Gas turbine peak regulation and frequency modulation control method and system based on model

Abstract

The invention provides a model-based gas turbine peak and frequency regulation control method and system. The method comprises the following steps: acquiring a first fuel instruction and a first VI GV / VGVs instruction input into a target gas turbine; inputting the first fuel command and the first VI GV / VGVs command into an online model of the target gas turbine to output model output data and model calculation measurement data; generating a fused signal value based on an actual measurement signal of the sensor, the model output data, and the model calculation measurement data; and inputting the fused signal value into the controller to replace the actual measurement value of the sensor so as to generate a second fuel instruction and a second VI GV / VGVs instruction, and inputting the second fuel instruction and the second VI GV / VGVs instruction into the target gas turbine and the online model for control adjustment. Therefore, the rapid response of the gas turbine VI GV / VGVs, the fuel quantity and the like is improved, the dynamic performance of load control, temperature control and the like of the gas turbine is improved, the flexible operation of rapid load change of the gas turbine during rapid peak regulation and frequency modulation of power grid dispatching is realized, and good peak regulation and frequency modulation control effects are achieved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of gas turbines, and particularly to a model-based peak shaving and frequency modulation control method and system for gas turbines. Background Art

[0002] A gas turbine is an impeller-type power machine that uses gas or liquid as fuel, converts the heat released during fuel combustion into useful work, and can rotate at high speed. It controls the increase or decrease of speed and load by changing the fuel quantity. A gas turbine is an efficient heat-work conversion type of power generation equipment and a core equipment in the fields of power generation and drive.

[0003] With the continuous improvement of the single-unit capacity and performance of gas turbines, their pressure ratio and turbine inlet temperature are also increasing. Currently, the designed value of the turbine inlet temperature of F / J / H-class gas turbines has exceeded 1400°C. To ensure the safe operation of gas turbines, the inlet temperature of the turbine must be limited within an effective range; at the same time, in order to make full use of the heat of the high-temperature exhaust gas of gas turbines and further improve the cycle efficiency, gas turbine power stations generally adopt the combined cycle mode of gas turbine - steam turbine, using the exhaust gas of the gas turbine to heat the feed water into high-temperature and high-pressure steam in the waste heat boiler and then sending it to the steam turbine to do work. To ensure that the waste heat boiler reaches a relatively high working efficiency, it is required that the exhaust temperature be maintained near the optimal temperature operating point of the waste heat boiler. Therefore, during the operation of gas turbines, it is necessary to control their exhaust temperature well, not only to limit the inlet and exhaust temperatures of the turbine to avoid over-temperature alarms or even trigger protection actions, but also to control and maintain the turbine exhaust temperature within a suitable working range to achieve the safe and efficient operation of the entire combined cycle unit. Summary of the Invention

[0004] The present disclosure aims to at least solve one of the technical problems in the related art to a certain extent.

[0005] For this reason, one object of the present disclosure is to propose a model-based gas turbine control method.

[0006] The second object of the present disclosure is to propose a model-based gas turbine control system.

[0007] The third object of the present disclosure is to propose a model-based gas turbine control device.

[0008] The fourth object of the present disclosure is to propose an electronic device.

[0009] The fifth object of the present disclosure is to propose a non-transitory computer-readable storage medium.

[0010] The sixth object of the present disclosure is to propose a computer program product.

[0011] To achieve the above object, an embodiment of the first aspect of the present disclosure provides a model-based gas turbine control method, including: obtaining a first fuel command and a first VIGV / VGVs command input to a target gas turbine; inputting the first fuel command and the first VIGV / VGVs command into an online model of the target gas turbine to output model output data and model calculation measurement data; generating a fusion signal value based on an actual measurement signal of a sensor, the model output data, and the model calculation measurement data; inputting the fusion signal value into a controller to replace the actual measurement value of the sensor, so as to generate a second fuel command and a second VIGV / VGVs command, and inputting the second fuel command and the second VIGV / VGVs command into the target gas turbine and the online model for control adjustment.

[0012] According to an embodiment of the present disclosure, inputting the fusion signal value into a controller to replace the actual measurement value of the sensor to generate a second fuel command and a second VIGV / VGVs command includes: obtaining a set value of a control quantity of the target gas turbine through the controller; comparing, by the controller, the fusion signal value with the set value of the control quantity, and generating the second fuel command and the second VIGV / VGVs command based on a comparison result.

[0013] According to an embodiment of the present disclosure, comparing the fusion signal value with the set value of the control quantity and generating the second fuel command and the second VIGV / VGVs command based on a comparison result includes: obtaining a fusion signal value and a set value of a control quantity of the target gas turbine, such as turbine exhaust temperature, turbine inlet temperature, gas turbine power, VIGV / VGVs opening, gas turbine fuel quantity, compressor inlet pressure, compressor inlet temperature, compressor outlet pressure, compressor outlet temperature, combustion chamber pressure, turbine exhaust diffuser pressure, etc.; generating the second fuel command and the second VIGV / VGVs command based on a comparison result between the fusion signal value and the set value of the control quantity.

[0014] According to an embodiment of the present disclosure, the method further includes: generating a third VIGV / VGVs command based on fuel-VIGV / VGVs feedforward and the second VIGV / VGVs command.

[0015] According to an embodiment of the present disclosure, obtaining the fuel quantity-VIGV / VGVs feedforward includes: obtaining historical operation data and current operating condition data of the target gas turbine; matching the current operating condition data with the historical operation data to obtain a historical VIGV / VGVs opening value in the successfully matched historical operation data; generating the fuel quantity-VIGV / VGVs feedforward based on the historical VIGV / VGVs opening value.

[0016] According to an embodiment of the present disclosure, the method further includes: obtaining the operating condition data of the target gas turbine through the controller; generating the second fuel command and the second VIGV / VGVs command by the controller based on the operating condition data and the comparison result.

[0017] According to an embodiment of the present disclosure, generating the fusion signal value based on the actual measurement signal of the sensor, the model output data, and the model calculation measurement data includes: subtracting the model output data from the model calculation measurement data to calculate and obtain a dynamic compensation value; adding the dynamic compensation value to the actual measurement signal to calculate and obtain the fusion signal value.

[0018] According to an embodiment of the present disclosure, the formula for calculating the fusion signal value is: where y accel is the acceleration signal fusion value, y meas is the actual measurement signal of the sensor, y model is the model calculation value, is the model calculation measurement value.

[0019] According to an embodiment of the present disclosure, the method further includes: adjusting the set parameters of the controller based on the model output data and the model calculation measurement data.

[0020] To achieve the above object, an embodiment of the second aspect of the present disclosure provides a model-based gas turbine control system, including: a target gas turbine, a controller, and an online model; wherein, the controller is configured to generate a first fuel command and a first VIGV / VGVs command, and input them into the target gas turbine and the online model; the online model is configured to output model output data and model calculation measurement data based on the first fuel command and the first VIGV / VGVs command; the controller is further configured to generate a fusion signal value based on the actual measurement signal of the sensor, the model output data, and the model calculation measurement data, and generate a second fuel command and a second VIGV / VGVs command, and then input the second fuel command and the second VIGV / VGVs command into the target gas turbine and the online model for control adjustment.

[0021] According to an embodiment of the present disclosure, the online model is further configured to: obtain a set value of the control quantity of the target gas turbine; compare the fusion signal value with the set value of the control quantity, and generate the second fuel command and the second VIGV / VGVs command based on the comparison result.

[0022] To achieve the above object, an embodiment of the third aspect of the present disclosure provides a model-based gas turbine control device, including: an acquisition module configured to acquire a first fuel command and a first VIGV / VGVs command input to a target gas turbine; an input module configured to input the first fuel command and the first VIGV / VGVs command into an online model of the target gas turbine to output model output data and model calculation measurement data; a generation module configured to generate a fusion signal value based on an actual measurement signal of a sensor, the model output data, and the model calculation measurement data; and a control module configured to input the fusion signal value into a controller to replace the actual measurement value of the sensor, so as to generate a second fuel command and a second VIGV / VGVs command, and input the second fuel command and the second VIGV / VGVs command into the target gas turbine and the online model for control adjustment.

[0023] To achieve the above object, an embodiment of the fourth aspect of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the model-based gas turbine control method as described in the embodiment of the first aspect of the present disclosure.

[0024] To achieve the above object, an embodiment of the fifth aspect of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the model-based gas turbine control method as described in the embodiment of the first aspect of the present disclosure.

[0025] To achieve the above object, an embodiment of the sixth aspect of the present disclosure provides a computer program product, including a computer program, where the computer program is used to implement the model-based gas turbine control method as described in the embodiment of the first aspect of the present disclosure when executed by a processor.

[0026] Thus, through the solution of the present disclosure, the rapid response of the gas turbine VIGV / VGVs, fuel quantity, etc. is improved, the dynamic performance of the gas turbine load control, temperature control, etc. is improved, the flexible operation of the gas turbine with rapid load change during the rapid peak shaving and frequency modulation of the power grid dispatching is realized, and good peak shaving and frequency modulation control effects are achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 is a schematic diagram of a model-based gas turbine control method according to an embodiment of the present disclosure;

[0028] Figure 2 is a schematic diagram of another model-based gas turbine control method according to an embodiment of the present disclosure Figure 2 ;

[0029] Figure 3 It is a schematic diagram of another model - based gas turbine control method according to an embodiment of the present disclosure. Figure 3 ;

[0030] Figure 4 It is a schematic diagram of the calculation principle of the fusion signal value according to an embodiment of the present disclosure;

[0031] Figure 5 It is a schematic diagram of the simulation comparison result of the response process of a model - based control method according to the present disclosure compared with the response process of the control method in the current technology;

[0032] Figure 6 It is a schematic diagram of a model - based gas turbine control system according to an embodiment of the present disclosure;

[0033] Figure 7 It is a schematic diagram of a model - based gas turbine control device according to an embodiment of the present disclosure;

[0034] Figure 8 It is a schematic diagram of an electronic device according to an embodiment of the present disclosure. Specific Embodiments

[0035] The embodiments of the present disclosure will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present disclosure, but should not be construed as a limitation of the present disclosure.

[0036] In the technical solution of the present disclosure, the acquisition, storage, use, processing, etc. of data all comply with the relevant regulations of relevant laws and regulations.

[0037] It should be noted that in the embodiments of the present application, some industry - existing solutions such as certain software, components, models, etc. may be mentioned. They should be regarded as exemplary. The purpose is only to illustrate the feasibility in the implementation of the technical solution of the present application, but it does not mean that the applicant has already or necessarily used this solution.

[0038] In the current technology, for the load and temperature control loops of gas turbines, generally, the deviation between the set value and the feedback value of the control variables (such as gas turbine power, temperature, angles of variable inlet guide vanes / variable guide vanes (VIGV / VGVs), etc.) is input into a proportional-integral-derivative controller (PID) to calculate the corresponding control commands (such as fuel quantity commands, VIGV / VGVs valve position commands, etc.). These commands act on the gas turbine and related equipment through actuators to achieve the control of gas turbine power, gas turbine turbine inlet temperature, and exhaust gas temperature. The traditional control strategy relies relatively heavily on the measured values of sensors. However, due to some limitations of the sensors themselves, such as feedback delay caused by hysteresis, inability to measure some parameters due to environmental requirements, and inaccurate measurement caused by temperature drift after long-term use, etc., the control effect will be affected. In the existing control schemes, when the gas turbine participates in peak shaving and frequency modulation control, especially when quickly adjusting the peak load and changing the load in response to the power grid dispatch, and when the gas turbine performs frequency modulation response control and other rapid load increase conditions, it is difficult to control the gas turbine turbine inlet temperature and exhaust gas temperature within a suitable range. The exhaust gas temperature of the gas turbine will fluctuate greatly or even exceed the temperature, resulting in the waste heat boiler not being able to maintain the optimal temperature operating point, affecting the economy of the unit and the safety of operation; at the same time, the turbine inlet temperature will also fluctuate greatly or even exceed the temperature, affecting the safe operation of the unit and even damaging the hot-end components of the gas turbine, causing significant losses.

[0039] To solve the above problems, the present disclosure proposes a model-based gas turbine control method, as Figure 1 shown. The model-based gas turbine control method includes the following steps:

[0040] S101, obtain a first fuel command and a first VIGV / VGVs command input to the target gas turbine.

[0041] The model-based gas turbine control method of the embodiments of the present application can be applied to the scenario of gas turbine dynamic control. The execution subject of the model-based gas turbine control of the embodiments of the present application can be the model-based gas turbine control device of the embodiments of the present application, and this model-based gas turbine control device can be set on an electronic device.

[0042] It should be noted that the first fuel command and the first VIGV / VGVs command can be manually established or can be automatically generated by the controller according to the actual operating condition data of the gas turbine and the working data feedback by the sensors, and no limitation is made here.

[0043] S102. Input the first fuel command and the first VIGV / VGVs command into the online model of the target gas turbine to output model output data and model calculation measurement data.

[0044] In the embodiments of the present disclosure, the fuel command is the fuel data that the target gas turbine needs to inject at the current or a future timestamp. The fuel data can include various types and is not limited herein. For example, the fuel data can include the fuel type, fuel quantity, etc.

[0045] The VIGV / VGVs command is the opening command of the VIGV / VGVs of the target gas turbine at the current or a future timestamp, which can be an angle command or an actuator stroke command and is not limited herein. The operating condition data of the gas turbine includes various types and is not limited herein. For example, it can include the gas turbine speed, ambient air temperature, ambient air pressure, fuel flow rate, emission concentration, turbine exhaust temperature, turbine inlet temperature, gas turbine power, VIGV / VGVs opening, compressor inlet pressure, compressor inlet temperature, compressor outlet pressure, compressor outlet temperature, combustion chamber pressure, turbine exhaust diffuser pressure, etc.

[0046] It should be noted that the online model is a model established based on the component characteristics and overall performance of the target gas turbine. The online model can be of various types and is not limited herein.

[0047] In a possible implementation manner, the online model can be a simulation model. For example, the online simulation model can be a physical simulation model, a mathematical simulation model, a hybrid simulation model, etc.

[0048] In another possible implementation manner, the online model can also be a neural network model.

[0049] It should be noted that the model output data is the output data such as the gas turbine state values and parameter values calculated by the gas turbine online model based on the input data such as the first fuel command, the first VIGV / VGVs command, and the actual operating condition data of the gas turbine. The model calculation measurement data is the data measured by the sensors simulated by the model calculation.

[0050] S103. Generate a fusion signal value based on the actual measurement signals of the sensors, the model output data, and the model calculation measurement data.

[0051] It should be noted that the sensors in the embodiments of the present disclosure can be of various types and are not limited herein. For example, the sensors of the target gas turbine can include temperature sensors, pressure sensors, fuel flow sensors, humidity sensors, mass flow sensors, angle measurement sensors, vibration sensors, speed sensors, acceleration sensors, power measurement devices, etc.

[0052] In the embodiments of the present disclosure, there can be various methods for generating the fused signal value based on the actual measurement signal of the sensor, the model output data, and the model-calculated measurement data, and no specific limitation is imposed here.

[0053] In one possible implementation, the actual measurement signal, the model output data, and the model-calculated measurement data can be input into a fused signal value generation model to generate the fused signal value. The fused signal value generation model is pre-trained and can be stored in the storage space of the electronic device for convenient retrieval and use when needed.

[0054] In another possible implementation, the fused signal value can also be calculated by a fused signal value algorithm for the actual measurement signal, the model output data, and the model-calculated measurement data. The fused signal value algorithm is pre-designed and can be adjusted according to the specific performance in the target gas turbine life cycle and the actual operating conditions of the gas turbine, and no specific limitation is imposed here.

[0055] S104. Input the fused signal value into the controller to replace the actual measurement value of the sensor, so as to generate a second fuel command and a second VIGV / VGVs command, and input the second fuel command and the second VIGV / VGVs command into the target gas turbine and the online model for control and adjustment.

[0056] In the embodiments of the present disclosure, the controller can be of various types, and no specific limitation is imposed here.

[0057] In one possible implementation, the controller can be a PID. The PID (Proportional-Integral-Derivative controller) is a widely used controller in the field of industrial control, which is used to adjust a specific process variable (such as temperature, pressure, flow rate, speed, etc.) to a set value. The PID controller achieves this goal by calculating the error (the difference between the actual measurement value and the target set value) and making adjustments based on this error.

[0058] In an embodiment of the present disclosure, first, a first fuel command and a first VIGV / VGVs command for an input target gas turbine are obtained, and then the first fuel command and the first VIGV / VGVs command are input into an online model of the target gas turbine to output model output data and model calculation measurement data. Then, a fusion signal value is generated based on the actual measurement signal of the sensor, the model output data, and the model calculation measurement data. Finally, the fusion signal value is input into the controller to replace the actual measurement value of the sensor, so as to generate a second fuel command and a second VIGV / VGVs command, and the second fuel command and the second VIGV / VGVs command are input into the target gas turbine and the online model for control adjustment. Thus, through the solution of the present disclosure, the rapid response of the gas turbine VIGV / VGVs, fuel quantity, etc. is improved, the dynamic performance of the gas turbine load control, temperature control, etc. is improved, the flexible operation of the gas turbine with rapid load change during the rapid peak shaving and frequency modulation of the power grid dispatching is realized, and a good peak shaving and frequency modulation control effect is achieved.

[0059] In an embodiment of the present disclosure, the set parameters of the controller can also be adjusted based on the model output data and the model calculation measurement data.

[0060] In a possible implementation manner, when the controller is a PID, the proportional gain, integral gain, and derivative gain of the controller are adjusted based on the model output data and the model calculation measurement data.

[0061] In the above embodiment, the fusion signal value is input into the controller to replace the actual measurement value of the sensor to generate a second fuel command and a second VIGV / VGVs command, and it can also be passed through Figure 2 For further explanation, Figure 2 is a schematic diagram of another model-based gas turbine control method according to an embodiment of the present disclosure Figure 2 , and this method includes:

[0062] S201, obtain the set value of the control quantity of the target gas turbine through the controller.

[0063] It should be noted that the control quantity is a parameter or set value for control or related to the operation of the target gas turbine. There can be multiple control quantities, which are not limited here, and can be specifically determined according to actual design requirements or the actual operating conditions of the gas turbine. S202, compare the fusion signal value with the set value of the control quantity through the controller, and generate a second fuel command and a second VIGV / VGVs command based on the comparison result.

[0064] In a possible implementation, the fused signal values of the turbine exhaust temperature, turbine inlet temperature, gas turbine power, VIGV / VGVs opening, gas turbine fuel quantity, compressor inlet pressure, compressor inlet temperature, compressor outlet pressure, compressor outlet temperature, pressure in the combustion and pressure cylinder, pressure in the turbine exhaust diffuser section, etc., of the target gas turbine, and the set values of the relevant control quantities may be obtained first. Then, a second VIGV / VGVs command and a second fuel command are generated based on the comparison results between the fused signal values such as the turbine exhaust temperature, turbine inlet temperature, gas turbine power, VIGV / VGVs opening, gas turbine fuel quantity, compressor inlet pressure, compressor inlet temperature, compressor outlet pressure, compressor outlet temperature, pressure in the combustion and pressure cylinder, pressure in the turbine exhaust diffuser section, etc., and the set values of the control quantities.

[0065] For example, the fused value obtained by correcting the turbine exhaust temperature (T4) and the turbine inlet temperature (T3) using an online model is compared with the set value. The larger value in the difference (which can be considered as the temperature farther from the set value) is used as the input of the PID controller in the VIGV / VGVs control loop related to temperature control for control operations, improving the fast responsiveness of the VIGV / VGVs for gas turbine temperature control. Since the feedback value is accelerated, the parameters of the PID controller in the VIGV / VGVs control loop are adjusted accordingly.

[0066] By adopting the method based on the gas turbine online model and correspondingly adjusting the parameters of the PID controller in the temperature control closed loop, the control closed loop of the turbine exhaust temperature T4 is accelerated, and the pressure in the combustion and pressure cylinder, the pressure in the turbine exhaust diffuser section, and the turbine inlet temperature signal T3 are also accelerated, improving the dynamic performance of the T4 and T3 temperature control closed loops.

[0067] In another possible implementation, a third VIGV / VGVs command may also be generated based on the fuel quantity - VIGV / VGVs feedforward and the second VIGV / VGVs command.

[0068] It should be noted that the fuel quantity - VIGV / VGVs feedforward is an advanced control strategy. It actively adjusts the opening of VIGV / VGVs in advance by predicting changes in fuel supply, helping the gas turbine better adapt to dynamically changing operating conditions, and improving the response speed and stability of the system. In the embodiments of the present disclosure, the fuel quantity - VIGV / VGVs feedforward can be generated based on load demand signals, environmental conditions, and sensor feedback. By processing the second VIGV / VGVs command and the fuel quantity - VIGV / VGVs feedforward to generate the third VIGV / VGVs command, it is possible to predictively and actively adjust the opening of VIGV / VGVs in advance according to fuel quantity changes, accelerate the system's response speed to changes, reduce delays, and at the same time, maintain the stability of the combustion process and avoid problems such as gas turbine flameout or overheating when facing sudden load changes or environmental condition changes.

[0069] In a possible implementation manner of the present disclosure, to obtain the fuel quantity - VIGV / VGVs feedforward, it is possible to first obtain the historical operation data and current operating condition data of the target gas turbine, then match based on the current operating condition data in the historical operation data to obtain the historical VIGV / VGVs opening value in the successfully matched historical operation data, and finally generate the fuel quantity - VIGV / VGVs feedforward based on the historical VIGV / VGVs opening value. Thus, by matching to obtain the VIGV / VGVs opening value in historical data, it is possible to draw on the operation data under normal operation in the past, and at the same time, reduce the calculation amount and the complexity of obtaining data, and lower the calculation cost.

[0070] For example, especially for the VIGV / VGVs control related to temperature control outside of feedback control, using temperature as feedback has a slow response. Adding the fuel quantity - VIGV / VGVs feedforward control enables VIGV / VGVs to act in advance, improves the rapid response of gas turbine control, avoids excessive fluctuations or even overheating of the exhaust gas temperature, and keeps the combined cycle heat recovery boiler near the optimal temperature operating point, ensuring the economy, safety, and stability of the unit operation. The feedforward set value for controlling the gas turbine fuel quantity and the VIGV / VGVs opening can be obtained from the VIGV / VGVs opening value at the steady - state operating condition point under the same conditions.

[0071] In the embodiments of the present disclosure, first, the set value of the control quantity of the target gas turbine is obtained, and then the fusion signal value and the set value of the control quantity are compared, and a second fuel command and a second VIGV / VGVs command are generated based on the comparison result. Thus, by applying the load control and VIGV / VGVs control based on the online model of the gas turbine, it can respond quickly, prevent the rapid increase in the turbine inlet temperature and even over-temperature caused by the rapid increase in the fuel quantity during rapid load change, especially during rapid load increase in frequency modulation control, and at the same time prevent excessive fluctuations and even over-temperature of the exhaust gas temperature, keep the waste heat boiler working near the optimal temperature operating point, ensure the economy, operation safety and stability of the unit, and at the same time can quickly respond to the rapid load change scheduling of the power grid and meet the assessment requirements such as the rapidity and accuracy of frequency modulation response.

[0072] In actual operation, under different operating condition scenarios, the control strategies and control objectives of the target gas turbine may be different. Therefore, when generating the second fuel command and the second VIGV / VGVs command, the current operating condition data of the target gas turbine is also referred to for generation.

[0073] In a possible implementation manner, the operating condition data of the target gas turbine can be first obtained by the controller, and then the second fuel command and the second VIGV / VGVs command are generated by the controller based on the operating condition data and the comparison result.

[0074] In the above embodiments, the fusion signal value is generated based on the actual measurement signal of the sensor, the model output data and the model calculation measurement data, and can also be obtained by Figure 3 For further explanation, Figure 3 is a schematic diagram of another model-based gas turbine control method according to an embodiment of the present disclosure Figure 3 which includes:

[0075] S301, subtracting the model output data from the model calculation measurement data to calculate and obtain the dynamic compensation value.

[0076] S302, adding the dynamic compensation value to the actual measurement signal to calculate and obtain the fusion signal value.

[0077] In the embodiments of the present disclosure, an online model of a gas turbine is designed and established. The difference between the model calculated values such as the gas turbine power and the turbine exhaust gas temperature obtained using the online model and the sensor measured values is compensated to the actual sensor measured values to obtain corresponding fusion values. That is, after correcting the measured values of the corresponding gas turbine power (PWR), turbine exhaust gas temperature (T4), etc., and the dynamic performance of the turbine inlet temperature (T3), they are compared with the set values, and the difference is used as the input of the PID controller in the load control loop for control operations, improving the rapid response of the fuel quantity for gas turbine load control. Since the feedback values such as the gas turbine power (PWR), turbine exhaust gas temperature (T4), and turbine inlet temperature (T3) are accelerated, the parameters of the PID controller in the load control loop are also adjusted accordingly. For example, the calculation principle can be as Figure 4 shown.

[0078] In the embodiments of the present disclosure, the formula for calculating the fusion signal value is:

[0079]

[0080] where y accel is the accelerated signal fusion value, y meas is the actual sensor measured signal, y model is the model calculated value, is the model calculated measured value.

[0081] Through the method of the present disclosure, the simulation comparison results after the inventors' tests are as Figure 5 shown. In Figure 5 : CFRQ-PWR is the power compensation command for the gas turbine frequency response, FUEL-CMD is the gas turbine fuel quantity command, VIGV / VGVs is the feedback of the gas turbine VIGV / VGVs opening, PWR-ST is the gas turbine load set value including peak shaving and frequency modulation responses, PWR-PV is the actual gas turbine power, T4 is the turbine exhaust gas temperature, and T3 is the turbine inlet temperature. Through Figure 5 it can be seen that in the response process of the model-based control method of the present disclosure compared with the control method in the current technology, in the response process of the 10% load step simulation test of the frequency response, the adjustment response times of the gas turbine fuel quantity, VIGV / VGVs opening, actual gas turbine power, turbine exhaust gas temperature (T4), and turbine inlet temperature (T3) are all significantly shortened, the overshoot is also significantly reduced, and the response process is more stable. It improves the dynamic performance of the gas turbine VIGV / VGVs control, etc. It realizes the rapid adjustment of the gas turbine VIGV / VGVs and the fuel quantity, achieves rapid load increase without overheating of T4 and T3, responds to the rapid peak shaving of the power grid dispatching and the rapid load change dispatching during the gas turbine frequency modulation control, and improves the rapidity and accuracy of the gas turbine in responding to the power grid peak shaving and primary frequency modulation and other assessment performances.

[0082] Meanwhile, when the gas turbine participates in peak shaving and frequency modulation control, especially when responding to grid dispatching for rapid peak shaving and variable load and rapid load increase during frequency modulation control of the gas turbine, the control based on the online model superimposed with the fuel quantity-VIGV / VGVs feedforward control can quickly adjust the opening of VIGV / VGVs, prevent excessive fluctuations or even overheating of the exhaust gas temperature, keep the heat recovery boiler near the optimal temperature operating point, and ensure the economy, safety, and stability of the unit operation.

[0083] Figure 6 The present disclosure proposes a model-based gas turbine control system, as Figure 6 shown. The model-based gas turbine control system includes: a target gas turbine 610, a controller 620, and an online model 630.

[0084] Among them, the controller 620 is used to generate a first fuel command and a first VIGV / VGVs command, and input them into the target gas turbine 610 and the online model 630.

[0085] The online model 630 is used to output model output data and model calculation measurement data based on the first fuel command and the first VIGV / VGVs command.

[0086] The controller 620 is further used to generate a fusion signal value based on the actual measurement signals of the sensors, the model output data, and the model calculation measurement data, and generate a second fuel command and a second VIGV / VGVs command, and then input the second fuel command and the second VIGV / VGVs command into the target gas turbine 610 and the online model 630 for control adjustment.

[0087] According to an embodiment of the present disclosure, the online model is further used to: obtain the first fuel command, the first VIGV / VGVs command, and the set values of relevant control quantities; compare the fusion signal value with the set values of the control quantities, and generate the second fuel command and the second VIGV / VGVs command based on the comparison result.

[0088] Corresponding to the model-based gas turbine control methods provided in the above several embodiments, an embodiment of the present disclosure also provides a model-based gas turbine control device. Since the model-based gas turbine control device provided in the embodiments of the present disclosure corresponds to the model-based gas turbine control methods provided in the above several embodiments, the implementation manners of the above model-based gas turbine control methods are also applicable to the model-based gas turbine control device provided in the embodiments of the present disclosure, and will not be described in detail in the following embodiments.

[0089] Figure 7 is a schematic diagram of a model-based gas turbine control device according to an embodiment of the present disclosure, as Figure 7As shown, the model-based gas turbine control device 700 includes: an acquisition module 710, an input module 720, a generation module 730, and a control module 740.

[0090] The acquisition module 710 is configured to acquire a first fuel command and a first VIGV / VGVs command input to a target gas turbine.

[0091] The input module 720 is configured to input the first fuel command and the first VIGV / VGVs command into an online model of the target gas turbine to output model output data and model calculation measurement data.

[0092] The generation module 730 is configured to generate a fusion signal value based on an actual measurement signal of a sensor, the model output data, and the model calculation measurement data.

[0093] The control module 740 is configured to input the fusion signal value into a controller to replace an actual measurement value of the sensor, so as to generate a second fuel command and a second VIGV / VGVs command, and input the second fuel command and the second VIGV / VGVs command into the target gas turbine and the online model for control adjustment.

[0094] According to an embodiment of the present disclosure, inputting the fusion signal value into the controller to replace the actual measurement value of the sensor to generate a second fuel command and a second VIGV / VGVs command includes: obtaining a set value of a control quantity of the target gas turbine through the controller; comparing the fusion signal value and the set value of the control quantity through the controller, and generating a second fuel command and a second VIGV / VGVs command based on the comparison result.

[0095] According to an embodiment of the present disclosure, comparing the fusion signal value and the set value of the control quantity, and generating a second fuel command and a second VIGV / VGVs command based on the comparison result includes: obtaining a fusion signal value and a set value of a control quantity such as a turbine exhaust temperature, a turbine inlet temperature, a gas turbine power, a VIGV / VGVs opening, a gas turbine fuel quantity, a compressor inlet pressure, a compressor inlet temperature, a compressor outlet pressure, a compressor outlet temperature, a combustion chamber pressure, and a turbine exhaust diffuser pressure of the target gas turbine; generating a second fuel command and a second VIGV / VGVs command based on a comparison result of the fusion signal value and the set value of the control quantity.

[0096] According to an embodiment of the present disclosure, the method further includes: generating a third VIGV / VGVs command based on fuel-VIGV / VGVs feedforward and the second VIGV / VGVs command.

[0097] According to an embodiment of the present disclosure, obtaining the fuel quantity - VIGV / VGVs feedforward includes: obtaining the historical operation data and current operating condition data of the target gas turbine; matching based on the current operating condition data in the historical operation data to obtain the historical VIGV / VGVs opening value in the successfully matched historical operation data; generating the fuel quantity - VIGV / VGVs feedforward based on the historical VIGV / VGVs opening value.

[0098] According to an embodiment of the present disclosure, the method further includes: obtaining the operating condition data of the target gas turbine through a controller; generating a second fuel command and a second VIGV / VGVs command through the controller based on the operating condition data and the comparison result.

[0099] According to an embodiment of the present disclosure, generating a fusion signal value based on the actual measurement signal of the sensor, the model output data, and the model - calculated measurement data includes: subtracting the model output data from the model - calculated measurement data to calculate and obtain a dynamic compensation value; adding the dynamic compensation value to the actual measurement signal to calculate and obtain the fusion signal value.

[0100] According to an embodiment of the present disclosure, the formula for calculating the fusion signal value is: where y accel is the acceleration signal fusion value, y meas is the actual measurement signal of the sensor, y model is the model - calculated value, is the model - calculated measurement value.

[0101] According to an embodiment of the present disclosure, the method further includes: adjusting the set parameters of the controller based on the model output data and the model - calculated measurement data.

[0102] Thus, through the solution of the present disclosure, the rapid response of the gas turbine's VIGV / VGVs and fuel quantity, etc. is improved, the dynamic performance of the gas turbine's load control and temperature control, etc. is improved, the flexible operation of the gas turbine with rapid load change during the rapid peak - shaving and frequency - modulation of the power grid dispatching is realized, and good peak - shaving and frequency - modulation control effects are achieved.

[0103] To implement the above - mentioned embodiments, the present disclosure embodiments also propose an electronic device 800, Figure 8 which is a schematic diagram of an electronic device according to an embodiment of the present disclosure, as Figure 8 shown. The electronic device 800 includes: a processor 801 and a memory 802 communicatively connected to the processor. The memory 802 stores instructions executable by at least one processor. The instructions are executed by at least one processor 801 to implement the model - based gas turbine control method as in the embodiments of the present disclosure Figures 1 - 5 embodiments.

[0104] To implement the above embodiments, embodiments of the present disclosure also propose a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to implement the model-based gas turbine control method as described in the embodiments of the present disclosure. Figures 1 - 5

[0105] To implement the above embodiments, embodiments of the present disclosure also propose a computer program product, including a computer program, which when executed by a processor, implements the model-based gas turbine control method as described in the embodiments of the present disclosure. Figures 1 - 5

[0106] It should be noted that personal information from users should be collected for legal and reasonable purposes and should not be shared or sold outside of such legal uses. In addition, such collection / sharing should be carried out after obtaining the informed consent of the user, including but not limited to notifying the user to read the user agreement / user notice before the user uses the function and signing an agreement / authorization including authorizing relevant user information. In addition, any necessary steps should be taken to safeguard and protect access to such personal information data and ensure that others with access to the personal information data comply with their privacy policies and procedures.

[0107] This application anticipates providing embodiments that allow users to selectively block the use or access of personal information data. That is, the present disclosure anticipates providing hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, the risk can be minimized by restricting data collection and deleting the data. In addition, when applicable, personal identifiers are removed from such personal information to protect the privacy of the user.

[0108] In the description of the foregoing embodiments, the descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without conflict, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0109] ​​In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the technical features indicated. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0110] Any process or method description represented in a flowchart or described otherwise herein may be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of the present application includes additional implementations, where functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0111] The logic and / or steps represented in a flowchart or described otherwise herein, for example, may be considered as a sequenced list of executable instructions for implementing a logical function, and may be specifically implemented in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" may be any device that contains, stores, communicates, propagates, or transports a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion having one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium may even be paper or other suitable medium on which the program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpretation, or other appropriate processing as necessary, and then storing it in a computer memory.

[0112] It should be understood that each part of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application specific integrated circuits with suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0113] Those of ordinary skill in the art can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0114] In addition, in each embodiment of the present application, each functional unit can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0115] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A gas turbine control method based on a model, characterized in that: include: Obtaining a first fuel instruction and a first VIGV / VGVs instruction input to a target gas turbine; inputting the first fuel command and the first VIGV / VGVs command into an online model of the target gas turbine to output model output data and model calculation measurement data; generating a fused signal value based on an actual measurement signal of a sensor, the model output data, and the model calculated measurement data; The fused signal value is input into the controller to replace the actual measurement value of the sensor to generate a second fuel instruction and a second VIGV / VGVs instruction, and the second fuel instruction and the second VIGV / VGVs instruction are input into the target gas turbine and the online model for control and adjustment.

2. The method according to claim 1, characterized in that The step of inputting the fused signal value into the controller to replace the actual measured value of the sensor to generate a second fuel instruction and a second VIGV / VGVs instruction includes: Acquiring a set value of a control amount of a target gas turbine through the controller; The controller compares the fusion signal value with the set value of the control amount, and generates the second fuel instruction and the second VIGV / VGVs instruction based on the comparison result.

3. The method according to claim 2, characterized in that The comparing the fusion signal value with the set value of the control amount, and generating the second fuel instruction and the second VIGV / VGVs instruction based on the comparison result, comprises: Obtaining fused signal values ​​of turbine exhaust temperature, turbine inlet temperature, gas turbine power, and VIGV / VGVs opening of the target gas turbine; The second fuel command and the second VIGV / VGVs command are generated based on a comparison result between the fusion signal value and the set value of the control amount.

4. The method according to claim 3, characterized in that The method further comprises: A third VIGV / VGVs command is generated based on the fuel amount-VIGV / VGVs feedforward and the second VIGV / VGVs command.

5. The method according to claim 4, characterized in that Obtaining the fuel quantity-VIGV / VGVs feedforward includes: Acquiring historical operating data and current operating condition data of the target gas turbine; Matching the historical operating data based on the current operating condition data, and obtaining the historical VIGV / VGVs opening value in the historical operating data that successfully matches; The fuel amount-VIGV / VGVs feedforward is generated based on the historical VIGV / VGVs opening values.

6. The method according to claim 2, characterized in that The method further comprises: Acquiring operating condition data of the target gas turbine through the controller; The second fuel command and the second VIGV / VGVs command are generated by the controller based on the operating condition data and the comparison result.

7. The method according to claim 1, characterized in that The generating of the fused signal value based on the actual measurement signal of the sensor, the model output data and the model calculated measurement data comprises: Subtracting the model output data from the model calculation measurement data to calculate and obtain a dynamic compensation value; The dynamic compensation value is added to the actual measurement signal to calculate and obtain the fused signal value.

8. The method according to claim 7, characterized in that The formula for calculating the fusion signal value is: Among them, y accel is the acceleration signal fusion value, y meas is the actual measurement signal of the sensor, y model Calculate values ​​for the model, Calculate measurements for the model.

9. The method according to claim 1, characterized in that: The method further comprises: The setting parameters of the controller are adjusted based on the model output data and the model calculation measurement data.

10. The method according to claim 9, characterized in that The adjusting the setting parameters of the controller based on the model output data and the model calculation measurement data includes: Proportional gains, integral gains, and derivative gains of the controller are adjusted based on the model output data and the model calculated measurement data.

11. A gas turbine control system based on a model, characterized in that: include: Target gas turbine, controller and online model; wherein the controller is used to generate a first fuel instruction and a first VIGV / VGVs instruction, and input them into the target gas turbine and the online model; The online model is used to output model output data and model calculation measurement data based on the first fuel instruction and the first VIGV / VGVs instruction; The controller is also used to generate a fusion signal value based on the actual measurement signal of the sensor, the model output data and the model calculated measurement data, and generate a second fuel instruction and a second VIGV / VGVs instruction, and then input the second fuel instruction and the second VIGV / VGVs instruction into the target gas turbine and the online model for control and adjustment.

12. The system according to claim 11, characterized in that The online model is also used to: obtaining a set value of a control variable of a target gas turbine; The fusion signal value is compared with the set value of the control amount, and the second fuel instruction and the second VIGV / VGVs instruction are generated based on the comparison result.

13. A gas turbine control device based on a model, characterized in that: include: An acquisition module, used for acquiring a first fuel instruction and a first VIGV / VGVs instruction input to a target gas turbine; an input module, configured to input the first fuel instruction and the first VIGV / VGVs instruction into an online model of the target gas turbine to output model output data and model calculation measurement data; A generating module, used for generating a fusion signal value based on an actual measurement signal of a sensor, the model output data and the model calculated measurement data; A control module is used to input the fusion signal value into the controller instead of the actual measurement value of the sensor to generate a second fuel instruction and a second VIGV / VGVs instruction, and input the second fuel instruction and the second VIGV / VGVs instruction into the target gas turbine and the online model for control and adjustment.

14. An electronic device, characterized in that: Including memory and processor; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the method according to any one of claims 1 to 10.

15. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 10 when executed by a processor.

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