Intelligent monitoring method applied to improvement of primary frequency modulation performance of gas turbine

Abstract

The invention discloses an intelligent monitoring method applied to improvement of primary frequency modulation performance of a gas turbine. The intelligent monitoring method comprises the following steps: S1, acquiring power grid frequency data by communicating with a power grid system; wherein the power grid frequency data comprises the power grid frequency of the power grid at any moment; s2, monitoring, analyzing and processing the collected power grid frequency data to obtain a frequency deviation value; comparing the frequency deviation value with a threshold value of the frequency deviation value to generate an abnormal monitoring signaling; and S3, when the abnormal monitoring signaling is generated. According to the method, the power grid frequency data is divided into a plurality of power grid monitoring time zones according to the time sequence, so that the change conditions of the power grid frequency in different time periods can be observed more meticulously, the short-term fluctuation trend and the potential law of the power grid frequency can be found, and compared with only paying attention to the overall frequency data, the power grid frequency data is more accurate. And the starting and development processes of the abnormal fluctuation can be captured more timely.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid frequency monitoring, and in particular to an intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine. Background Art

[0002] Primary frequency regulation refers to the automatic control process in which the control system of the units in the power grid automatically controls the increase or decrease of the active power of the units, limits the change of the power grid frequency, and maintains a stable power grid frequency once the power grid frequency deviates from the rated value.

[0003] The frequency of the power grid is determined by the power generation and the power load. In a stable power system, the power grid frequency is stable at the rated frequency. When the power load of the system increases, the system will have a power shortage and the power grid frequency will decrease; conversely, the power grid frequency will increase. Therefore, the primary frequency regulation function is one of the means to dynamically ensure the active power balance of the power grid.

[0004] Gas turbines can start and stop quickly, change load quickly, and respond quickly to grid commands and changes in grid frequency. They are more suitable for grid peak regulation and frequency regulation than conventional units.

[0005] The output power of the steam turbine in the combined cycle unit varies with the operating conditions of the gas turbine. The regulation of the unit power simply becomes the regulation of the fuel quantity of the gas turbine, and the steam turbine itself no longer participates in the primary and secondary frequency regulation of the power grid.

[0006] Therefore, all primary frequency regulation tests are only conducted on gas turbines.

[0007] The grid frequency signal is connected to the gas turbine TCS system. When the logic determines a frequency modulation action, the TCS system automatically controls the opening of the gas turbine IGV, natural gas duty valve, premixing valve and other combustion-related actuators, thereby quickly increasing or decreasing the load and adjusting the frequency.

[0008] However, there are the following problems: the monitoring system monitors the frequency of the power grid and issues instructions to control the gas turbine to perform corresponding actions. However, the monitoring system can only monitor internal factors and ignores environmental factors, which leads to the gas turbine being unable to respond to instructions in time and quickly perform corresponding actions, or the gas turbine receiving the instructions and responding fails to meet the requirements of the monitoring system.

[0009] Therefore, an intelligent monitoring method for improving the primary frequency regulation performance of gas turbines is needed to address the above problems. Summary of the invention

[0010] The purpose of the present invention is to solve the above-mentioned problem and to propose an intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine.

[0011] In order to achieve the above object, the present invention adopts the following technical solutions:

[0012] The intelligent monitoring method applied to improving the primary frequency regulation performance of a gas turbine comprises the following steps:

[0013] S1: Acquire grid frequency data by communicating with the grid system; wherein the grid frequency data includes the grid frequency of the grid at any moment;

[0014] S2: Monitor, analyze and process the collected power grid frequency data to obtain a frequency deviation value; compare the frequency deviation value with its threshold value to generate an abnormal monitoring signal;

[0015] S3: When the abnormal monitoring signal is generated, the analysis of the relevant information of the state of the gas engine is triggered to obtain the comprehensive regulation coefficient of the gas engine;

[0016] S4: When generating the abnormal monitoring time zone, the frequency deviation value of the power grid monitoring time zone in the abnormal monitoring time zone is analyzed to obtain the power grid fluctuation frequency change value K.

[0017] Preferably, based on S2, the collected power grid frequency data is monitored, analyzed and processed, and the specific steps of the monitoring, analysis and processing process are:

[0018] S21: Obtain power grid frequency data, and divide the power grid frequency data into a number of power grid monitoring time zones in chronological order;

[0019] S22: Identify the grid frequency in any grid monitoring time zone, set a standard threshold value for the grid frequency, and subtract the standard threshold value from the grid frequency in any grid monitoring time zone to obtain a frequency deviation value GJ;

[0020] S23: Set the normal range of grid frequency fluctuations, mark the grid monitoring time zone corresponding to the frequency deviation value within the normal range of grid frequency fluctuations as the normal frequency time zone; mark the grid monitoring time zone corresponding to the frequency deviation value not within the normal range of grid frequency fluctuations as the abnormal frequency time zone, and generate abnormal monitoring signaling.

[0021] Preferably, the specific process of obtaining the comprehensive regulation coefficient of the gas engine is as follows:

[0022] S31: taking the current moment as the initial moment, and marking the time area within a set time length before the initial moment as the abnormality monitoring time zone;

[0023] S32: Acquiring state-related information at any collection time within the abnormal monitoring time zone, including the speed data of the gas engine, the fuel supply of the gas engine, the air intake volume of the gas engine air intake port, and the air intake temperature of the gas engine air intake port;

[0024] S33: setting a standard value of any parameter in the state related information, and subtracting the standard value corresponding to any parameter in the state related information from the parameter to obtain a gas engine parameter deviation Y1;

[0025] S34: Calculate the mean and standard deviation of the engine parameter deviation of any parameter in the abnormal monitoring time zone to obtain the engine parameter deviation mean value Y2 and the engine parameter deviation fluctuation value Y3; perform weighted processing on the engine parameter deviation, the engine parameter deviation mean value, and the engine parameter deviation fluctuation value to obtain the engine adjustment coefficient Y corresponding to the parameter; perform weighted calculation on the engine parameter deviation, the engine parameter deviation mean value, and the engine parameter deviation fluctuation value, using the formula:

[0026] Y = Y1 × L1 + Y2 × L2 + Y3 × L3;

[0027] The gas turbine adjustment coefficient Y is obtained, where L1, L2, and L3 represent the weights corresponding to the gas turbine parameter deviation, the gas turbine parameter deviation average, and the gas turbine parameter deviation fluctuation, respectively;

[0028] S35: Weighted calculation of the engine adjustment coefficients of all parameters in the state related information to obtain the comprehensive impact adjustment coefficient E; the formula is:

[0029]

[0030] Among them, U1, U2, U3, and U4 respectively represent the speed data of the engine, the fuel supply of the engine, the air intake amount of the engine air inlet, and the air intake temperature of the engine air inlet; V1, V2, V3, and V4 respectively represent the weights corresponding to the speed data of the engine, the fuel supply of the engine, the air intake amount of the engine air inlet, and the air intake temperature of the engine air inlet;

[0031] S36: Perform weighted processing on the comprehensive influence adjustment coefficient and the engine adjustment coefficient corresponding to the parameter to obtain the engine comprehensive adjustment coefficient Q corresponding to the parameter, using the formula:

[0032] Q = E × C1 + Y × C2;

[0033] Where C1 and C2 represent the weight factors corresponding to the comprehensive impact adjustment coefficient and the gas turbine adjustment coefficient respectively.

[0034] Preferably, the specific analysis process of the power grid fluctuation frequency change value K is as follows:

[0035] S41: Obtain the frequency deviation value of any power grid monitoring time zone in the abnormal monitoring time zone, and perform weighted processing on it, using the formula:

[0036]

[0037] The grid fluctuation frequency change value K is obtained; wherein i is the grid fluctuation frequency at the current moment, z is the grid fluctuation frequency of all the monitoring time zones, i GJ is the frequency deviation value at the current moment, and iw is the corresponding weight factor.

[0038] Preferably, after S4, the method further includes S5:

[0039] Receive the grid fluctuation frequency change value K and compare it with the set grid fluctuation frequency change threshold. The specific process is as follows:

[0040] If the grid fluctuation frequency change value is greater than the grid fluctuation frequency change threshold, it indicates that the grid frequency is in an abnormal state; if the grid fluctuation frequency change value is less than the grid fluctuation frequency change threshold, it indicates that the grid frequency is in a normal state.

[0041] Preferably, the power grid fluctuation frequency change value is matched with the value range of the warning light group, and the warning light group includes normal and abnormal warning lights, specifically:

[0042] If the grid frequency fluctuation change value is in an abnormal state, the fault warning light indicating abnormal grid frequency change in the control warning light group will light up; if the grid frequency is in a normal state, the warning light indicating normal grid frequency in the control warning light group will light up.

[0043] Preferably, the warning light group is also matched with an audible alarm speaker. When the normal warning light is on, the audible alarm speaker does not respond; when the fault warning light indicating abnormal grid frequency is on, the alarm speaker indicating abnormal grid frequency sounds an alarm sound.

[0044] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0045] 1. The present invention divides the power grid frequency data into several power grid monitoring time zones in chronological order, which can more carefully observe the changes in power grid frequency in different time periods, help to discover the short-term fluctuation trend and potential laws of power grid frequency, and can capture the initiation and development process of abnormal fluctuations more timely than only focusing on the overall frequency data.

[0046] 2. The present invention calculates the deviation of the gas turbine parameters, the average deviation of the gas turbine parameters and the fluctuation of the gas turbine parameter deviation, and obtains the gas turbine adjustment coefficient and the comprehensive influence adjustment coefficient through weighted processing, and finally obtains the comprehensive adjustment coefficient of the gas turbine corresponding to the parameters. This multi-step calculation method fully considers the changes in the gas turbine parameters in the abnormal monitoring time zone, and not only considers the degree of deviation of the parameters, but also considers the average value and fluctuation of the deviation, so that the calculated adjustment coefficient is more scientific and accurate. These adjustment coefficients can provide precise guidance for the subsequent regulation of the gas turbine operating parameters, ensure that the gas turbine can make appropriate adjustments according to the changes in the grid frequency, and improve the primary frequency regulation performance of the gas turbine and the response speed to the changes in the grid frequency. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0048] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0049] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete, and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0050] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and / or this specification, and will not be interpreted in an idealized or overly formal sense, unless explicitly defined as such herein.

[0051] See also Figure 1 As shown, the present invention provides a technical solution:

[0052] An intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine comprises the following steps:

[0053] S1: Acquire grid frequency data by communicating with the grid system; wherein the grid frequency data includes the grid frequency of the grid at any moment;

[0054] S2: Monitor, analyze and process the collected power grid frequency data. The specific steps of the monitoring, analysis and processing process are as follows:

[0055] S21: Obtain power grid frequency data, and divide the power grid frequency data into a number of power grid monitoring time zones in chronological order;

[0056] S22: Identify the grid frequency in any grid monitoring time zone, set a standard threshold value for the grid frequency, and subtract the standard threshold value from the grid frequency in any grid monitoring time zone to obtain a frequency deviation value GJ;

[0057] S23: Setting a normal range of grid frequency fluctuation, marking a grid monitoring time zone corresponding to a frequency deviation value within the normal range of grid frequency fluctuation as a normal frequency time zone; marking a grid monitoring time zone corresponding to a frequency deviation value not within the normal range of grid frequency fluctuation as an abnormal frequency time zone, and generating an abnormal monitoring signaling;

[0058] S3: When the abnormal monitoring signal is generated, the status information of the gas turbine is analyzed to obtain the comprehensive adjustment coefficient of the gas turbine:

[0059] S31: taking the current moment as the initial moment, and marking the time area within a set time length before the initial moment as the abnormality monitoring time zone;

[0060] S32: Acquiring state-related information at any collection time within the abnormal monitoring time zone, including the speed data of the gas engine, the fuel supply of the gas engine, the air intake volume of the gas engine air intake port, and the air intake temperature of the gas engine air intake port;

[0061] S33: setting a standard value of any parameter in the state related information, and subtracting the standard value corresponding to any parameter in the state related information from the parameter to obtain a gas engine parameter deviation Y1;

[0062] S34: Calculate the mean and standard deviation of the engine parameter deviation of any parameter in the abnormal monitoring time zone to obtain the engine parameter deviation mean value Y2 and the engine parameter deviation fluctuation value Y3; perform weighted processing on the engine parameter deviation, the engine parameter deviation mean value, and the engine parameter deviation fluctuation value to obtain the engine adjustment coefficient Y corresponding to the parameter; perform weighted calculation on the engine parameter deviation, the engine parameter deviation mean value, and the engine parameter deviation fluctuation value, using the formula:

[0063] Y = Y1 × L1 + Y2 × L2 + Y3 × L3;

[0064] The gas turbine adjustment coefficient Y is obtained, where L1, L2, and L3 represent the weights corresponding to the gas turbine parameter deviation, the gas turbine parameter deviation average, and the gas turbine parameter deviation fluctuation, respectively;

[0065] S35: Weighted calculation of the engine adjustment coefficients of all parameters in the state related information to obtain the comprehensive impact adjustment coefficient E; the formula is:

[0066]

[0067] Among them, U1, U2, U3, and U4 respectively represent the speed data of the engine, the fuel supply of the engine, the air intake amount of the engine air inlet, and the air intake temperature of the engine air inlet; V1, V2, V3, and V4 respectively represent the weights corresponding to the speed data of the engine, the fuel supply of the engine, the air intake amount of the engine air inlet, and the air intake temperature of the engine air inlet;

[0068] S36: Perform weighted processing on the comprehensive influence adjustment coefficient and the engine adjustment coefficient corresponding to the parameter to obtain the engine comprehensive adjustment coefficient Q corresponding to the parameter, and substitute it into the formula:

[0069] Q = E × C1 + Y × C2;

[0070] Where C1 and C2 represent the weight factors corresponding to the comprehensive impact adjustment coefficient and the gas turbine adjustment coefficient respectively;

[0071] S4: When generating the abnormal monitoring time zone, the frequency deviation value of the power grid monitoring time zone in the abnormal monitoring time zone is analyzed, specifically:

[0072] S41: Obtain the frequency deviation value of any power grid monitoring time zone in the abnormal monitoring time zone, and perform weighted processing on it, using the formula:

[0073]

[0074] Get the power grid fluctuation frequency change value K; where i is the power grid fluctuation frequency at the current moment, z is the power grid fluctuation frequency of all monitoring time zones, i GJ is the frequency deviation value at the current moment, and iw is the corresponding weight factor;

[0075] S42: Receive the power grid fluctuation frequency change value K and compare it with the set power grid fluctuation frequency change threshold value, specifically:

[0076] The grid frequency fluctuation change value represents the comprehensive degree of grid frequency fluctuation in the abnormal monitoring time zone. It reflects the change of grid frequency relative to the standard frequency and the trend and amplitude of this change. If the value is large, it means that the grid frequency fluctuates significantly during this period, and there may be factors that affect the stable operation of the power system. On the contrary, if the value is small, it means that the fluctuation of grid frequency is relatively small and is in a relatively stable state.

[0077] The received power grid fluctuation frequency change value K is compared with the set power grid fluctuation frequency change threshold value. The specific process is as follows:

[0078] If the grid fluctuation frequency change value is greater than the grid fluctuation frequency change threshold, it indicates that the grid frequency is in an abnormal state; if the grid fluctuation frequency change value is less than the grid fluctuation frequency change threshold, it indicates that the grid frequency is in a normal state;

[0079] The power grid fluctuation frequency change value is matched with the value range of the warning light group. The warning light group includes normal and abnormal warning lights, specifically:

[0080] If the grid frequency fluctuation value is in an abnormal state, the fault warning light indicating abnormal grid frequency in the control warning light group will light up; if the grid frequency is in a normal state, the warning light indicating normal grid frequency in the control warning light group will light up;

[0081] The warning light group is also matched with the sound alarm speaker. When the normal warning light is on, the sound alarm speaker does not respond; when the fault warning light of abnormal grid frequency is on, the alarm speaker indicating abnormal grid frequency sounds an alarm sound;

[0082] If the grid fluctuation frequency change value is greater than the grid fluctuation frequency change threshold, it means that the grid frequency is in an abnormal state, and a gas turbine adjustment signal is generated; the signal is a command trigger, which is used to trigger the gas turbine comprehensive adjustment coefficient corresponding to the gas turbine state related information parameters to control the gas turbine operation parameters, and then the fuel increase of the gas turbine is calculated according to the relevant parameters, and the corresponding amount of fuel is provided to the gas turbine under the action of the gas turbine feeding system, that is, the gas turbine is provided with an additional standard amount of fuel, so that the gas turbine can change its speed more quickly;

[0083] Electric or pneumatic automatic control valves are used to accurately adjust the valve opening by receiving signals from the control system, thereby changing the air intake of the gas turbine; the automatic control valve can adjust the air intake in real time according to the change of the grid frequency to achieve precise control; however, when the grid fluctuation frequency change value is greater than the grid fluctuation frequency change threshold, in addition to adjusting according to the grid frequency change, the automatic control valve also needs to increase the valve opening according to the grid fluctuation frequency change value to increase the air intake of the gas turbine;

[0084] The air near the gas turbine air inlet first passes through a filter to remove large molecular particles in the air, and then reaches the heat exchanger to exchange heat with the cooling medium in the heat exchanger. The air temperature changes according to the frequency of power grid fluctuations until it drops to the corresponding parameter. It is then transported to the gas turbine air inlet through the pipeline system. The intake temperature affects the density of the air. A lower intake temperature means a higher air density. With the same intake volume, the air mass increases. According to the combustion principle, more air mass can be mixed with more fuel to generate more energy, which is beneficial to increasing the speed of the gas turbine. On the contrary, a higher intake temperature will reduce the air density, reduce the intake mass, and may cause a decrease in speed.

[0085] If the grid fluctuation frequency change value is less than the grid fluctuation frequency change threshold, it means that the grid frequency is in a normal state; the speed change of the gas turbine can be changed accordingly under the control of the control system according to the monitored grid frequency to achieve the effect of stabilizing the grid frequency.

[0086] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The influencing weight factor and specific coefficient value in the formula are set by technical personnel in this field according to actual conditions, and can be adjusted and modified later.

[0087] The above description of the embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine, characterized in that: The following steps are involved: S1: Acquire grid frequency data by communicating with the grid system; wherein the grid frequency data includes the grid frequency of the grid at any moment; S2: Monitor, analyze and process the collected power grid frequency data to obtain a frequency deviation value; compare the frequency deviation value with its threshold value to generate an abnormal monitoring signal; S3: When the abnormal monitoring signal is generated, the analysis of the relevant information of the state of the gas engine is triggered to obtain the comprehensive regulation coefficient of the gas engine; S4: When generating the abnormal monitoring time zone, the frequency deviation value of the power grid monitoring time zone in the abnormal monitoring time zone is analyzed to obtain the power grid fluctuation frequency change value K.

2. The intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine according to claim 1 is characterized in that: Based on S2, the collected power grid frequency data is monitored, analyzed and processed. The specific steps of the monitoring, analysis and processing process are as follows: S21: Obtain power grid frequency data, and divide the power grid frequency data into a number of power grid monitoring time zones in chronological order; S22: Identify the grid frequency in any grid monitoring time zone, set a standard threshold value for the grid frequency, and subtract the standard threshold value from the grid frequency in any grid monitoring time zone to obtain a frequency deviation value GJ; S23: Set the normal range of grid frequency fluctuations, mark the grid monitoring time zone corresponding to the frequency deviation value within the normal range of grid frequency fluctuations as the normal frequency time zone; mark the grid monitoring time zone corresponding to the frequency deviation value not within the normal range of grid frequency fluctuations as the abnormal frequency time zone, and generate abnormal monitoring signaling.

3. The intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine according to claim 1 is characterized in that: The specific process of obtaining the comprehensive regulation coefficient of the gas turbine is as follows: S31: taking the current moment as the initial moment, and marking the time area within a set time length before the initial moment as the abnormality monitoring time zone; S32: Acquiring state-related information at any collection time within the abnormal monitoring time zone, including the speed data of the gas engine, the fuel supply of the gas engine, the air intake volume of the gas engine air intake port, and the air intake temperature of the gas engine air intake port; S33: setting a standard value of any parameter in the state related information, and subtracting the standard value corresponding to any parameter in the state related information from the parameter to obtain a gas engine parameter deviation Y1; S34: Calculate the mean and standard deviation of the engine parameter deviation of any parameter in the abnormal monitoring time zone to obtain the engine parameter deviation mean value Y2 and the engine parameter deviation fluctuation value Y3; perform weighted processing on the engine parameter deviation, the engine parameter deviation mean value, and the engine parameter deviation fluctuation value to obtain the engine adjustment coefficient Y corresponding to the parameter; perform weighted calculation on the engine parameter deviation, the engine parameter deviation mean value, and the engine parameter deviation fluctuation value, using the formula: Y = Y1 × L1 + Y2 × L2 + Y3 × L3; The gas turbine adjustment coefficient Y is obtained, where L1, L2, and L3 represent the weights corresponding to the gas turbine parameter deviation, the gas turbine parameter deviation average, and the gas turbine parameter deviation fluctuation, respectively; S35: Weighted calculation of the engine adjustment coefficients of all parameters in the state related information to obtain the comprehensive impact adjustment coefficient E; the formula is: Among them, U1, U2, U3, and U4 respectively represent the speed data of the engine, the fuel supply of the engine, the air intake amount of the engine air inlet, and the air intake temperature of the engine air inlet; V1, V2, V3, and V4 respectively represent the weights corresponding to the speed data of the engine, the fuel supply of the engine, the air intake amount of the engine air inlet, and the air intake temperature of the engine air inlet; S36: Perform weighted processing on the comprehensive influence adjustment coefficient and the engine adjustment coefficient corresponding to the parameter to obtain the engine comprehensive adjustment coefficient Q corresponding to the parameter, using the formula: Q = E × C1 + Y × C2; Where C1 and C2 represent the weight factors corresponding to the comprehensive impact adjustment coefficient and the gas turbine adjustment coefficient respectively.

4. The intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine according to claim 1 is characterized in that: The specific analysis process of the power grid fluctuation frequency change value K is as follows: S41: Obtain the frequency deviation value of any power grid monitoring time zone in the abnormal monitoring time zone, and perform weighted processing on it, using the formula: The grid fluctuation frequency change value K is obtained; wherein i is the grid fluctuation frequency at the current moment, z is all grid fluctuation frequencies in the monitoring time zone, iGJ is the frequency deviation value at the current moment, and iw is the corresponding weight factor.

5. The intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine according to claim 4 is characterized in that , based on S4, it also includes S5: Receive the grid fluctuation frequency change value K and compare it with the set grid fluctuation frequency change threshold. The specific process is as follows: If the grid fluctuation frequency change value is greater than the grid fluctuation frequency change threshold, it indicates that the grid frequency is in an abnormal state; if the grid fluctuation frequency change value is less than the grid fluctuation frequency change threshold, it indicates that the grid frequency is in a normal state.

6. The intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine according to claim 5 is characterized in that: The power grid fluctuation frequency change value is matched with the value range of the warning light group, and the warning light group includes normal and abnormal warning lights, specifically: If the grid frequency fluctuation change value is in an abnormal state, the fault warning light indicating abnormal grid frequency in the control warning light group will light up; if the grid frequency is in a normal state, the warning light indicating normal grid frequency in the control warning light group will light up.

7. The intelligent monitoring method for improving the primary frequency regulation performance of a gas turbine according to claim 6 is characterized in that: The warning light group is also matched with the sound alarm speaker. When the normal warning light is on, the sound alarm speaker does not respond; when the fault warning light indicating abnormal grid frequency is on, the alarm speaker indicating abnormal grid frequency sounds an alarm sound.

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