A method and system for grid connection testing of heavy-duty gas turbines

Abstract

This invention discloses a method and system for grid-connected testing of heavy-duty gas turbines. The system includes a grid-coupled load regulation module for directly coupling the heavy-duty gas turbine to the power grid; a data acquisition module for acquiring data from multiple sensors and preprocessing the raw data to obtain first data; a real-time grid disturbance input module for acquiring grid disturbance signals; a multi-strategy collaborative control and protection module for controlling the gas turbine based on the first data and disturbance signals, using a target emergency strategy determined by a three-layer distributed architecture; and a central integrated test management module for evaluating the control strategies in the target emergency strategy and generating corresponding analysis reports. This invention restores the electromechanical coupling nature of grid-connected gas turbine operation, achieves real-world operating condition reproduction, provides reliable data for dynamic control logic optimization, realizes closed-loop verification of the target emergency strategy under grid fault conditions, and ensures the comprehensiveness and accuracy of the test results.

Description

Technical Field

[0001] This invention relates to the field of gas turbine testing technology, and in particular to a method and system for grid-connected testing of heavy-duty gas turbines. Background Technology

[0002] Before a heavy-duty gas turbine is put into operation, it needs to undergo rigorous whole-machine testing to verify its performance indicators and operational reliability.

[0003] In related technologies, whole-machine testing is conducted using an off-grid test bench based on a hydraulic dynamometer. The off-grid test bench can consist of a heavy-duty gas turbine, a hydraulic dynamometer, an independent control system, and a conventional data acquisition unit. The corresponding testing method involves adjusting the opening of the hydraulic dynamometer's drain valve to change the water resistance torque, thereby simulating different mechanical loads on the gas turbine. This allows the turbine to reach a steady-state operating point at a preset speed, and then its steady-state performance parameters such as power, efficiency, and exhaust temperature are measured.

[0004] However, throughout the entire testing process, all the mechanical work output by the gas turbine was absorbed by the hydraulic dynamometer and converted into heat energy dissipation, completely isolating the test system from the actual power system (grid). Based on this, the testing methods in related technologies cannot reproduce the electrical load characteristics of a real power grid, and the gas turbine's output power during the test can only be dissipated through the hydraulic dynamometer, making it impossible to achieve power conversion and long-distance transmission under grid-connected conditions. This results in significant differences between the test conditions and actual grid-connected operation conditions. Furthermore, constrained by mechanical inertia and the physical limits of hydraulic regulation, the hydraulic dynamometer cannot quickly and accurately simulate millisecond-level transient processes such as grid load jumps and load shedding, making it impossible to effectively verify key dynamic performance aspects such as governor response under grid frequency fluctuations. Additionally, the aforementioned test system itself lacks any grid fault simulation and grid-connected interaction functions, failing to reproduce real fault scenarios such as grid voltage drops, frequency fluctuations, and short circuits. Consequently, it cannot assess the rationality of the gas turbine's control and protection logic under grid disturbances or whether its emergency response capabilities meet standards, leading to inaccurate and incomplete test results. Therefore, there is an urgent need for a grid connection testing system for heavy-duty gas turbines to comprehensively verify their grid connection adaptability and rapid response control capabilities. Summary of the Invention

[0005] This invention provides a method and system for testing the grid connection of heavy-duty gas turbines, in order to solve the technical problems of inaccurate and incomplete testing and inability to verify rapid response control capabilities in the prior art.

[0006] To address this, this invention proposes a heavy-duty gas turbine grid-connected testing system. At the physical level, it replicates the electromechanical coupling nature of gas turbine grid-connected operation through a grid-coupled load regulation module, achieving real-world operating condition reproduction. Furthermore, it utilizes a data acquisition module and a real grid disturbance input module to accurately capture transient processes such as load shedding, providing a reliable data foundation for dynamic control logic optimization. Simultaneously, through a millisecond-level low-latency multi-strategy collaborative control and protection module and a central integrated test management module, it achieves closed-loop verification of target emergency strategies under real grid fault conditions, ensuring the comprehensiveness and accuracy of the test results.

[0007] Another objective of this invention is to provide a test method for grid connection of heavy-duty gas turbines.

[0008] To achieve the above objectives, the present invention provides a heavy-duty gas turbine grid connection testing system, comprising:

[0009] A grid-coupled load regulation module is used to directly couple a heavy-duty gas turbine to the power grid, so that the speed of the gas turbine is locked by the frequency of the power grid.

[0010] The data acquisition module is connected to the heavy-duty gas turbine and the power grid coupling load regulation module. It is used to synchronously acquire multi-source sensor data through a group of sensors distributed in key parts of the gas turbine and generator, and to preprocess the acquired raw data to obtain the first data.

[0011] A real power grid disturbance input module is connected to the power grid coupled load adjustment module to acquire disturbance signals from the power grid.

[0012] A multi-strategy collaborative control and protection module is connected to the real disturbance input module of the power grid, the data acquisition module and the heavy-duty gas turbine respectively. It is used to determine the target emergency strategy of the gas turbine based on the first data and the disturbance signal, using a three-layer distributed architecture, and to control the gas turbine based on the target emergency strategy.

[0013] The central integrated test management module is connected to the data acquisition module and the multi-strategy collaborative control and protection module, respectively, and is used to evaluate the control strategies in the target emergency strategy based on the first data and generate corresponding analysis reports.

[0014] The heavy-duty gas turbine grid connection test system of this invention may also have the following additional technical features:

[0015] In this embodiment of the invention, the grid-coupled load regulation module further includes a generator, a generator output circuit breaker, and a grid connection unit, wherein,

[0016] The rotor shaft of the generator is rigidly connected to the output shaft of the gas turbine;

[0017] The input terminal of the generator output circuit breaker is electrically connected to the stator output terminal of the generator;

[0018] The power grid connection unit is electrically connected to the output terminal of the generator outlet circuit breaker via a transformer, and is used to connect to the real power grid.

[0019] In this embodiment of the invention, the data acquisition module includes a sensor array, a multi-channel high-speed data acquisition module, a unified clock source, and a front-end data processing module, wherein...

[0020] The sensor group includes a high-precision speed sensor, a high-speed temperature sensor, a pressure sensor, a vibration sensor, an electrical measurement unit, and a valve position sensor, which are used to collect the operating parameters of the gas turbine and / or the generator, respectively.

[0021] A multi-channel high-speed data acquisition module is connected to the output of the sensor group;

[0022] A unified clock source is connected to each acquisition channel of the multi-channel high-speed data acquisition module to synchronize the time of all acquisition channels;

[0023] The front-end data processing module is connected to the output of the multi-channel high-speed data acquisition module and is used to preprocess the acquired raw data using a wavelet transform algorithm to obtain the first data.

[0024] In this embodiment of the invention, the multi-strategy collaborative control and protection module includes a power grid protection and regulation submodule, a gas turbine control interface submodule, and an emergency strategy execution submodule, wherein,

[0025] The power grid protection and regulation submodule is connected to the data acquisition module and is used to identify power grid faults and generate fault events based on the first data when a disturbance signal is received, and to perform power grid support functions when there are no faults.

[0026] The emergency strategy execution submodule is connected to the power grid protection and regulation submodule, and is used to determine the corresponding target emergency strategy based on the fault event and the first data, and parse the target emergency strategy into a time-series instruction sequence.

[0027] The gas turbine control interface submodule is connected to the emergency strategy execution submodule and the gas turbine, respectively, and is used to generate a target control quantity based on the timing command sequence through a control algorithm, and to control the gas turbine based on the target control quantity.

[0028] In this embodiment of the invention, the step of identifying power grid faults and generating fault events based on the first data, and performing power grid support functions when there are no faults, includes:

[0029] The first data is filtered and converted from digital to analog to obtain the second data, and a unified time tag is added to the second data;

[0030] Extract the multidimensional electrical features from the second data to obtain a multidimensional feature vector;

[0031] The multidimensional feature vector is input into a multi-feature fusion detection algorithm to obtain the target fault type, and a fault event is generated based on the target fault type and the corresponding fault information.

[0032] If no fault is found, the deviation between the grid frequency and the rated value is calculated based on the first data, and the grid is actively supported for primary frequency regulation according to the deviation and the preset gas turbine primary frequency regulation characteristic curve and droop coefficient.

[0033] In this embodiment of the invention, determining the corresponding target emergency strategy based on the fault event and the first data, and parsing the target emergency strategy into a time-series instruction sequence, includes:

[0034] Based on the fault event and the first data, a first candidate emergency strategy set is determined through a preset strategy library;

[0035] The first candidate emergency strategy set is filtered using the Rete algorithm to obtain the second candidate emergency strategy set;

[0036] Based on the preset strategy priority rules, the candidate emergency strategies in the second candidate emergency strategy set are prioritized and sorted, and the candidate emergency strategy with the highest priority is determined as the target emergency strategy.

[0037] The target emergency strategy is broken down into a sequence of time-series instructions, which are then issued based on a preset time order and a first preset rule.

[0038] In this embodiment of the invention, the preset strategy library includes a basic strategy layer, a composite strategy layer, and a self-adaptive strategy layer; the step of determining a first candidate emergency strategy set based on the fault event and the first data through the preset strategy library includes:

[0039] Based on the fault event and the first data, the composite strategy layer matches a basic strategy set from the basic strategy layer, and uses a finite state machine to combine the basic strategy set to obtain a third candidate emergency strategy set.

[0040] The self-adaptive strategy layer determines the fuzzy input quantity based on the fault event and the first data, and dynamically optimizes the adjustable parameters of the composite strategy in the third candidate emergency strategy set by matching preset fuzzy rules through a fuzzy inference algorithm to obtain a fourth candidate emergency strategy set, wherein the basic combination of the composite strategies in the fourth candidate emergency strategy set remains unchanged.

[0041] The fourth candidate emergency strategy set is determined as the first candidate emergency strategy set.

[0042] In this embodiment of the invention, the step of generating a target control quantity based on the timing command sequence using a control algorithm, and controlling the gas turbine based on the target control quantity, includes:

[0043] Based on the timing instruction sequence, a target control quantity is generated through the corresponding control algorithm, wherein the control algorithm includes one or more of the following: power-fuel feedforward compensation algorithm, speed change rate suppression algorithm, exhaust temperature dispersion balancing algorithm, and compressor surge boundary protection algorithm;

[0044] Priority arbitration is performed between the instructions in the timing instruction sequence and the native instructions in the gas turbine, and the gas turbine is controlled based on the priority order and the corresponding target control quantity.

[0045] In this embodiment of the invention, the step of evaluating the control strategy in the target emergency strategy based on the first data and generating a corresponding analysis report includes:

[0046] The data acquisition module acquires the third data after the control strategy is executed, and determines whether the dynamic response of the gas turbine meets the design requirements based on the third data and the first data, thus obtaining the first test result;

[0047] The target emergency strategy and its action sequence invoked by the multi-strategy collaborative control and protection module are compared with the preset emergency strategy library to obtain the second test result;

[0048] Determine the fault trigger time and the control command issuance time of the multi-strategy collaborative control and protection module, and verify whether the total response time meets the system design specifications based on the fault trigger time and the control command issuance time to obtain the third test result;

[0049] The measured curves obtained based on the gas turbine operating data are superimposed and compared with the design envelope to obtain the fourth test result.

[0050] Based on the first test result, the second test result, the third test result, and the fourth test result, a corresponding analysis report is generated.

[0051] To achieve the above objectives, another aspect of the present invention proposes a test method for grid connection of heavy-duty gas turbines, the method comprising:

[0052] The heavy-duty gas turbine is directly coupled to the power grid, so that the rotational speed of the gas turbine is locked by the frequency of the power grid;

[0053] By using a group of sensors distributed in key parts of the gas turbine and generator, multi-source sensor data is collected synchronously, and the collected raw data is preprocessed to obtain the first data.

[0054] Acquire the disturbance signal of the power grid;

[0055] Based on the first data and the disturbance signal, a three-layer distributed architecture is used to determine the target emergency strategy for the gas turbine, and the gas turbine is controlled based on the target emergency strategy.

[0056] The control strategies in the target emergency response strategy are evaluated based on the first data, and a corresponding analysis report is generated.

[0057] The heavy-duty gas turbine grid-connected testing method and system of this invention includes a grid-coupled load regulation module for directly coupling the heavy-duty gas turbine to the power grid, thereby locking the speed of the gas turbine to the grid frequency; a data acquisition module connected to the heavy-duty gas turbine and the grid-coupled load regulation module for synchronously acquiring multi-source sensor data through a sensor group distributed at key parts of the gas turbine and generator, and preprocessing the acquired raw data to obtain first data; a grid real disturbance input module connected to the grid-coupled load regulation module for acquiring grid disturbance signals; a multi-strategy collaborative control and protection module connected to the grid real disturbance input module, the data acquisition module, and the heavy-duty gas turbine, respectively, for determining the target emergency strategy of the gas turbine based on the first data and the disturbance signal using a three-layer distributed architecture, and controlling the gas turbine based on the target emergency strategy; and a central integrated test management module connected to the data acquisition module and the multi-strategy collaborative control and protection module, for evaluating the control strategy in the target emergency strategy based on the first data and generating a corresponding analysis report. Therefore, this invention can restore the electromechanical coupling nature of gas turbine grid-connected operation at the physical level through the grid-coupled load regulation module, realizing the reproduction of real operating conditions. It also uses the data acquisition module and the real grid disturbance input module to accurately capture transient processes such as load shedding, providing a reliable data foundation for dynamic control logic optimization. At the same time, through the millisecond-level low-latency multi-strategy collaborative control and protection module and the central integrated test management module, it realizes the closed-loop verification of the target emergency strategy under real grid faults, ensuring the comprehensiveness and accuracy of the test results.

[0058] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0059] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0060] Figure 1 This is a schematic diagram of the structure of a heavy-duty gas turbine grid-connected testing system according to an embodiment of the present invention;

[0061] Figure 2 This is a schematic diagram of the operation process of a heavy-duty gas turbine grid-connected testing system according to an embodiment of the present invention;

[0062] Figure 3 This is a flowchart illustrating a method for testing a heavy-duty gas turbine connected to the grid according to an embodiment of the present invention. Detailed Implementation

[0063] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0064] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0065] The following description, with reference to the accompanying drawings, describes a method and system for testing the grid connection of heavy-duty gas turbines according to embodiments of the present invention.

[0066] Figure 1 This is a schematic diagram of the heavy-duty gas turbine grid connection test system according to an embodiment of the present invention.

[0067] like Figure 1 As shown, the heavy-duty gas turbine grid connection test system may include:

[0068] The grid-coupled load regulation module 101 is used to directly couple the heavy-duty gas turbine to the power grid, so that the speed of the gas turbine is locked by the grid frequency.

[0069] The data acquisition module 102 is connected to the heavy-duty gas turbine and the grid-coupled load regulation module. It is used to synchronously acquire multi-source sensor data through a group of sensors distributed in key parts of the gas turbine and generator, and to preprocess the acquired raw data to obtain the first data.

[0070] The real power grid disturbance input module 103 is connected to the power grid coupled load regulation module and is used to acquire the disturbance signal of the power grid.

[0071] The multi-strategy collaborative control and protection module 104 is connected to the real disturbance input module of the power grid, the data acquisition module and the heavy-duty gas turbine respectively. It is used to determine the target emergency strategy of the gas turbine based on the first data and the disturbance signal, and to control the gas turbine based on the target emergency strategy.

[0072] The central integrated test management module 105 is connected to the data acquisition module and the multi-strategy collaborative control and protection module, respectively, and is used to evaluate the control strategies in the target emergency strategy based on the first data and generate corresponding analysis reports.

[0073] In this embodiment of the invention, the above-mentioned grid coupling load regulation module 101 further includes a generator 1011, a generator output circuit breaker 1012, and a grid connection unit 1013.

[0074] In this embodiment of the invention, the rotor shaft of the generator is rigidly connected to the output shaft of the gas turbine; the input terminal of the generator output circuit breaker is electrically connected to the stator output terminal of the generator; the power grid connection unit is electrically connected to the output terminal of the generator output circuit breaker through a transformer, for connecting to the real power grid.

[0075] In this embodiment of the invention, a synchronous generator is used to directly couple the gas turbine to the power grid, replacing the traditional hydraulic dynamometer. This allows the speed of the gas turbine to be locked by the grid frequency, realizing the real conversion and transmission of mechanical power to electrical energy, thereby physically restoring the load characteristics of the gas turbine operating in grid connection.

[0076] In this embodiment of the invention, the above-mentioned grid-coupled load regulation module enables the heavy-duty gas turbine grid-connected test system to support steady-state testing across the entire load range, realistically reproducing millisecond-level transient processes such as load shedding and load step jumps; and by controlling the generator disconnection, the physical process of load shedding can be realistically reproduced, fully capturing dynamic responses such as speed surge, fuel cut-off, and anti-surge actions; and by receiving various real grid disturbances such as voltage drops, short circuits, and frequency fluctuations, the control logic and response speed of the gas turbine in primary frequency regulation, low-frequency oscillation suppression, and fault ride-through can be verified.

[0077] In this embodiment of the invention, the data acquisition module may include a sensor group 201, a multi-channel high-speed data acquisition module 202, a unified clock source 203, and a front-end data processing module 204.

[0078] In this embodiment of the invention, the aforementioned sensor group 201 may include a high-precision speed sensor (accuracy ≤ 0.5 rpm), a high-speed temperature sensor (response time ≤ 1.5 s), a pressure sensor (≤ 0.075% FS), a vibration sensor, an electrical measurement unit, and a valve position sensor (≤ 0.5% FS), respectively used to collect operating parameters of the gas turbine and / or generator. In this embodiment, the operating parameters may include three-phase voltage, current, frequency, active / reactive power, gas turbine speed, combustion chamber temperature, combustion chamber pulsating pressure, and fuel valve opening.

[0079] In this embodiment of the invention, the multi-channel high-speed data acquisition module is connected to the output of the sensor group.

[0080] In this embodiment of the invention, the aforementioned unified clock source is connected to each acquisition channel of the multi-channel high-speed data acquisition module to synchronize the time of all acquisition channels, ensuring that all parameters are recorded on the same time reference, thus solving the problem of inconsistent time of multi-source sensor data.

[0081] In this embodiment of the invention, the front-end data processing module is connected to the output of the multi-channel high-speed data acquisition module, and is used to preprocess the acquired raw data using a wavelet transform algorithm to obtain the first data. The front-end data processing module can preprocess the raw data using a built-in wavelet transform algorithm to filter out noise and extract key features, thereby effectively reducing data transmission pressure.

[0082] In this embodiment of the invention, the sampling frequency of the data acquisition module is not less than 1000Hz, which can control the response delay to the millisecond level when transient events such as power grid faults are triggered, thereby providing a complete and reliable data foundation for subsequent dynamic analysis.

[0083] In this embodiment of the invention, the real disturbance input module of the power grid is connected to the power grid coupled load regulation module. When the power grid generates at least one real disturbance such as voltage drop, short circuit and frequency fluctuation, the real disturbance input module of the power grid can send a disturbance signal to represent the occurrence of a real fault disturbance in the power grid. When the power grid is running smoothly, the real disturbance input module of the power grid outputs a fault-free signal.

[0084] In this embodiment of the invention, the above-mentioned multi-strategy collaborative control and protection module includes a power grid protection and regulation submodule 1041, a gas turbine control interface submodule 1043, and an emergency strategy execution submodule 1042.

[0085] In this embodiment of the invention, the aforementioned power grid protection and regulation submodule 1041 is connected to the data acquisition module, and is used to identify power grid faults and generate fault events based on first data in response to receiving a disturbance signal, and to perform power grid support functions when there is no fault. In this embodiment of the invention, a fault-free state can be confirmed when a fault-free signal is received.

[0086] In this embodiment of the invention, the method for identifying power grid faults and generating fault events based on first data, and for performing power grid support functions when there are no faults, may include the following steps:

[0087] Step 1: Filter and perform analog-to-digital conversion on the first data to obtain the second data, and add a uniform time tag to the second data;

[0088] Step 2: Extract multidimensional electrical features from the second data to obtain a multidimensional feature vector;

[0089] Step 3: Input the multi-dimensional feature vector into the multi-feature fusion detection algorithm to obtain the target fault type, and generate a fault event based on the target fault type and the corresponding fault information;

[0090] Step 4: If no fault is found, calculate the deviation between the grid frequency and the rated value based on the first data, and actively support the grid primary frequency regulation according to the deviation and the preset gas turbine primary frequency regulation characteristic curve and droop coefficient.

[0091] In this embodiment of the invention, time-domain and frequency-domain features can be extracted from the collected voltage, current, and frequency signals to obtain feature values ​​of voltage amplitude, current abrupt change, frequency change rate, three-phase unbalance, and harmonic components, thereby obtaining a multi-dimensional fault feature vector.

[0092] In this embodiment of the invention, the multi-feature fusion detection algorithm may include a weighted fusion criterion algorithm or a machine learning algorithm. Specifically, in this embodiment, the weighted fusion criterion algorithm may assign weights and thresholds to each feature, and then perform a weighted summation based on the score and weight of each feature to determine a comprehensive score, and determine the fault type based on the comprehensive score. Furthermore, in this embodiment, the fault type may be determined based on a table showing the relationship between scores and fault types, using the comprehensive score.

[0093] In this embodiment of the invention, the machine learning algorithm described above can be any one of the following: SVM (Support Vector Machine), Random Forest, BP Neural Network, and Bayesian classification.

[0094] In this embodiment of the invention, the fault information may include the time when the fault occurred.

[0095] In one embodiment of the present invention, the deviation between the grid frequency and the rated value can be calculated based on the first data, and the active power output adjustment of the gas turbine can be determined according to the deviation and the preset gas turbine primary frequency regulation characteristic curve and the droop coefficient. Thus, the gas turbine control system can be quickly adjusted according to the active power output adjustment to increase or decrease the output to smooth frequency fluctuations and realize the gas turbine's active support for the primary frequency regulation of the grid.

[0096] In another embodiment of the present invention, the power grid protection and regulation submodule can also identify oscillation modes online based on the Prony algorithm and apply additional damping control through the power system stabilizer (PSS) to improve the system damping ratio, thereby suppressing low-frequency oscillations and realizing active support of the gas turbine for the power grid.

[0097] In this embodiment of the invention, the emergency strategy execution submodule 1042 is connected to the power grid protection and regulation submodule 1041, and is used to determine the corresponding target emergency strategy based on the fault event and the first data, and parse the target emergency strategy into a time-series instruction sequence.

[0098] In this embodiment of the invention, the method for determining the corresponding target emergency strategy based on the fault event and the first data, and parsing the target emergency strategy into a sequence of timing instructions, may include the following steps:

[0099] Step S1: Based on the fault event and the first data, determine the first candidate emergency strategy set through the preset strategy library;

[0100] Step S2: The first candidate emergency strategy set is filtered using the Rete algorithm to obtain the second candidate emergency strategy set;

[0101] Step S3: Based on the preset strategy priority rules, sort the candidate emergency strategies in the second candidate emergency strategy set by priority, and determine the candidate emergency strategy with the highest priority as the target emergency strategy.

[0102] Step S4: Decompose the target emergency strategy into a sequence of time-series instructions and issue them based on a preset time order and a first preset rule.

[0103] In this embodiment of the invention, the aforementioned preset strategy library may include a basic strategy layer, a composite strategy layer, and a self-adaptive strategy layer. Specifically, in this embodiment, the method for determining a first candidate emergency strategy set based on a fault event and first data using the preset strategy library includes the following steps:

[0104] In step S11, the composite strategy layer matches the basic strategy set from the basic strategy layer based on the fault event and the first data, and uses a finite state machine to combine the basic strategy set to obtain the third candidate emergency strategy set.

[0105] In this embodiment of the invention, based on gas turbine design specifications, protection logic diagrams, and power grid operation procedures, a variety of standard emergency strategies corresponding to different faults, such as emergency shutdown, rapid load reduction, and switching to islanded operation, can be extracted to obtain a basic strategy set.

[0106] In this embodiment of the invention, the composite strategy layer can be modeled using a finite state machine (FSM), that is, by using "preset rules + real-time judgment" to combine basic strategies into composite strategies according to different fault types. For example, assuming the fault type is a power grid short-circuit fault, the corresponding composite strategy is "rapid load reduction of 50% + strong excitation + load restoration after fault clearance".

[0107] Step S12: The self-applicable strategy layer determines the fuzzy input quantity based on the fault event and the first data, and dynamically optimizes the adjustable parameters of the composite strategy in the third candidate emergency strategy set by matching the preset fuzzy rules through the fuzzy inference algorithm, thereby obtaining the fourth candidate emergency strategy set. The basic combination of the composite strategies in the fourth candidate emergency strategy set remains unchanged.

[0108] In this embodiment of the invention, a fuzzy logic algorithm is introduced into the self-applicable strategy layer to use the first data quantification indicators (such as voltage drop depth, fault duration, and frequency offset) corresponding to different fault events as fuzzy input quantities. Furthermore, the aforementioned preset fuzzy rules can be parameter adjustment strategies corresponding to different fuzzy input quantities. For example, "if the voltage drop depth is ≥30% and the duration is >0.5s, the corresponding fast load reduction ratio is increased to 60%."

[0109] In this embodiment of the invention, the adjustment parameters of the composite strategy are dynamically optimized through fuzzy reasoning to form a fourth set of candidate emergency strategies adapted to the current fault, thereby improving the flexibility and pertinence of emergency response.

[0110] Step S13: The fourth candidate emergency strategy set is determined as the first candidate emergency strategy set.

[0111] In this embodiment of the invention, after obtaining the first candidate emergency strategy set through the above steps, the emergency strategy execution submodule 1042 can call the Rete algorithm to quickly retrieve the candidate emergency strategies in the first candidate emergency strategy set, and compare the currently detected fault type, the real-time operating status of the gas turbine in the first data with the strategy matching conditions of the first candidate emergency strategy set to select the second candidate emergency strategy set that matches the current scenario.

[0112] In this embodiment of the invention, after obtaining the second candidate emergency strategy set through the above steps, the candidate emergency strategies in the second candidate emergency strategy set can be prioritized according to a preset strategy priority rule, and the candidate emergency strategy with the highest priority can be determined as the target emergency strategy, thereby ensuring the rationality and urgency of the response action. For example, the preset strategy priority rule is emergency shutdown > rapid load reduction > islanding operation switchover.

[0113] In this embodiment of the invention, after obtaining the target emergency strategy through the above steps, the target emergency strategy can be decomposed into a sequence of time-series instructions, and issued based on a preset time order and a first preset rule. In this embodiment of the invention, the first preset rule can be a logical relationship.

[0114] In this embodiment of the invention, the methods of issuing different commands may vary. Specifically, in this embodiment of the invention, discrete commands such as tripping can be directly output through hardwiring, while continuous commands such as rapid load reduction are processed by the gas turbine control interface submodule algorithm and output as analog signals to the gas turbine TCS.

[0115] In this embodiment of the invention, the above-mentioned emergency strategy execution submodule is also used to continuously monitor key parameters during the execution of the target emergency strategy, and automatically trigger higher-level strategies, such as system shutdown, when the key parameters are abnormal, so as to form a closed-loop monitoring.

[0116] The gas turbine control interface submodule 1043 is connected to the emergency strategy execution submodule 1042 and the gas turbine, respectively. It is used to generate a target control quantity based on the timing command sequence through the control algorithm, and to control the gas turbine based on the target control quantity.

[0117] In this embodiment of the invention, the method for generating a target control quantity based on a timing command sequence using a control algorithm, and controlling the gas turbine based on the target control quantity, may include the following steps:

[0118] Step a: Based on the timing instruction sequence, generate the target control quantity through the corresponding control algorithm. The control algorithm includes one or more of the following: power-fuel feedforward compensation algorithm, speed change rate suppression algorithm, exhaust temperature dispersion balancing algorithm, and compressor surge boundary protection algorithm.

[0119] Step b involves arbitrating the priority of the instructions in the timing instruction sequence with the native instructions in the gas turbine, and controlling the gas turbine based on the priority order and the corresponding target control quantity.

[0120] In this embodiment of the invention, when a rapid load reduction is required in the timing command sequence, the power-fuel feedforward compensation algorithm can directly calculate the fuel adjustment amount based on the power change demand, issuing the command in advance of the TCS's own closed-loop regulation, thus shortening the response time. When a load shedding is required in the timing command sequence, the speed change rate suppression algorithm can adopt a method of rapid adjustment based on speed deviation to actively suppress speed spikes and prevent overspeed protection malfunctions or rotor overstress. The exhaust temperature dispersion balancing algorithm can calculate the exhaust temperature deviation of each combustion chamber through Kalman filtering to adjust the fuel distribution of each combustion chamber, avoiding local overheating and combustion instability, and extending the life of hot components. The compressor surge boundary protection algorithm can calculate the compressor's stable operating margin in real time, and automatically open the vent valve or trigger fuel limiting when it is lower than the safe value, preventing the compressor from entering the unstable operating region.

[0121] In this embodiment of the invention, a combination of voting mechanism and priority encoder can be used to arbitrate the priority of issued instructions and TCS native instructions. By comparing the importance of various instructions, the problem of multi-source instruction conflict can be resolved, ensuring that emergency instructions are executed first, and guaranteeing the safety and priority rationality of gas turbine emergency response.

[0122] In this embodiment of the invention, the control commands issued by the gas turbine control interface submodule 1043 may be simultaneously sent to the gas turbine control system TCS and the grid load regulation module. If the issued command is to disconnect the grid or to regulate the primary frequency, the circuit breaker needs to be disconnected or the generator excitation system needs to be regulated.

[0123] For example, after the power grid protection and regulation submodule 1041 detects a 50% voltage drop, it generates a fault event. The emergency strategy execution submodule 1042 matches the target emergency strategy of "rapidly reducing load by 50% when voltage drops" according to the current load, extracts the instruction sequence, and calculates the fuel correction value through the power-fuel feedforward algorithm of the gas turbine control interface submodule 1043 and outputs it to the TCS of the gas turbine. At the same time, the speed change rate suppression algorithm monitors the speed in real time to prevent overshoot, and completes the closed-loop response throughout the process.

[0124] In this embodiment of the invention, after the multi-strategy collaborative control and protection module 104 is executed, the central integrated test management module 105 can evaluate the control strategy in the target emergency strategy based on the first data and generate a corresponding analysis report.

[0125] In this embodiment of the invention, the method for evaluating the control strategies in the target emergency strategy based on the first data and generating a corresponding analysis report may include:

[0126] Step 1: Obtain the third data from the data acquisition module after the control strategy is executed, and determine whether the dynamic response of the gas turbine meets the design requirements based on the third data and the first data, thus obtaining the first test result;

[0127] In this embodiment of the invention, the accuracy of the gas turbine's dynamic response and control strategy is verified by comparing the parameter change curves before and after the fault with the third data and the first data. Specifically, the third data, obtained from millisecond-level multi-source data acquired by the high-speed synchronous data acquisition module, includes grid-side electrical quantities, gas turbine-side thermal parameters, and control and protection signals, forming a comprehensive time-domain curve. During analysis, the design specifications are first compared, and key parameters such as the speed fluctuation amplitude, exhaust temperature peak, and power recovery time during the fault period and recovery process are examined to determine whether the gas turbine's dynamic response meets the design requirements. If the key parameters of speed fluctuation amplitude, exhaust temperature peak, and power recovery time do not exceed the limits, the first test result is that the gas turbine's dynamic response meets the design requirements; otherwise, the first test result is that the gas turbine's dynamic response does not meet the design requirements.

[0128] Step 2: Compare the target emergency strategy and its action sequence called by the multi-strategy collaborative control and protection module with the preset emergency strategy library to obtain the second test result;

[0129] In this embodiment of the invention, after a fault is identified, it is checked whether the multi-strategy collaborative control and protection module 104 accurately calls the corresponding emergency strategy (such as fast load reduction instead of tripping the machine), and whether the timing of each action logic is consistent with the design. For example, whether the primary frequency regulation function correctly responds to frequency deviation, and whether the low-frequency oscillation suppression algorithm intervenes in time. If the target emergency strategy and its action timing called by the multi-strategy collaborative control and protection module are the same as the emergency strategies in the preset emergency strategy library, then the second test result is that the control strategy is correct; otherwise, the second test result is that the control strategy is incorrect.

[0130] Step 3: Determine the fault trigger time and the control command issuance time of the multi-strategy collaborative control and protection module, and verify whether the total response time meets the system design specifications based on the fault trigger time and the control command issuance time, and obtain the third test result;

[0131] In this embodiment of the invention, by marking the fault trigger time and the control command issuance time, the detection delay and execution delay are calculated respectively. If the total response time of the sum of the detection delay and the execution delay does not exceed the time threshold, the third test result is that the total response time meets the system design index; otherwise, the total response time does not meet the system design index.

[0132] Step four: The measured curves obtained based on the gas turbine operating data are superimposed and compared with the design envelope to obtain the fourth test result;

[0133] In this embodiment of the invention, the measured curves can be superimposed and compared with the design envelope, and the deviations between the measured values ​​and the limits of each index can be listed in tabular form. The fourth test results of dynamic response, control correctness and speed are also given, providing a quantitative basis for the optimization of the gas turbine control system and the verification of grid connection reliability.

[0134] Step 5: Based on the first test results, the second test results, the third test results, and the fourth test results, generate the corresponding analysis report.

[0135] In this embodiment of the invention, the central integrated test management module 105 is also connected to the data acquisition module and the power grid real disturbance input module to provide a graphical human-machine interface through an integrated host computer software system for test scheme configuration (defining load points and acquisition lists), automatic execution of the entire process, real-time monitoring and data visualization.

[0136] Figure 2 This is a schematic diagram illustrating the operation flow of a heavy-duty gas turbine grid-connected testing system according to an embodiment of the present invention. Figure 2 As shown, the operation process of the heavy-duty gas turbine grid-connected test system can include: the central integrated test management module 105 creates a test project (setting the target load and stable dwell time of the gas turbine) through the front-end page of the host computer software system; the multi-strategy collaborative control and protection module 104 establishes the grid-connected steady-state operating condition, adjusts the fuel supply, enables the gas turbine to drive the generator to accelerate to synchronous speed, closes the generator output circuit breaker to connect to the grid, and loads the generator to the target load point for stable operation; whether the grid real disturbance input module acquires the grid fault signal; when the grid fault signal is acquired, the data acquisition module 102 synchronously and at high speed records key parameters such as sudden changes in voltage and current in the electrical circuit; the grid protection and regulation submodule of the multi-strategy collaborative control and protection module 104 determines the fault event, prepares the action according to the preset logic (such as low voltage protection), and on the other hand, transmits the fault event to the emergency strategy execution submodule at high speed. The emergency strategy execution submodule determines the corresponding target emergency strategy based on the fault type in the fault event and sends control commands, such as rapid load adjustment commands or protection action commands, to the gas turbine controller through the gas turbine control interface submodule. Throughout the entire process, all key parameters of the gas turbine, such as speed, exhaust temperature, vibration, and fuel valve position, are fully recorded by the data acquisition module. The emergency strategy execution submodule determines whether the gas turbine is stable. When the gas turbine is determined to be stable, after the fault test is completed, the central integrated test management module 105 automatically generates a data report, including millisecond-level change curves of all physical and electrical parameters before and after the fault, to analyze whether the gas turbine's dynamic response meets the design requirements and whether the control strategy is correct and fast, thus completing the test. When the gas turbine is determined to be unstable, the emergency strategy execution submodule executes a trip / emergency shutdown.

[0137] The heavy-duty gas turbine grid-connected testing system of this invention includes a grid-coupled load regulation module for directly coupling the heavy-duty gas turbine to the power grid, thereby locking the turbine's speed to the grid frequency; a data acquisition module connected to both the heavy-duty gas turbine and the grid-coupled load regulation module, for synchronously acquiring multi-source sensor data through a sensor array distributed across key parts of the gas turbine and generator, and preprocessing the acquired raw data to obtain first data; a real grid disturbance input module connected to the grid-coupled load regulation module for acquiring disturbance signals from the power grid; a multi-strategy collaborative control and protection module connected to the real grid disturbance input module, the data acquisition module, and the heavy-duty gas turbine, for determining the target emergency strategy for the gas turbine based on the first data and the disturbance signal using a three-layer distributed architecture, and controlling the gas turbine based on the target emergency strategy; and a central integrated test management module connected to both the data acquisition module and the multi-strategy collaborative control and protection module, for evaluating the control strategy in the target emergency strategy based on the first data and generating a corresponding analysis report. Therefore, this invention can restore the electromechanical coupling nature of gas turbine grid-connected operation at the physical level through the grid-coupled load regulation module, realizing the reproduction of real operating conditions. It also uses the data acquisition module and the real grid disturbance input module to accurately capture transient processes such as load shedding, providing a reliable data foundation for dynamic control logic optimization. At the same time, through the millisecond-level low-latency multi-strategy collaborative control and protection module and the central integrated test management module, it realizes the closed-loop verification of the target emergency strategy under real grid faults, ensuring the comprehensiveness and accuracy of the test results.

[0138] To achieve the above embodiments, such as Figure 3 As shown, this embodiment also provides a test method for grid connection of heavy-duty gas turbines, which may include the following steps:

[0139] Step 301: Directly couple the heavy-duty gas turbine to the power grid so that the speed of the gas turbine is locked by the power grid frequency;

[0140] Step 302: Simultaneously collect multi-source sensor data through a sensor group distributed in key parts of the gas turbine and generator, and preprocess the collected raw data to obtain the first data.

[0141] Step 303: Obtain the disturbance signal of the power grid;

[0142] Step 304: Based on the first data and the disturbance signal, a three-layer distributed architecture is used to determine the target emergency strategy for the gas turbine, and the gas turbine is controlled based on the target emergency strategy;

[0143] Step 305: Evaluate the control strategies in the target emergency strategy based on the first data, and generate a corresponding analysis report.

[0144] For details regarding steps 301 to 305, please refer to the detailed descriptions in the above embodiments. These details will not be repeated here.

[0145] The proposed method for grid-connected testing of heavy-duty gas turbines involves directly coupling the gas turbine to the power grid, locking the turbine's speed to the grid frequency. Multi-source sensor data is simultaneously collected via a sensor array distributed across key components of the gas turbine and generator. The raw data is preprocessed to obtain initial data. Power grid disturbance signals are acquired. Based on the initial data and disturbance signals, a three-layer distributed architecture is used to determine the target emergency strategy for the gas turbine, and the gas turbine is controlled according to this strategy. The control strategy within the target emergency strategy is evaluated based on the initial data, and a corresponding analysis report is generated. Thus, this invention physically recreates the electromechanical coupling nature of grid-connected gas turbine operation, achieving real-world operating condition reproduction and accurately capturing transient processes such as load shedding. This provides a reliable data foundation for dynamic control logic optimization. Furthermore, it enables closed-loop verification of the target emergency strategy under real power grid faults, ensuring the comprehensiveness and accuracy of the test results.

[0146] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0147] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A heavy-duty gas turbine grid connection testing system, characterized in that, include: A grid-coupled load regulation module is used to directly couple a heavy-duty gas turbine to the power grid, so that the speed of the gas turbine is locked by the grid frequency. The data acquisition module is connected to the heavy-duty gas turbine and the power grid coupling load regulation module. It is used to synchronously acquire multi-source sensor data through a group of sensors distributed in key parts of the gas turbine and generator, and to preprocess the acquired raw data to obtain the first data. A real power grid disturbance input module is connected to the power grid coupled load adjustment module to acquire disturbance signals from the power grid. A multi-strategy collaborative control and protection module is connected to the real disturbance input module of the power grid, the data acquisition module and the heavy-duty gas turbine respectively. It is used to determine the target emergency strategy of the gas turbine based on the first data and the disturbance signal, using a three-layer distributed architecture, and to control the gas turbine based on the target emergency strategy. The central integrated test management module is connected to the data acquisition module and the multi-strategy collaborative control and protection module, respectively, and is used to evaluate the control strategies in the target emergency strategy based on the first data and generate corresponding analysis reports.

2. The system according to claim 1, characterized in that, The grid-coupled load regulation module also includes a generator, a generator output circuit breaker, and a grid connection unit, wherein... The rotor shaft of the generator is rigidly connected to the output shaft of the gas turbine; The input terminal of the generator output circuit breaker is electrically connected to the stator output terminal of the generator; The power grid connection unit is electrically connected to the output terminal of the generator outlet circuit breaker via a transformer, and is used to connect to the real power grid.

3. The system according to claim 1, characterized in that, The data acquisition module includes a sensor array, a multi-channel high-speed data acquisition module, a unified clock source, and a front-end data processing module. The sensor group includes a high-precision speed sensor, a high-speed temperature sensor, a pressure sensor, a vibration sensor, an electrical measurement unit, and a valve position sensor, which are used to collect the operating parameters of the gas turbine and / or the generator, respectively. A multi-channel high-speed data acquisition module is connected to the output of the sensor group; A unified clock source is connected to each acquisition channel of the multi-channel high-speed data acquisition module to synchronize the time of all acquisition channels; The front-end data processing module is connected to the output of the multi-channel high-speed data acquisition module and is used to preprocess the acquired raw data using a wavelet transform algorithm to obtain the first data.

4. The system according to claim 1, characterized in that, The multi-strategy collaborative control and protection module includes a power grid protection and regulation submodule, a gas turbine control interface submodule, and an emergency strategy execution submodule, wherein... The power grid protection and regulation submodule is connected to the data acquisition module and is used to identify power grid faults and generate fault events based on the first data when a disturbance signal is received, and to perform power grid support functions when there are no faults. The emergency strategy execution submodule is connected to the power grid protection and regulation submodule, and is used to determine the corresponding target emergency strategy based on the fault event and the first data, and parse the target emergency strategy into a time-series instruction sequence. The gas turbine control interface submodule is connected to the emergency strategy execution submodule and the gas turbine, respectively, and is used to generate a target control quantity based on the timing command sequence through a control algorithm, and control the gas turbine based on the target control quantity.

5. The system according to claim 4, characterized in that, The steps of identifying power grid faults and generating fault events based on the first data, and performing power grid support functions when there are no faults, include: The first data is filtered and converted from digital to analog to obtain the second data, and a unified time tag is added to the second data; Extract the multidimensional electrical features from the second data to obtain a multidimensional feature vector; The multidimensional feature vector is input into a multi-feature fusion detection algorithm to obtain the target fault type, and a fault event is generated based on the target fault type and the corresponding fault information. If no fault is found, the deviation between the grid frequency and the rated value is calculated based on the first data, and the grid is actively supported for primary frequency regulation according to the deviation and the preset gas turbine primary frequency regulation characteristic curve and droop coefficient.

6. The system according to claim 4, characterized in that, The step of determining the corresponding target emergency strategy based on the fault event and the first data, and parsing the target emergency strategy into a time-series instruction sequence, includes: Based on the fault event and the first data, a first candidate emergency strategy set is determined through a preset strategy library; The first candidate emergency strategy set is filtered using the Rete algorithm to obtain the second candidate emergency strategy set; Based on the preset strategy priority rules, the candidate emergency strategies in the second candidate emergency strategy set are prioritized and sorted, and the candidate emergency strategy with the highest priority is determined as the target emergency strategy. The target emergency strategy is broken down into a sequence of time-series instructions, which are then issued based on a preset time order and a first preset rule.

7. The system according to claim 6, characterized in that, The preset strategy library includes a basic strategy layer, a composite strategy layer, and a self-adaptive strategy layer; the step of determining a first candidate emergency strategy set based on the fault event and the first data through the preset strategy library includes: Based on the fault event and the first data, the composite strategy layer matches a basic strategy set from the basic strategy layer, and uses a finite state machine to combine the basic strategy set to obtain a third candidate emergency strategy set. The self-adaptive strategy layer determines the fuzzy input quantity based on the fault event and the first data, and dynamically optimizes the adjustable parameters of the composite strategy in the third candidate emergency strategy set by matching preset fuzzy rules through a fuzzy inference algorithm to obtain a fourth candidate emergency strategy set, wherein the basic combination of the composite strategies in the fourth candidate emergency strategy set remains unchanged. The fourth candidate emergency strategy set is determined as the first candidate emergency strategy set.

8. The system according to claim 4, characterized in that, The step of generating a target control quantity based on the timing command sequence using a control algorithm, and controlling the gas turbine based on the target control quantity, includes: Based on the timing instruction sequence, a target control quantity is generated through the corresponding control algorithm, wherein the control algorithm includes one or more of the following: power-fuel feedforward compensation algorithm, speed change rate suppression algorithm, exhaust temperature dispersion balancing algorithm, and compressor surge boundary protection algorithm; Priority arbitration is performed between the instructions in the timing instruction sequence and the native instructions in the gas turbine, and the gas turbine is controlled based on the priority order and the corresponding target control quantity.

9. The system according to claim 1, characterized in that, The evaluation of the control strategies in the target emergency response strategy based on the first data, and the generation of a corresponding analysis report, includes: The data acquisition module acquires the third data after the control strategy is executed, and determines whether the dynamic response of the gas turbine meets the design requirements based on the third data and the first data, thus obtaining the first test result; The target emergency strategy and its action sequence invoked by the multi-strategy collaborative control and protection module are compared with the preset emergency strategy library to obtain the second test result; Determine the fault trigger time and the control command issuance time of the multi-strategy collaborative control and protection module, and verify whether the total response time meets the system design specifications based on the fault trigger time and the control command issuance time to obtain the third test result; The measured curves obtained based on the gas turbine operating data are superimposed and compared with the design envelope to obtain the fourth test result. Based on the first test result, the second test result, the third test result, and the fourth test result, a corresponding analysis report is generated.

10. A method for grid-connected testing of a heavy-duty gas turbine, characterized in that, include: The heavy-duty gas turbine is directly coupled to the power grid, so that the speed of the gas turbine is locked by the power grid frequency; By using a group of sensors distributed in key parts of the gas turbine and generator, multi-source sensor data is collected synchronously, and the collected raw data is preprocessed to obtain the first data. Acquire the disturbance signal of the power grid; Based on the first data and the disturbance signal, a three-layer distributed architecture is used to determine the target emergency strategy for the gas turbine, and the gas turbine is controlled based on the target emergency strategy. The control strategies in the target emergency response strategy are evaluated based on the first data, and a corresponding analysis report is generated.

11. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the method as described in claim 10.

12. A computer storage medium, characterized in that, in, The computer storage medium stores computer-executable instructions; when executed by a processor, the computer-executable instructions can implement the method as described in claim 10.

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