0059] Frequency modulation error, which is the average absolute value of the deviation between the actual power output and the commanded power output of the gas turbine unit after the gas turbine unit completes the tracking process of a single AGC command until the next command change.

[0060] According to another aspect of this disclosure, a gas turbine unit frequency regulation capability assessment device based on measured data model parameter prediction is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0061] According to another aspect of this disclosure, a non-volatile computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the above-described method.

[0062] According to another aspect of this disclosure, a computer program product is provided, including a computer program or a non-volatile computer-readable storage medium carrying the computer program, wherein the computer program, when executed by a processor, implements the steps of the above-described method.

[0063] This disclosure utilizes historical measured operating data of gas turbine units participating in frequency regulation to effectively evaluate the primary and secondary frequency regulation capabilities of gas turbine units during actual operation. Compared to the frequency regulation characteristic curves obtained from traditional pre-commissioning tests, it provides a more accurate assessment of the primary frequency regulation output of units operating under low frequency deviation conditions. Regarding the actual power tracking capability after receiving grid AGC commands, it can more accurately obtain evaluation indicators of secondary frequency regulation capabilities based on different operating conditions, providing a basis and reference for the operational planning and optimized control of gas turbine units participating in grid frequency regulation.

[0064] Other features and aspects of this disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0065] The accompanying drawings, which are included in and form part of this specification, illustrate exemplary embodiments, features, and aspects of this disclosure together with the specification and serve to explain the principles of this disclosure.

[0066] Figure 1 A flowchart is shown for a method for evaluating the frequency regulation capability of a gas turbine unit based on measured data model parameter prediction, provided by an exemplary embodiment of this disclosure.

[0067] Figure 2 A flowchart is shown for a method for evaluating the frequency regulation capability of a gas turbine unit based on measured data model parameter prediction, provided by another exemplary embodiment of this disclosure.

[0068] Figure 3 A flowchart is shown for a method for evaluating the frequency regulation capability of a gas turbine unit based on measured data model parameter prediction, provided by another exemplary embodiment of this disclosure.

[0069] Figure 4 A block diagram of frequency regulation control logic for a gas turbine unit provided in an exemplary embodiment of this disclosure is shown.

[0070] Figure 5 A schematic diagram showing the relationship between an ideal frequency modulation characteristic curve and measured data points provided by an exemplary embodiment of this disclosure is shown.

[0071] Figure 6 A schematic diagram of the actual frequency modulation characteristic curve obtained based on measured data, provided by an exemplary embodiment of this disclosure, is shown.

[0072] Figure 7A schematic diagram of the frequency modulation command power curve and the actual power curve of a generator unit that receives AGC commands, provided in an exemplary embodiment of this disclosure, is shown.

[0073] Figure 8 A schematic diagram of the cumulative deviation of actual generated power provided by an exemplary embodiment of this disclosure is shown.

[0074] Figure 9 This illustration shows a schematic diagram of determining a target evaluation index on a valid evaluation segment, provided by an exemplary embodiment of the present disclosure.

[0075] Figure 10 A schematic diagram of a gas turbine frequency regulation capability evaluation device based on measured data model parameter prediction provided in an exemplary embodiment of this disclosure is shown.

[0076] Figure 11 This is a block diagram illustrating an apparatus according to an exemplary embodiment. Detailed Implementation

[0077] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0078] As used herein, the terms “comprising,” “including,” “having,” or variations thereof are open-ended and include one or more of the stated features, integrals, elements, steps, components, or functions, but do not exclude the presence or addition of one or more other features, integrals, elements, steps, components, functions, or groups thereof.

[0079] When an element is referred to as “connected,” “coupled,” “responding,” or a variation thereof relative to another element, it may be directly connected, coupled, or responding to another element, or there may be an intermediate element present.

[0080] Although the terms first, second, third, etc., may be used herein to describe various elements / operations, these elements / operations should not be limited by these terms. These terms are used only to distinguish one element / operation from another. Therefore, without departing from the teachings of this disclosure, a first element / operation in some embodiments may be referred to as a second element / operation in other embodiments.

[0081] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0082] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0083] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant regions.

[0084] The frequency regulation capability assessment of gas turbine units mainly includes two aspects: primary frequency regulation capability and secondary frequency regulation capability. Regarding primary frequency regulation capability, early research focused on the basic principles of primary frequency regulation of gas turbine units and their compatibility with power systems, clarifying the mechanism of differential regulation achieved through the static characteristics of the speed control system and dynamic control of fuel flow. Currently, the common approach is to establish a corresponding control model based on the control logic of the primary frequency regulation of the gas turbine unit, and obtain actual response data through field disturbance tests to verify the rationality of the model and evaluation indicators. Among these methods, the frequency disturbance test is the most commonly used. This involves artificially applying frequency step or ramp disturbances before the unit is put into operation, recording key parameters such as active power, speed, and fuel flow, and then analyzing performance indicators such as response time and overshoot. For units already in operation, the online measurement method is mainly used for evaluation, which involves collecting the actual frequency response characteristic curves of the unit during the primary frequency regulation process to complete the assessment.

[0085] However, the operating conditions under which the unit is tested before commissioning often differ significantly from the actual conditions after long-term operation, leading to corresponding changes in the primary frequency regulation characteristics. Furthermore, the characteristic curve of the gas turbine unit actually participating in primary frequency regulation is often not an ideal straight line, especially in the low-frequency deviation range. Therefore, to improve the accuracy of primary frequency regulation capability assessment, it is necessary to correct and fit the frequency regulation characteristic curve of the gas turbine unit based on measured operating data.

[0086] Regarding secondary frequency regulation capabilities, the evaluation primarily relies on a series of frequency response indicators. These indicators focus on AGC command tracking performance, regulation constraint adaptability, stability, and economy to accommodate the rapid response characteristics of gas turbine units (including simple cycle and combined cycle units) and relevant grid assessment requirements. Key evaluation indicators include regulation rate, response delay time, command tracking error, regulation accuracy, overshoot, steady-state deviation, and action qualification rate. The core objective is to quantify the unit's real-time following ability of AGC commands. For example, the 1-minute / 5-minute regulation rate directly reflects the gas turbine unit's advantage in rapid regulation. Furthermore, economic and stability indicators are also indispensable, such as AGC regulation energy consumption, lifespan loss rate, frequency regulation benefits, and oscillation frequency, aiming to balance the contribution of frequency regulation with operating costs.

[0087] Currently, the evaluation of the aforementioned frequency regulation capability indicators mainly employs two methods: simulation evaluation and field measurement. Simulation evaluation, based on mechanistic models or data-driven models, reproduces the AGC response process and is suitable for capability pre-assessment, parameter optimization, and extreme condition analysis. Field measurement includes two methods: AGC command disturbance tests and online measurements. The former involves manually applying step or ramp commands and recording active power, fuel flow, steam parameters, etc., to analyze indicators such as regulation rate, response delay, and overshoot. The latter utilizes actual AGC dispatch commands issued by the power grid and uses a distributed control system (DCS) to collect data in real time, statistically analyzing action qualification rate, tracking error, etc. However, similar to primary frequency regulation evaluation, pre-commissioning tests often deviate from actual results due to the incomplete matching of operating conditions with actual operation. Secondary frequency regulation evaluations based on field operation experiments, on the other hand, need to consider current operational requirements, making it difficult to conduct a detailed and in-depth analysis of frequency regulation capability.

[0088] To improve the accuracy of assessing the frequency regulation capability of gas turbine units and to support their frequency regulation operation planning and optimized control, it is necessary to study a method for assessing the frequency regulation capability of gas turbine units based on measured data and model parameter prediction, considering their operating characteristics and frequency control features in actual frequency regulation scenarios. A gas turbine unit refers to a complete set of equipment that uses natural gas, coal gas, or other gaseous fuels to drive a gas turbine (or gas internal combustion engine) to rotate, thereby driving a generator to generate electricity. It typically includes a gas turbine, generator, waste heat boiler (combined cycle unit), control system, and auxiliary equipment, which can be simply referred to as the unit in this disclosure. The core of measured data and model parameter prediction is to identify, estimate, or correct key parameters in the mathematical model (especially the control model) by analyzing and processing historical measured operating data recorded by the gas turbine unit under real operating conditions. The aim is to make the model parameters closer to the actual dynamic characteristics of the unit, thereby improving the accuracy of various assessments or predictions based on the model. Frequency regulation capability assessment is the process of quantitatively analyzing and evaluating the ability of a generator unit to automatically, quickly, and accurately adjust its active power output in response to changes in power system frequency or dispatch commands to help maintain system frequency stability. It mainly includes two aspects: primary frequency modulation capability and secondary frequency modulation (AGC) capability.

[0089] The following describes, using several exemplary embodiments, the method for evaluating the frequency regulation capability of gas turbine units based on measured data model parameter prediction provided in this disclosure.

[0090] Please refer to Figure 1 This document illustrates a flowchart of a method for evaluating the frequency regulation capability of a gas turbine unit based on predicted parameters of a model using measured data, provided in an exemplary embodiment of this disclosure. This embodiment uses the method in a computing device as an example for illustration. The method includes the following steps.

[0091] Step 101: Obtain historical measured operating data of the gas turbine unit. The historical measured operating data includes primary frequency regulation response data of the gas turbine unit when it does not receive AGC commands, and secondary frequency regulation response data of the gas turbine unit when it receives AGC commands.

[0092] Historical measured operational data consists of a continuous sequence of data collected from the gas turbine unit's control system or wide-area measurement system, recording the gas turbine unit's actual participation in grid frequency regulation during historical periods. This data forms the objective basis for the assessment and specifically includes a series of curves with the same time reference.

[0093] An Active Power Control (AGC) command is a remote instruction automatically issued by the power dispatch center through the energy management system to a designated generator unit, requiring it to adjust its active power output based on the real-time balance requirements of system load and generation. This command is typically given in the form of a target power value or a power adjustment value, and is used to achieve secondary frequency regulation and economic dispatch.

[0094] Primary frequency regulation response data is the recorded data of the automatic and rapid power adjustment process performed by the gas turbine unit based on the inherent static characteristics (such as speed-power droop characteristics) of its speed regulation system when the grid frequency or unit speed deviates from the rated value due to load disturbances. This process does not rely on AGC commands and is a spontaneous response of the unit itself.

[0095] In one possible implementation, the primary frequency regulation response data is historical actual operating curve data, including parameter deviation curves and power change curves. The parameter deviation curve is the curve showing the change of the difference between the actual frequency of the power grid or the actual speed of the gas turbine unit and the standard set value over time, and the power change curve is the curve showing the change of the active power output value of the gas turbine unit over time.

[0096] The parameter deviation curve, also known as the frequency deviation curve or speed deviation curve, describes the change over time of the difference between the actual frequency of the power grid or the actual speed of the gas turbine unit and the standard set value (e.g., 50Hz). The horizontal axis represents time, and the vertical axis represents the frequency deviation (unit: Hz) or speed deviation (unit: rpm or per unit value). It is the input signal that triggers the primary frequency regulation of the unit.

[0097] The power variation curve is a curve that records the change of the active power output value of a gas turbine unit over time when it is not receiving AGC commands. The horizontal axis represents time, and the vertical axis represents active power (unit: MW). It represents the output response of the gas turbine unit as it autonomously adjusts its output only in response to frequency deviations.

[0098] Secondary frequency regulation response data is the recorded data of the gas turbine unit receiving and executing AGC commands issued by the power dispatch center, and tracking and adjusting its own active power output. This process is used to eliminate the frequency deviation (frequency difference) remaining after primary frequency regulation or to meet more refined power allocation requirements.

[0099] In one possible implementation, the secondary frequency regulation response data includes a frequency regulation command power curve, an actual power curve, and a real-time parameter curve. The frequency regulation command power curve is the curve showing the change of the commanded power of the AGC command over time. The actual power curve is the curve showing the change of the actual power generated by the gas turbine unit over time during actual operation. The real-time parameter curve is the curve showing the change of the actual grid frequency or the actual speed of the gas turbine unit over time, which is recorded synchronously with the AGC command and the actual power curve.

[0100] The frequency regulation command power curve is a curve that records the change of command power issued by the power grid AGC system to the gas turbine unit over time. Its horizontal axis is time, and the vertical axis is command power (unit: MW). Command power is also called power command value.

[0101] The actual power output curve is a curve that records the change of the measured total active power output of a gas turbine unit over time during actual operation. The horizontal axis represents time, and the vertical axis represents active power (unit: MW). It includes the comprehensive response of the gas turbine unit to AGC commands, primary frequency regulation response, and other factors.

[0102] Real-time parameter curves, including real-time frequency curves or real-time speed curves, refer to curves that record the actual frequency of the power grid or the actual speed of the gas turbine unit over time, synchronously with the frequency regulation command and the actual power generation curve. The horizontal axis represents time, and the vertical axis represents the absolute value of the frequency (unit: Hz) or the absolute value of the speed (unit: rpm).

[0103] Step 102: Correct the preset model parameters based on the primary frequency regulation response data. The corrected model parameters are used to indicate the primary frequency regulation capability of the gas turbine unit.

[0104] Model parameters are a set of constant coefficients (such as primary frequency dead zone, droop coefficient, etc.) that need to be determined based on the actual system characteristics in the mathematical model used to describe the frequency regulation control logic or dynamic characteristics of the gas turbine unit. These parameters directly affect the relationship between the model input (such as frequency deviation) and output (such as power regulation).

[0105] In one possible implementation, the model parameters are the model parameters in a preset primary frequency control model, which is a parameterized mathematical model used to convert frequency deviation or speed deviation into primary frequency power regulation.

[0106] The primary frequency regulation control model is pre-built and consists of a series of control elements (represented by transfer functions). The input to this model is the frequency deviation, and the output is the primary frequency regulation power adjustment. The primary frequency regulation control model is used to convert the input frequency deviation (the difference between the grid frequency and the rated value) or speed deviation (the difference between the actual unit speed and the rated value) into the theoretically required primary frequency regulation power adjustment command that the unit should issue, based on the embedded control logic and parameters.

[0107] This disclosure addresses the issue of inaccurate model parameters after unit commissioning testing by correcting the model parameters based on primary frequency regulation response data. In one possible implementation, the model parameters include a primary frequency regulation dead zone and a droop coefficient. The primary frequency regulation dead zone is the range of frequency or speed deviation without power regulation during the primary frequency regulation of the gas turbine unit. The droop coefficient is the relative change in system frequency or unit speed corresponding to the gas turbine unit's transition from no-load to full-load.

[0108] The primary frequency control dead zone refers to a frequency (speed) deviation range in the primary frequency control function of a gas turbine unit that is set to avoid activation in response to minute frequency fluctuations. Theoretically, the unit will not perform power regulation when the absolute value of the frequency deviation is less than this dead zone value. It is a key model parameter identified by analyzing historical primary frequency control response data.

[0109] The droop factor is a parameter that measures the static characteristics of the primary frequency regulation of a gas turbine unit. It is defined as the relative (percentage) change in system frequency (or unit speed) when the active power of the unit changes from no-load (0%) to full-load (100%) within the ideal linear operating range of the gas turbine unit speed regulation system, which does not include the primary frequency regulation dead zone.

[0110] Calibration is a technical process that uses measured operating data to compare and analyze the model output, and adjusts the values ​​of model parameters through methods such as parameter identification and optimization algorithms, so that the behavior (output) of the mathematical model can fit or reproduce the actual response process of the unit to the greatest extent.

[0111] Primary frequency regulation capability refers to the ability of a generator set to autonomously adjust its power output to small and rapid fluctuations in system frequency (or speed) without relying on external dispatch commands, solely through its own control system. It is typically measured using indicators such as response speed, regulation amount, and droop characteristics.

[0112] Step 103: Based on the corrected model parameters and secondary frequency regulation response data, determine the target evaluation index, which is used to indicate the secondary frequency regulation capability of the gas turbine unit.

[0113] Based on the corrected model parameters, the secondary frequency regulation response data is processed and analyzed to calculate target evaluation indicators for assessing secondary frequency regulation performance. These target evaluation indicators are a set of specific, calculable metrics used to quantitatively evaluate the secondary frequency regulation (AGC) performance of gas turbine units. These indicators are directly extracted or calculated from the unit's secondary frequency regulation response process data, such as response time (the time difference between the command change point and the point where continuous power tracking begins), regulation rate (the power change within a specific interval divided by time), and regulation error (the average or integral of the deviation between the command and actual power output during steady-state tracking). These indicators represent the final quantitative representation of the evaluation results.

[0114] Secondary frequency regulation capability refers to the generator set's ability to receive and track AGC commands and adjust its active power output accordingly. The main evaluation criteria include the speed of command tracking (e.g., response time, frequency regulation rate), accuracy (e.g., frequency regulation error), and stability.

[0115] In summary, this embodiment of the present disclosure acquires historical measured operating data of the gas turbine unit, including primary frequency regulation response data when the gas turbine unit does not receive Automatic Generation Control (AGC) commands, and secondary frequency regulation response data when the gas turbine unit receives AGC commands. Based on the primary frequency regulation response data, preset model parameters are corrected, and the corrected model parameters are used to indicate the primary frequency regulation capability of the gas turbine unit. Based on the corrected model parameters and the secondary frequency regulation response data, a target evaluation index is determined, which is used to indicate the secondary frequency regulation capability of the gas turbine unit. Therefore, based on historical measured operating data of the gas turbine unit under normal operating conditions, the frequency regulation capability of the gas turbine unit to participate in grid frequency regulation upon receiving commands can be effectively evaluated. This method has good versatility and provides a reference for the operation planning and power generation control of gas turbine units.

[0116] Please refer to Figure 2 This document illustrates a flowchart of a method for evaluating the frequency regulation capability of a gas turbine unit based on predicted parameters of a model using measured data, provided in another exemplary embodiment of this disclosure. This embodiment uses the method in a computing device as an example. The method includes the following steps.

[0117] Step 201: Obtain historical measured operating data of the gas turbine unit. The historical measured operating data includes the parameter deviation curve of the gas turbine unit participating in primary frequency regulation when it does not receive AGC command, the power change curve of the gas turbine unit when it does not receive AGC command, the frequency regulation command power curve of the gas turbine unit when it receives AGC command, the actual power generation curve of the gas turbine unit when it receives AGC command, and the corresponding real-time parameter curve.

[0118] In one possible implementation, based on the evaluation requirements, a time range is set, data labels (such as frequency, power, and AGC commands) are filtered, and it is ensured that key data such as parameter deviation curves, power change curves, frequency modulation command power curves, actual generated power curves, and real-time parameter curves are collected completely and synchronously. Specifically, the parameter deviation curve is either a frequency deviation curve or a speed deviation curve, and the real-time parameter curve is either a real-time frequency curve or a real-time speed curve.

[0119] Step 202: Based on the parameter deviation curve and power change curve, the model parameters in the preset primary frequency regulation control model are corrected to obtain the corrected model parameters, which include the primary frequency regulation dead zone and the droop coefficient.

[0120] In one possible implementation, a preset primary frequency regulation control model is obtained. The primary frequency regulation control model is a parameterized mathematical model constructed based on the frequency regulation control logic of the gas turbine unit, used to convert frequency deviation or speed deviation into primary frequency regulation power adjustment. The model parameters in the primary frequency regulation control model are corrected according to the parameter deviation curve and the power change curve.

[0121] In one possible implementation, the frequency regulation control logic of the gas turbine unit is constructed, including speed characteristic circuits, limiting circuits, PI control circuits, and power generation system simulation circuits. Control parameters for each module are preset based on parameters provided during gas turbine unit commissioning and experimental parameters. A simulation test model is built according to the control logic and the preset control descriptions for each module. The parameter deviation curves and power change curves of the gas turbine unit participating in primary frequency regulation without receiving AGC commands are compared with those from actual measurements to correct the primary frequency regulation dead zone and droop coefficient of the speed characteristic circuit.

[0122] Using the measured data of primary frequency modulation (parameter deviation curve as input and power change curve as output) as a benchmark, the dead zone of primary frequency modulation is determined by analyzing the maximum frequency deviation when the power is zero, and the droop coefficient is determined by fitting the proportional relationship between frequency deviation and power change.

[0123] In one possible implementation, the slopes of the primary frequency regulation dead zone and operating range are identified from the parameter deviation curve and power change curve, respectively corresponding to the proportional coefficients of the dead zone and proportional control loops in the primary frequency regulation control model. The model parameter correction process may include, but is not limited to, the following steps: 1. Determine the dead zone interval: Based on the measured parameter deviation curve and power change curve, statistically analyze the frequency deviation corresponding to when the primary frequency regulation power adjustment is close to zero. The frequency deviation with the largest absolute value is determined as the primary frequency regulation dead zone. That is, within this interval, the unit does not perform active power regulation. 2. Identify the droop coefficient (proportional coefficient): For data outside the dead zone, based on each sampling point on the frequency (speed) deviation curve, process them sequentially in ascending order of absolute frequency deviation value. For each frequency deviation measurement point, adjust the parameters of the proportional control loop (i.e., the droop coefficient) so that the primary frequency regulation power change calculated by the model is consistent with the value at the corresponding moment on the measured power change curve. The parameter determined at this time is the proportional coefficient under that specific frequency deviation. 3. Extrapolation rule: For intervals exceeding the measured maximum frequency deviation, the droop coefficient is determined by the value at the measured maximum frequency deviation and used as the droop coefficient of the unit under larger frequency disturbances.

[0124] Step 203: Based on the corrected model parameters, determine the actual primary frequency regulation characteristic curve. The actual primary frequency regulation characteristic curve is a curve showing the quantitative relationship between the frequency deviation change and the power regulation of the gas turbine unit.

[0125] Typically, the frequency deviation of measured data (the frequency (speed) deviation curve of units that have not received AGC commands and participated in primary frequency regulation) will be concentrated in a narrow range, such as -0.05Hz to 0.05Hz. Therefore, the above correction process uses measured data within this range to correct model parameters.

[0126] After obtaining the corrected model parameters, the primary frequency regulation control model is determined. Then, simulations are performed over a wider frequency deviation range (where no measured data is available), such as -1Hz to 1Hz, to obtain the primary frequency regulation power and plot the curve. This process of determining the actual primary frequency regulation characteristic curve of the unit based on the corrected model parameters (primary frequency dead zone and slip coefficient) is a process of transforming parameters into an intuitive, quantitative graphical representation. Simulations are conducted over a wider frequency deviation range, with frequency (speed) deviation as the abscissa and the change in primary frequency regulation power as the ordinate, plotting points on the coordinate system to form the actual primary frequency regulation characteristic curve. The actual primary frequency regulation characteristic curve describes the functional relationship between the change in grid frequency deviation and the theoretically required primary frequency regulation power regulation of the gas turbine unit under steady-state or quasi-steady-state conditions. It is typically simplified to a straight line, with its slope (slip coefficient) being the key parameter. It reflects the actual static regulation characteristics of the unit under the current state.

[0127] Step 204: Calculate the regulating power of the primary frequency regulation of the gas turbine unit based on the primary frequency regulation characteristic curve and the real-time parameter curve.

[0128] Calculating the time series of the theoretical primary frequency regulation power of a gas turbine unit within any given time period, based on the primary frequency regulation characteristic curve and real-time parameter curve, is a process of "table lookup" or "function calculation." In one possible implementation, the calculation process for the primary frequency regulation power of the gas turbine unit includes: for each time point on the real-time parameter curve, taking its frequency value, calculating the frequency deviation from the rated value, and then determining the theoretical primary frequency regulation power value corresponding to that moment according to the rules defined by the primary frequency regulation characteristic curve. This operation is repeated for all time points to generate a new time series curve. In other words, the primary frequency regulation power refers to the theoretical curve representing the change in active power that the unit should theoretically contribute to primary frequency regulation over time, obtained by calculating the deviation curve of any given frequency (speed) based on the actual primary frequency regulation characteristic curve.

[0129] Step 205: Subtract the primary frequency modulation adjustment power from the actual power curve to obtain the corrected actual power curve.

[0130] Assuming perfect alignment of the time series, the power value at each point of the actual power generation curve is subtracted from the calculated primary frequency regulation power at the same moment, resulting in a new power curve, namely the corrected actual power generation curve. The corrected actual power generation curve refers to the new power time series curve obtained by subtracting the theoretical power regulation component generated by the primary frequency regulation function from the original actual power generation curve of the gas turbine unit (i.e., the actual total active power output time series).

[0131] The purpose of this step is to achieve signal separation. In actual unit operation, its power variation is the result of the combined and superimposed effects of primary frequency regulation (responding to frequency fluctuations) and secondary frequency regulation (responding to AGC commands). Directly using the original actual power curve to evaluate AGC tracking performance will introduce errors due to the interference of primary frequency regulation actions. Through the above subtraction operation, the aim is to theoretically eliminate the power fluctuations caused by the unit's spontaneous response system frequency changes, thereby obtaining a power curve that more purely reflects the unit's tracking and execution of AGC commands, creating conditions for a pure evaluation of secondary frequency regulation tracking performance. Therefore, the corrected actual power curve can also be called the "net AGC response power curve" or the "actual power curve after removing the influence of primary frequency regulation".

[0132] Step 206: Preprocess the frequency modulation command power curve and the corrected actual power curve to identify the effective evaluation section for evaluating the secondary frequency modulation capability.

[0133] The frequency modulation command power curve and the corrected actual power curve are preprocessed to remove irrelevant or interfering data, thereby identifying the effective evaluation section.

[0134] In one possible implementation, the frequency regulation command power curve and the corrected actual power curve are preprocessed, including: filtering out segments in the frequency regulation command power curve where the power duration time interval is less than the estimated value, based on the estimated value of the secondary frequency regulation response time of the gas turbine unit; removing segments in the corrected actual power curve that have the same time interval as the filtered segments in the frequency regulation command power curve to obtain the filtered actual power curve; digitally filtering the filtered actual power curve and segmenting the filtered actual power curve and the corresponding frequency regulation command power curve according to a fixed power range; and identifying the effective evaluation segment for assessing the secondary frequency regulation capability based on the segmented actual power curve and the segmented frequency regulation command power curve.

[0135] The filtering in preprocessing refers to identifying and removing data segments that do not meet the requirements from the data sequence based on preset logical judgment conditions. This step includes, but is not limited to, the following operations: using the estimated value of the secondary frequency regulation response time of the gas turbine unit (an empirical or calculated value, such as 30 seconds) as the judgment threshold; traversing the frequency regulation command power curve to find all command power durations that remain constant, and marking command platform segments with durations shorter than the estimated value as invalid. In one possible implementation, the curve period in the frequency regulation command power curve where the power duration interval is less than the estimated value can be: the curve period where the time interval between two opposite changes in the frequency regulation command power is less than the estimated value.

[0136] The calculation method for the estimated value of the secondary frequency regulation response time of the gas turbine unit may include: shifting the actual power generation curve forward along the time axis according to a preset time interval, and calculating the cumulative deviation of the actual power generation by comparing it with the frequency regulation command power curve. Repeat the previous step until the cumulative shift time interval is greater than or equal to the preset time window, and determine the estimated value of the secondary frequency regulation response time of the gas turbine unit.

[0137] A preset time window refers to a pre-defined maximum time length value used to limit the range of inherent delays in the search unit's response to AGC commands. It represents a reasonable upper limit for the expected unit response delay time.

[0138] In one possible implementation, the method for calculating the cumulative deviation of actual generated power may include: determining the frequency regulation command power curve and the shifted actual generated power curve with the time axis as the horizontal axis in the same reference time coordinate system; calculating the absolute value of the difference between the frequency regulation command power and the actual generated power of the unit at each time point of the curve during the entire evaluation period as the regulation power deviation; and summing the regulation power deviations at all time points as the cumulative deviation of actual generated power.

[0139] The cumulative deviation of actual generated power refers to the scalar value obtained by summing the absolute values ​​of the power values ​​at the same point in time between the shifted "actual generated power curve" and the original "frequency modulation command power curve" over the entire evaluation period. It is used to measure the overall difference between the two curves after time alignment.

[0140] In one possible implementation, the method for determining the estimated value of the unit's secondary frequency regulation response time may include: setting the initial cumulative shift time to zero; calculating the cumulative shift time after each shift of the unit's actual power curve receiving the AGC command, and correspondingly calculating the cumulative deviation of the actual power after that shift; when the cumulative shift time is greater than or equal to a preset time window, sorting the cumulative deviations of the actual power calculated for each shift, and the cumulative shift time corresponding to the smallest cumulative deviation of the actual power is the estimated value of the secondary frequency regulation response time. Here, shifting refers to the data processing operation performed to estimate the response delay, that is, moving the data points of the "actual power curve" forward along the time axis by a fixed time interval. After the shift, the time label of the curve advances, but the power value remains unchanged.

[0141] The removal process in preprocessing refers to performing a synchronous deletion operation. On one data curve, data that corresponds exactly in time to the deleted segment of another curve is removed. This step includes, but is not limited to, the following operations: based on the filtered segment (time interval) marked on the frequency modulation command curve in the previous step, power data within the same time period is precisely deleted from the corrected actual power curve. This ensures strict synchronization and consistency of the two curves (frequency modulation command power curve and actual power curve) in the time dimension. It avoids situations where commands are invalid but their corresponding responses are still being analyzed in subsequent analyses, ensuring the correct matching relationship of data pairs.

[0142] Digital filtering in preprocessing refers to a signal processing algorithm applied to data sequences such as actual power generation curves. Its purpose is to suppress or eliminate high-frequency measurement noise and irrelevant fluctuations in the data, thereby obtaining a smoother curve that better reflects the actual adjustment trend of the generating unit. Common methods include smoothing filtering or low-pass filtering. This step includes, but is not limited to, the following operations: filtering the filtered actual power generation curves (i.e., data with invalid periods removed). This improves the signal-to-noise ratio, making the trend changes in the power curve that reflect the unit's true tracking intention and capability clearer, and reducing noise interference with subsequent segmentation and index calculations.

[0143] Segmentation in preprocessing refers to dividing and classifying continuous time-series data into several consecutive intervals or data blocks according to certain division rules. This step includes, but is not limited to, the following operations: using a fixed power interval (e.g., starting from zero, with each 100MW as a power interval) as the division basis, synchronously segmenting the filtered actual power curve and its corresponding frequency regulation command power curve. That is, when the actual power enters a new power interval, a new data segment is started. The significance of segmentation is that the secondary frequency regulation capability may vary significantly between different power intervals. For example, the frequency regulation capability will be different in two power intervals: 100-200MW and 200-300MW. Therefore, segmentation is necessary, and then evaluation is performed separately in each power interval.

[0144] Identifying effective evaluation segments refers to locating and selecting subsets that meet specific analytical objectives from the processed dataset by setting criteria and analyzing data characteristics. This step includes, but is not limited to, the following operations: On the segmented curves, apply a series of criteria (e.g., whether the command change amplitude of the segment is significant, whether the actual power generation has completely experienced the tracking process, whether the process data is complete, whether it is under stable unit operating conditions, etc.) to determine and label those effective time segments suitable for calculating secondary frequency regulation performance indicators. Finally, determine the sample range for evaluation. Ensure that the data used to calculate the target evaluation indicators all come from a clear, complete, and representative secondary frequency regulation operation process of the unit, thereby guaranteeing the validity and statistical significance of the evaluation results.

[0145] In one possible implementation, valid evaluation segments can be categorized into the following two types:

[0146] The first type of segment corresponds to the first time period in which a single AGC command remains constant, and the actual power output of the gas turbine unit changes within the first time period meets the first preset morphological characteristic. Within this time period, the actual power output of the gas turbine unit needs to exhibit a complete "Z-shaped" curve shape, that is, the first preset morphological characteristic can be set to a "Z-shaped" morphological characteristic, thereby forming a complete single-command cycle that can be used to evaluate response time, regulation rate, and accuracy.

[0147] The second type of segment corresponds to the second time period of multiple consecutive unidirectional AGC commands, and the actual power output change of the gas turbine unit within the second time period meets the second preset morphological characteristics. In this type of time period, the actual power output change of the unit presents a superimposed or connected pattern of multiple "Z-shaped" responses, that is, the second preset morphological characteristics are multiple superimposed or connected "Z-shaped" patterns. In this type of time period, although the actual power output change of the unit still presents a "Z-shaped" pattern, due to the continuous changes in commands, it is difficult to accurately determine the response start point of a single command. Therefore, it is mainly suitable for evaluating frequency regulation rate and regulation accuracy, but not for calculating response time.

[0148] The two types of segments can be identified by recognizing the "Z-shaped" changes in the measured power curve. This method supports both manual and machine recognition. The recognition rules can be set as follows: if the measured power curve sequentially exhibits one of the following patterns, it is determined to be a "Z-shaped" change segment (i.e., a valid evaluation segment): Rise-fall-rise: Power first rises (allowing for stability, but not a fall), then strictly falls, and then rises again (allowing for stability, but not a fall); Fall-rise-fall: Power first falls (allowing for stability, but not a rise), then strictly rises, and then falls again (allowing for stability, but not a rise). To ensure the reliability of the recognition, the following continuous sampling period constraints must be met: the first and last two stages of the "Z-shape" (the first and third segments) must each last for no less than 5 sampling periods; the middle stage (the second segment) must last for no less than 10 sampling periods.

[0149] Step 207: Determine the target evaluation index in the effective evaluation section. The target evaluation index is used to indicate the secondary frequency regulation capability of the gas turbine unit.

[0150] Within each valid evaluation segment, target evaluation indicators are determined according to a predefined method. These target evaluation indicators are used to indicate the secondary frequency regulation capability of the gas turbine unit. The target evaluation indicators include at least one of the following: response time, frequency regulation rate, and frequency regulation error.

[0151] Response time is the time difference between the moment the AGC command changes and the moment when the actual power output of the gas turbine unit begins to show continuous, unidirectional tracking changes. "Continuous, unidirectional tracking" typically requires that the power change direction matches the command change direction for multiple consecutive sampling cycles (e.g., 5 cycles). Response time measures the delay or speed at which the unit responds to dispatch requests.

[0152] The frequency regulation rate is the average adjustment speed calculated based on the rate of change of actual generated power over time within a specific percentage range (typically 10% to 90%) of the command change during the power point tracking process of a gas turbine unit responding to an AGC command. The frequency regulation rate is used to measure the unit's average ramp-up capability or regulation intensity during the core regulation phase.

[0153] Frequency regulation error is the average absolute value of the deviation between the actual power output and the commanded power output of the gas turbine unit after the unit completes the tracking process of a single AGC command, until the next command change. Frequency regulation error is used to measure the accuracy or static precision of the unit in tracking commands under steady-state conditions.

[0154] Please refer to Figure 3 This document illustrates a flowchart of a method for evaluating the frequency regulation capability of a gas turbine unit based on predicted parameters of a model using measured data, provided in another exemplary embodiment of this disclosure. This embodiment uses the method in a computing device as an example. The method includes the following steps.

[0155] Step 301: Obtain historical actual operating curve data of the gas turbine unit participating in the frequency regulation process.

[0156] During the period of frequency regulation capability assessment, historical actual operating curve data of gas turbine units participating in the frequency regulation process are obtained. The historical actual operating curve data includes: frequency (speed) deviation curve of units that did not receive AGC commands participating in primary frequency regulation, power change curve of units that did not receive AGC commands, frequency regulation command power curve of units that received AGC commands, actual power curve of units that received AGC commands, and corresponding real-time frequency (speed) curve.

[0157] Step 302: Based on the frequency (speed) deviation curve of the unit that did not receive the AGC command and the power change curve of the unit that did not receive the AGC command, obtain the primary frequency regulation dead zone and the actual primary frequency regulation characteristic curve of the unit.

[0158] In one possible implementation, the dead zone and actual primary frequency regulation characteristic curve of the unit are obtained, including but not limited to the following steps: constructing the frequency regulation control logic of the gas turbine unit, including speed characteristic link, limiting link, PI control link and power generation system simulation link, etc.; presetting the control parameters of each module based on the parameters provided by the gas turbine unit commissioning and experimental parameters; building a simulation test model according to the control logic and the pre-set control description of each module; correcting the dead zone and slip-power characteristic parameters of the speed characteristic link by comparing the frequency (speed) deviation curve of the unit participating in primary frequency regulation without receiving AGC command and the power change curve of the unit without receiving AGC command; conducting simulations within a wider frequency deviation range, plotting points in the coordinate system with the frequency (speed) deviation as the abscissa and the primary frequency regulation power change as the ordinate to form the frequency regulation characteristic curve.

[0159] Step 303: According to the actual primary frequency modulation characteristic curve, the primary frequency modulation adjustment power of the computer group is calculated, and the primary frequency modulation adjustment power is subtracted from the actual power curve of the unit receiving the AGC command.

[0160] Step 304: Preset the time window T for evaluating the power curve with a delay. w .

[0161] Step 305, according to The actual power generation curve of the unit receiving AGC commands is shifted forward along the time axis at an interval of t = 1s.

[0162] Step 306: Determine whether the cumulative translation time interval is greater than or equal to T. w .

[0163] If the cumulative translation time interval is less than T w Then proceed to step 307 until the cumulative translation time interval is greater than or equal to T. w If the cumulative translation time interval is greater than or equal to T w Then, the estimated value of the unit's secondary frequency regulation response time is determined. T, proceed to step 310.

[0164] In one possible implementation, the estimated value of the unit's secondary frequency regulation response time is determined. The method of T includes: initial cumulative translation time T0 = ​​0; After each translation of the actual power output curve of the unit receiving the AGC command, calculate the cumulative translation time for this translation. T i = T i-1 + t corresponds to the cumulative deviation S of the actual generated power after this translation. i When the translation time is accumulated T i≥T w At that time, S is calculated for each translation. i Sort the data, and find the smallest S. i corresponding T i This is the estimated value of the second frequency modulation response time. T.

[0165] Step 307: Calculate the cumulative deviation S of the actual generated power by comparing it with the frequency modulation command power curve of the unit receiving the AGC command. i .

[0166] If the cumulative translation time interval is less than T w Then, by referring to the frequency modulation command power curve of the unit receiving the AGC command, the cumulative deviation S of the actual generated power is calculated. i In one possible implementation, the cumulative deviation S of the actual generated power is calculated. i The method includes: determining the frequency modulation command power curve of the unit receiving AGC commands and the actual power curve of the unit receiving AGC commands after translation, with the time axis as the horizontal axis and under the same reference time coordinate system; calculating the absolute value of the difference between the frequency modulation command power and the actual power of the unit as the regulation power deviation at each time point of the curve throughout the entire evaluation period; and summing the regulation power deviations at all time points as the cumulative deviation S of the actual power. i .

[0167] Step 308, determine the cumulative deviation S of the actual generated power. i Is it less than the minimum deviation S of the current record? min .

[0168] If the cumulative deviation of the actual generated power is S i Less than the minimum deviation S of the current record min Then proceed to step 309; if the cumulative deviation of the actual generated power is S i Greater than or equal to the minimum deviation S of the current record min If so, continue with step 305 above.

[0169] Step 309, set the minimum deviation S min Updated to cumulative deviation of actual generated power S i .

[0170] If the cumulative deviation of the actual generated power is S i Less than the minimum deviation S of the current record min Then the minimum deviation S min Updated to cumulative deviation of actual generated power S i Continue with step 305 above.

[0171] Step 310: Select units that receive AGC commands, and ensure that the power duration time interval in their frequency modulation command power curves is less than [a certain value]. For the curve period of T, remove the actual power generation curve of the unit that received AGC command within the same time period.

[0172] In one possible implementation, the power duration time interval in the frequency modulation command power curve is less than... The curve period of T can be: the time interval between two opposite changes in the power of the AGC frequency modulation command is less than The curve period of T.

[0173] Step 311: Perform digital filtering on the actual power curve of the unit receiving AGC commands, and segment the actual power curve and frequency modulation command power curve of the unit receiving AGC commands according to a fixed power range.

[0174] In one possible implementation, digital filtering is smoothing filtering and / or low-pass filtering.

[0175] In one possible implementation, a fixed power range can be defined as starting from zero, with each 100MW segment serving as a power range. When the actual power output curve of a unit receiving an AGC command falls within that power range, the unit is considered to be operating within that power range.

[0176] Step 312: Based on the actual power output curve and frequency modulation command power output curve of the unit receiving AGC command after segmentation processing, identify the effective evaluation segment of the unit's frequency modulation capability in the actual power output curve;

[0177] In one possible implementation, the effective evaluation range of the unit's frequency regulation capability includes: within a constant period of a single frequency regulation command, the actual power output curve of the unit must satisfy a "Z-shaped" change, so that a complete single-command evaluation cycle can be obtained; after continuous unidirectional frequency regulation commands, the actual output power curve of the unit satisfies a "Z-shaped" change, making it difficult to evaluate the frequency regulation response time, but it can be used to evaluate the frequency regulation response rate and regulation accuracy.

[0178] Step 313: Calculate the secondary frequency regulation capability evaluation index of the gas turbine unit in the effective evaluation section.

[0179] In one possible implementation, the method for calculating the secondary frequency regulation capability evaluation index of the gas turbine unit includes: taking the time when the frequency regulation command is issued (changes) as T0, and taking the starting point of the same-direction tracking of the actual generated power for 5 consecutive sampling cycles as T0. b Calculate the response time T r = T b- T0; Calculate the rate of change of power over time as the frequency modulation rate at two actual power points (10% and 90% of the load command target) during single-phase power tracking; The tracking termination time T is defined as the actual power reaching the specified frequency modulation power setting, or the termination of power tracking (resulting in a reverse power change). c Calculate T c The average steady-state error of the segment before the next frequency modulation command change is taken as the frequency modulation error.

[0180] Figure 4 A block diagram of the frequency regulation control logic for a gas turbine unit provided in an exemplary embodiment of this disclosure is shown. It includes: a primary frequency regulation characteristic module f(x), a limiting circuit, a PI control circuit, a differential adjustment gain module, and a power generation system dynamics module. The reference models and parameters of each module are determined by the test results during the commissioning of the gas turbine unit.

[0181] The simulation model built according to the given reference model and parameters shows that the primary frequency regulation of the gas turbine unit conforms to an ideal frequency regulation characteristic curve. A schematic diagram illustrating the relationship between the ideal frequency regulation characteristic curve and the measured data points is shown below. Figure 5 As shown in the figure, the frequency (speed) deviation of the gas turbine unit is plotted on the x-axis, and the primary frequency regulation power adjustment is plotted on the y-axis. The frequency regulation characteristic curve consists of three linear segments, as shown by the blue curve in the figure. However, in actual operation, the primary frequency regulation power adjustment of the gas turbine unit in the low-frequency deviation segment, as marked by the red five-pointed star in the figure, does not fall on the ideal frequency regulation characteristic curve. Therefore, correction is required. Figure 4 The model parameters in the model.

[0182] The model parameters are corrected as follows: By gradually reducing the dead zone range of module f(x) and decreasing its droop coefficient, the actual operating point at this frequency offset is brought back to the theoretical frequency regulation characteristic curve. For each actually obtainable operating point, the f(x) parameters are adjusted piecewise until all measured points fall on the corrected curve. The curve obtained by fitting the curve is the actual primary frequency regulation characteristic curve of the unit, such as... Figure 6 As shown by the purple curve in the image.

[0183] Figure 7 This illustration shows a schematic diagram of the frequency modulation command power curve and the actual power curve of a generator unit receiving AGC commands, provided in an exemplary embodiment of this disclosure. The green curve represents the actual power curve of the generator unit receiving AGC commands, and the blue curve represents the frequency modulation command power curve of the generator unit receiving AGC commands. According to... Figure 6 The actual primary frequency modulation characteristic curve shown is the regulated power of the computer group's primary frequency modulation, and the actual generated power curve of the unit receiving AGC commands ( Figure 7 Subtract the frequency modulation adjustment power from the green curve in the graph.

[0184] Assess the actual operating conditions of the unit and preset the time window T for evaluating the power curve. w =60s; according to The actual power generation curve of the unit receiving AGC commands is shifted forward along the time axis at intervals of t = 1s. Taking a segment as an example, such as... Figure 8 As shown, the actual power generation curve before the shift is the blue curve, and the actual power generation curve after the shift is the green curve. Throughout the entire evaluation period, for each point in time on the curve, the absolute value of the difference between the frequency regulation command power and the actual power generation of the unit is calculated as the regulation power deviation, i.e. Figure 8 The absolute value of the difference between the red dashed line and the green solid line at each time point is used to sum the adjustment power deviations over all time points to obtain the cumulative deviation S of the actual generated power. i This can be approximated by the area of ​​the green shaded region in the diagram, based on the concept of difference. Repeat the previous step until the cumulative translation time interval is ≥ T. w S is calculated for each translation. i Sort the data, and find the smallest S. i corresponding T i This is the estimated value of the second frequency modulation response time. T=25s. The power duration interval in the frequency modulation command power curve of the unit accepting AGC commands is less than... For the curve period T, remove the actual power output curves of units receiving AGC commands within the same time period. Perform digital filtering on the actual power output curves of units receiving AGC commands, segmenting the actual power output curves and frequency regulation command power curves of units receiving AGC commands into fixed power ranges. Based on the actual power output curves of units receiving AGC commands, identify the effective evaluation segments of the unit's frequency regulation capability within the curve. On the effective evaluation segments of the curve unit's frequency regulation capability, calculate the target evaluation indicators used to indicate the secondary frequency regulation capability of the gas turbine unit, such as... Figure 9 As shown, the target evaluation index can be defined as:

[0185] (1) Response time: refers to the time required for the unit output to correctly change in the direction of adjustment after the AGC command of the system changes. The calculation method is the time difference between the moment the AGC command begins to change and the moment the actual power output of the unit begins to change correctly. The expression for the response time index is as follows:

[0186]

[0187] in, For response time; This is the moment when the unit's actual power output begins to change correctly. This is the moment when the AGC instruction begins to change.

[0188] (2) Adjustment rate: The slope of the line connecting the actual power output to the two actual power output points of 10% and 90% of the AGC load command target. The index expression of the adjustment rate is as follows:

[0189]

[0190] in, To adjust the rate; This refers to the moment when the actual power output first reaches 10% of the commanded change. This refers to the moment when the actual power output first reaches 90% of the commanded change. For at any time The actual power output value; For at any time The actual power output value.

[0191] (3) Regulation accuracy: Under stable unit conditions, the deviation between the actual generated power and the AGC command during the assessment period. The expression for regulation accuracy is as follows:

[0192]

[0193] in, To adjust the precision; This marks the start time of the assessment period. This is the end time of the assessment period. It is the actual power output of the unit within a certain period of time. It is the command power value of the AGC commands received by the unit during this period.

[0194] In summary, this embodiment of the present disclosure effectively evaluates the primary and secondary frequency regulation capabilities of a gas turbine unit during actual operation by utilizing measured operating curve data from the unit's participation in the frequency regulation process. By basing the evaluation on real historical operating data rather than idealized design parameters, the evaluation results better reflect the unit's actual performance. Furthermore, it clearly distinguishes between the frequency regulation capabilities of primary frequency regulation (rapid response to frequency fluctuations) and secondary frequency regulation (tracking AGC commands), two different time scales and control objectives, and adopts a strategy of "first calibrating the primary frequency regulation model, then evaluating the secondary frequency regulation capability," avoiding mutual interference between the two frequency regulation functions and making the evaluation of the secondary frequency regulation capability purer and more accurate.

[0195] This disclosure also defines the "primary frequency modulation response data" as including the "parameter deviation curve" (frequency / speed deviation) and the "power change curve". The "parameter deviation" is the input (excitation) and the "power change" is the output (response). The two constitute a complete input-output pair, which is the basis for system identification and parameter correction, and ensures that subsequent correction steps can be performed effectively.

[0196] This disclosure also introduces a "primary frequency regulation control model" (such as an f(x) function with dead zone and droop coefficient), and clarifies that the key model parameters that need to be corrected are the "primary frequency regulation dead zone" and the "droop coefficient". Correcting these two parameters can effectively make the model fit the actual static and dynamic characteristics of the unit's primary frequency regulation, laying the foundation for accurately separating the primary frequency regulation component from the actual generated power.

[0197] This disclosure further defines the "secondary frequency modulation response data" as including the "frequency modulation command power curve," the "actual power curve," and the "real-time parameter curve" (frequency / speed). The "frequency modulation command power curve" is the target, the "actual power curve" is the result, and the "real-time parameter curve" is used to explain the primary frequency modulation component mixed into the "actual power curve," making the crucial operation of "subtracting the primary frequency modulation component from the actual power" possible.

[0198] This embodiment of the disclosure also obtains a power change curve that only reflects the unit's response to AGC commands by subtracting the primary frequency regulation power from the actual power curve. After removing the primary frequency regulation interference, the true secondary frequency regulation response characteristics (such as delay and rate) of the unit are clearly displayed. The evaluation results will not be distorted by the magnitude of grid frequency fluctuations during the evaluation period, and can better reflect the performance of the unit's own control system.

[0199] This disclosure further refines the "preprocessing" steps, including filtering out AGC command oscillation segments, synchronously filtering out corresponding actual power segments, digital filtering, and power segmentation. On the one hand, this enhances the robustness and fairness of the evaluation, namely, filtering out segments where commands change too rapidly (intervals shorter than the unit's estimated response time), avoiding "misjudgments" caused by the unit's physical inability to respond in a timely manner, and ensuring that the evaluation is only performed on command segments for which the unit is capable of a complete response. On the other hand, it optimizes data quality, namely, digital filtering smooths measurement noise, and power segmentation facilitates refined analysis of frequency regulation performance under different load levels.

[0200] This disclosure also defines two typical forms of "effective evaluation segment": single instruction constant segment and continuous unidirectional instruction segment. These two segments correspond to the "step change" and "ramp change" scenarios of AGC instructions, respectively. They are typical operating conditions for evaluating the unit's response characteristics and tracking characteristics, ensuring the comprehensiveness of the evaluation.

[0201] This disclosure also clarifies that the "target evaluation index" includes at least one of the following indicators: response time, frequency modulation rate, and frequency modulation error. These three indicators characterize the secondary frequency modulation performance of the unit from three dimensions: speed (response time), capability (frequency modulation rate), and accuracy (frequency modulation error), respectively. Each indicator has a clear technical definition and calculation method, avoiding ambiguity and making the evaluation results of different units and at different times comparable.

[0202] The following are device embodiments of the present disclosure. For parts not described in detail in the device embodiments, please refer to the technical details disclosed in the above method embodiments.

[0203] Please refer to Figure 10 This illustration shows a schematic diagram of a gas turbine unit frequency regulation capability evaluation device based on measured data model parameter prediction, provided in an exemplary embodiment of this disclosure. The device can be implemented, in whole or in part, through software, hardware, or a combination of both, as a computing device. The device includes: an acquisition module 1002, a correction module 1004, and a determination module 1006.

[0204] The acquisition module 1002 is used to acquire historical measured operating data of the gas turbine unit. The historical measured operating data includes primary frequency regulation response data when the gas turbine unit does not receive the automatic generator control (AGC) command, and secondary frequency regulation response data when the gas turbine unit receives the AGC command.

[0205] The calibration module 1004 is used to calibrate the preset model parameters based on the primary frequency regulation response data. The calibrated model parameters are used to indicate the primary frequency regulation capability of the gas turbine unit.

[0206] The determination module 1006 is used to determine the target evaluation index based on the corrected model parameters and secondary frequency regulation response data. The target evaluation index is used to indicate the secondary frequency regulation capability of the gas turbine unit.

[0207] In one possible implementation, the primary frequency regulation response data includes a parameter deviation curve and a power change curve. The parameter deviation curve is the curve showing the change of time between the actual grid frequency or the actual speed of the gas turbine and the standard set value. The power change curve is the curve showing the change of the active power output value of the gas turbine over time.

[0208] In another possible implementation, the device also includes:

[0209] The acquisition module 1002 is also used to acquire a preset primary frequency control model, which is a parameterized mathematical model used to convert frequency deviation or speed deviation into primary frequency power adjustment amount.

[0210] The correction module 1004 is also used to correct the model parameters in the primary frequency control model according to the parameter deviation curve and the power change curve. The model parameters include the primary frequency dead zone and the droop coefficient. The primary frequency dead zone is the range of frequency deviation or speed deviation in the primary frequency control of the gas turbine unit without power regulation. The droop coefficient is the relative change in system frequency or unit speed of the gas turbine unit from no load to full load.

[0211] In another possible implementation, the secondary frequency regulation response data includes the frequency regulation command power curve, the actual power curve, and the real-time parameter curve. The frequency regulation command power curve is the curve of the commanded power of the AGC command changing over time. The actual power curve is the curve of the actual power generated by the gas turbine unit changing over time during actual operation. The real-time parameter curve is the curve of the actual grid frequency or the actual speed of the gas turbine unit changing over time, which is recorded synchronously with the AGC command and the actual power curve.

[0212] In another possible implementation, the determining module 1006 is also used for:

[0213] Based on the corrected model parameters, the actual primary frequency regulation characteristic curve is determined. The actual primary frequency regulation characteristic curve is a curve showing the quantitative relationship between the frequency deviation change and the power regulation of the gas turbine unit.

[0214] Calculate the regulating power of the primary frequency regulation of the gas turbine unit based on the primary frequency regulation characteristic curve and real-time parameter curve;

[0215] The corrected actual power curve is obtained by subtracting the primary frequency modulation regulation power from the actual power curve.

[0216] Preprocessing is performed on the frequency modulation command power curve and the corrected actual power curve to identify the effective evaluation segment for evaluating the secondary frequency modulation capability;

[0217] In the effective assessment section, target assessment indicators are determined.

[0218] In another possible implementation, the determining module 1006 is also used for:

[0219] Based on the estimated value of the secondary frequency regulation response time of the gas turbine unit, the segments in the power curve of the frequency regulation command where the power duration time interval is less than the estimated value are filtered out.

[0220] In the corrected actual power curve, the segment that is in the same time period as the filtered segment of the frequency modulation command power curve is removed to obtain the filtered actual power curve.

[0221] The filtered actual power curve is digitally filtered, and the filtered actual power curve and the corresponding frequency modulation command power curve are segmented according to a fixed power range.

[0222] Based on the segmented actual power curve and the segmented frequency modulation command power curve, the effective evaluation segment for evaluating the secondary frequency modulation capability is identified.

[0223] In another possible implementation, efficient segment evaluation includes:

[0224] The first type of segment corresponds to a first time period in which a single AGC command remains constant, and the actual power output of the gas turbine unit changes within the first time period in accordance with a first preset morphological characteristic; and / or,

[0225] The second type of segment corresponds to the second time period of multiple consecutive unidirectional AGC commands, and the actual power output of the gas turbine unit changes within the second time period meets the second preset morphological characteristics.

[0226] In another possible implementation, the target evaluation metrics include at least one of the following metrics:

[0227] Response time is the time difference between the moment the AGC command changes and the moment when the actual power output of the gas turbine unit begins to show continuous and unidirectional tracking changes.

[0228] Frequency regulation rate is the average adjustment speed calculated based on the rate of change of actual power over time within a specific percentage range of the command change during the power tracking process of the gas turbine unit in response to AGC commands.

[0229] Frequency regulation error is the average absolute value of the deviation between the actual power output and the commanded power output of the gas turbine unit after the gas turbine unit completes the tracking process of a single AGC command until the next command change.

[0230] It should be noted that the above embodiments only illustrate the division of the above functional modules when implementing the device. In actual applications, the above functions can be assigned to different functional modules according to actual needs, that is, the content structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0231] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0232] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0233] This disclosure also provides a gas turbine unit frequency regulation capability evaluation device based on measured data model parameter prediction, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0234] This disclosure also provides a non-volatile computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0235] This disclosure also provides a computer program product, including a computer program or a non-volatile computer-readable storage medium carrying the computer program, wherein the computer program, when executed by a processor, implements the steps of the above method.

[0236] Figure 11 This is a block diagram illustrating an apparatus 1900 according to an exemplary embodiment. For example, apparatus 1900 may be provided as a server or terminal device for executing the above-described method for evaluating the frequency regulation capability of a gas turbine unit based on measured data model parameter prediction. (Refer to...) Figure 11 The apparatus 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0237] Device 1900 may also include a power supply component 1926 configured to perform power management of device 1900, a wired or wireless network interface 1950 configured to connect device 1900 to a network, and an input / output interface 1958 (I / O interface). Device 1900 can operate on an operating system, such as Windows Server, stored in memory 1932. TM macOS X TM Unix TM Linux TM FreeBSD TM Or similar.

[0238] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of the device 1900 to perform the above-described method.

[0239] Computer-readable storage media can be tangible devices capable of holding and storing programs / instructions used by instruction execution devices. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0240] The computer program (or computer-readable program instructions) described herein can be downloaded from a computer-readable storage medium to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage medium in the respective computing / processing device.

[0241] The computer program (or computer program instructions) used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions to implement various aspects of this disclosure.

[0242] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0243] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0244] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0245] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0246] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for evaluating the frequency regulation capability of gas turbine units based on measured data model parameter prediction, characterized in that, The method includes: Acquire historical measured operating data of the gas turbine unit, including primary frequency regulation response data when the gas turbine unit does not receive the automatic generation control (AGC) command, and secondary frequency regulation response data when the gas turbine unit receives the AGC command; The preset model parameters are corrected based on the primary frequency regulation response data, and the corrected model parameters are used to indicate the primary frequency regulation capability of the gas turbine unit. Based on the corrected model parameters and the secondary frequency regulation response data, a target evaluation index is determined, which is used to indicate the secondary frequency regulation capability of the gas turbine unit.

2. The method according to claim 1, characterized in that, The primary frequency regulation response data includes a parameter deviation curve and a power change curve. The parameter deviation curve is the curve showing the change of time between the actual frequency of the power grid or the actual speed of the gas turbine unit and the standard set value. The power change curve is the curve showing the change of time between the active power output value of the gas turbine unit and the standard set value.

3. The method according to claim 2, characterized in that, Before correcting the preset model parameters based on the primary frequency modulation response data, the process also includes: Obtain a preset primary frequency control model, wherein the primary frequency control model is a parameterized mathematical model used to convert frequency deviation or speed deviation into primary frequency power adjustment amount; The step of correcting the preset model parameters based on the primary frequency modulation response data includes: Based on the parameter deviation curve and the power change curve, the model parameters in the primary frequency regulation control model are corrected. The model parameters include the primary frequency regulation dead zone and the droop coefficient. The primary frequency regulation dead zone is the range of frequency deviation or speed deviation in the primary frequency regulation of the gas turbine unit without power adjustment. The droop coefficient is the relative change in system frequency or unit speed of the gas turbine unit from no-load to full-load.

4. The method according to any one of claims 1 to 3, characterized in that, The secondary frequency regulation response data includes a frequency regulation command power curve, an actual power curve, and a real-time parameter curve. The frequency regulation command power curve is the curve showing the change of the command power of the AGC command over time. The actual power curve is the curve showing the change of the actual power of the gas turbine unit over time during actual operation. The real-time parameter curve is the curve showing the change of the actual grid frequency or the actual speed of the gas turbine unit over time, recorded synchronously with the AGC command and the actual power curve.

5. The method according to claim 4, characterized in that, The step of determining the target evaluation index based on the corrected model parameters and the secondary frequency modulation response data includes: Based on the corrected model parameters, the actual primary frequency regulation characteristic curve is determined. The actual primary frequency regulation characteristic curve is a curve showing the quantitative relationship between the frequency deviation change and the power regulation of the gas turbine unit. The regulating power of the primary frequency regulation of the gas turbine unit is calculated based on the primary frequency regulation characteristic curve and the real-time parameter curve. The corrected actual power curve is obtained by subtracting the primary frequency modulation adjustment power from the actual power curve. The frequency modulation command power curve and the corrected actual power curve are preprocessed to identify the effective evaluation segment for evaluating the secondary frequency modulation capability. The target evaluation index is determined within the effective evaluation segment.

6. The method according to claim 5, characterized in that, The preprocessing of the frequency modulation command power curve and the corrected actual power curve to identify the effective evaluation segment for assessing the secondary frequency modulation capability includes: Based on the estimated value of the secondary frequency regulation response time of the gas turbine unit, the segments in the power curve of the frequency regulation command where the power duration time interval is less than the estimated value are filtered out; In the corrected actual power curve, the segment that is in the same time period as the filtered segment of the frequency modulation command power curve is removed to obtain the filtered actual power curve. The filtered actual power curve is digitally filtered, and the filtered actual power curve and the corresponding frequency modulation command power curve are segmented according to a fixed power range. Based on the segmented actual power curve and the segmented frequency modulation command power curve, the effective evaluation segment for evaluating the secondary frequency modulation capability is identified.

7. The method according to claim 5 or 6, characterized in that, The effective evaluation segment includes: The first type of segment corresponds to a first time period in which a single AGC command remains constant, and the actual power output of the gas turbine unit during the first time period satisfies a first preset morphological characteristic; and / or, The second type of segment corresponds to the second time period of multiple consecutive AGC commands in the same direction, and the actual power output of the gas turbine unit changes within the second time period satisfies the second preset morphological characteristics.

8. The method according to any one of claims 1 to 5, characterized in that, The target evaluation indicators include at least one of the following indicators: The response time is the time difference between the moment when the AGC command changes and the moment when the actual power output of the gas turbine unit begins to show continuous and unidirectional tracking changes. Frequency regulation rate, which is the average adjustment speed calculated based on the rate of change of actual power over time within a specific percentage range of the change in the command during the power tracking process of the gas turbine unit responding to the AGC command; Frequency modulation error, which is the average absolute value of the deviation between the actual power output and the commanded power output of the gas turbine unit after the gas turbine unit completes the tracking process of a single AGC command until the next command change.

9. A device for evaluating the frequency regulation capability of a gas turbine unit based on measured data model parameter prediction, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

10. A non-volatile computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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