A control method and system for emergency generator set

Abstract

The present application relates to the technical field of generator set control, and specifically to a method and system for controlling an emergency generator set, the method comprising: collecting load power data and speed data of the emergency generator set; calculating the power fluctuation coefficient and load drastic change significance of each time period; and then obtaining the generator set turbulence coefficient of each time period; calculating the speed peak steepness coefficient and the speed peak order coefficient of each time period; obtaining the interference significance coefficient of each time period; and then obtaining the speed disorder fluctuation value of the emergency generator set; and controlling the emergency generator set based on the speed disorder fluctuation value combined with the PID control algorithm. The present application solves the defect of poor anti-interference ability of the generator set during the control process.

Description

Technical Field

[0001] The present application relates to the technical field of generator set control, and in particular to an emergency generator set control method and system. Background Art

[0002] An emergency generator set is a backup power system that automatically starts when the main power fails to provide emergency power supply. It is usually equipped with a control system that can respond quickly in a short period of time to ensure the continued operation of key power equipment. As an important power source, diesel generator sets are often used as emergency backup power sources for banks, hospitals, and data centers.

[0003] The control quality of the generator set speed affects the stability of the generator set's output voltage. In addition to being controlled by the generator's own voltage regulator, the generator's speed control also plays a decisive role in the voltage and frequency of the generator set. The engine speed responds to changes in load, and the speed of the response affects the stability of the unit's AC voltage and frequency. Existing generator sets often use electronic regulators for speed control, and electronic regulators are usually based on PID control algorithms. However, in actual applications, because load fluctuations and possible abnormalities in the intake and exhaust systems are not fully considered, the impact of speed changes caused by the PID parameter settings in the existing methods is difficult to maintain a constant speed, resulting in the generator set having a poor anti-interference ability during the control process. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide an emergency generator set control method and system, and the technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides an emergency generator set control method, the method comprising the following steps:

[0006] Collect the load power data and speed data of the emergency generator set at each collection time in each time period;

[0007] Based on the difference between the load power data and the predicted value of the load power data, the power fluctuation coefficient of each time period is obtained;

[0008] Based on the test statistics of the load power data and the number of mutation points of the load power data, the significance of the sudden change of the load in each time period is obtained;

[0009] Obtain the turbulence coefficient of the generator set in each time period based on the power fluctuation coefficient and the significance of load sudden change;

[0010] Based on the values ​​of the peak point and the non-peak point of the speed data, the speed peak steepness coefficient of each time period is obtained;

[0011] Based on the autocorrelation of the difference in the collection time of adjacent peak points of the speed data, the speed peak order coefficient of each time period is obtained;

[0012] Obtain the interference apparent coefficient of each time period based on the generator set turbulence coefficient, speed peak steepness coefficient and speed peak order coefficient;

[0013] Based on the differences between the interference obvious coefficients and the autocorrelation of the interference obvious coefficients, the disordered fluctuation value of the speed of the emergency generator set is obtained;

[0014] The emergency generator set is controlled based on the disordered speed fluctuation value combined with the PID control algorithm.

[0015] Furthermore, the method for obtaining the power fluctuation coefficient is:

[0016] For each time period, all load power data within the time period are used as the input of the Holt linear trend algorithm, and the output is the load power data prediction value at a preset number of collection moments after each time period. The mean of all load power data within the time period is calculated, and the absolute value of the difference between the predicted value of each load power data and the mean is calculated. The sum of all the absolute values ​​of the difference is used as the power fluctuation coefficient of each time period.

[0017] Furthermore, the method for obtaining the significance of the load sudden change is:

[0018] For each time period, all load power data in the time period are used as the input of the time series data segmentation algorithm, and the test statistics of all load power data in the time period and the positions of all mutation points are output. The mean of the test statistics of all load power data in the time period is calculated as the test mean, and the ratio of the total number of mutation points in the time period to the total number of load power data in the time period is calculated as the mutation ratio;

[0019] The product of the test mean and the mutation ratio in each time period is taken as the significance of the load sudden change in each time period.

[0020] Furthermore, the turbulence coefficient of the generator set in each time period is the product of the power fluctuation coefficient and the significance of the load sudden change in each time period.

[0021] Furthermore, the method for obtaining the speed peak steepness coefficient is:

[0022] For each time period, a peak extraction algorithm is used to obtain the peak point of the speed data within the time period, the mean of the speed data of all non-peak points within the time period is calculated as the first mean, and the sum of the absolute values ​​of the differences between the speed data of all peak points within the time period and the first mean is calculated as the speed peak steepness coefficient of each time period.

[0023] Furthermore, the method for obtaining the rotation speed peak ordered coefficient is:

[0024] For each time period, the absolute value of the difference between the collection times of any two adjacent peak points of the speed data in the time period is calculated as the first difference absolute value, and all the first difference absolute values ​​in the time period are sorted in chronological order to obtain the time series difference sequence of each time period; the absolute value of the autocorrelation coefficient of the time series difference sequence of each time period is calculated as the speed peak order coefficient of each time period.

[0025] Furthermore, the method for obtaining the interference obvious coefficient is:

[0026] For each time period, the product of the turbulence coefficient of the generator set and the speed peak steepness coefficient is calculated, and the ratio of the product to the speed peak order coefficient is taken as the interference obvious coefficient of each time period.

[0027] Furthermore, the method for obtaining the disorderly fluctuation value of the rotation speed is:

[0028] Sort all interference obvious coefficients in chronological order to obtain an interference obvious coefficient sequence;

[0029] The calculation formula of the speed disorder fluctuation value is: ; In the formula, It is the disorderly fluctuation value of the speed of the emergency generator set; is the absolute value of the autocorrelation coefficient of the interference-significant coefficient sequence, Indicates the total number of time periods, , They represent the interference significance coefficients of the i-th and j-th time periods respectively.

[0030] Further, the control of the emergency generator set based on the disorderly speed fluctuation value combined with the PID control algorithm includes:

[0031] The sum of the normalized value of the disorderly speed fluctuation value and the preset constant is calculated as the proportional parameter of the PID control algorithm to control the emergency generator set.

[0032] In a second aspect, an embodiment of the present application further provides an emergency generator set control system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned methods when executing the computer program.

[0033] This application has at least the following beneficial effects:

[0034] The present application proposes a control method and system for an emergency generator set. Existing generator sets often use electronic regulators for speed control. Electronic regulators are usually based on PID control algorithms. In practical applications, they do not fully consider the impact of load fluctuations and possible abnormalities in the intake and exhaust systems on speed changes. As a result, the PID parameter settings in the existing methods are difficult to maintain a constant speed, resulting in the generator set having a poor anti-interference ability during the control process. Therefore, in order to reflect the fluctuation degree of load power data in each time period, the present application constructs a power fluctuation coefficient, in order to reflect the significance of the sudden change of load power data in each time period, constructs the significance of load sudden change, and constructs the generator set turbulence coefficient according to the power fluctuation coefficient and the significance of load sudden change to reflect the instability of the fluctuation and sudden change of the load connected to the generator set; in order to reflect the steepness of the peak value of the speed data, a speed peak steepness coefficient is constructed, and in order to reflect the random situation of the peak value of the speed data in each time period, a speed peak ordered coefficient is constructed, and an interference significance coefficient is constructed based on the generator set turbulence coefficient, the speed peak steepness coefficient and the speed peak ordered coefficient to reflect the influence of load changes and the intake and exhaust system on the generator set; and combined with the differences and regular characteristics of the interference significance coefficient, the disordered fluctuation value of the speed of the generator set is calculated to reflect the instability of the speed of the emergency generator set, and the parameters of the PID control algorithm are adjusted. The beneficial effect is to accurately evaluate the constant state of the speed and optimize the parameters of the PID control in the electronic regulator, thereby making up for the defect of poor anti-interference ability of the generator set during the control process. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 A flowchart of a method for controlling an emergency generator set provided in one embodiment of the present application;

[0037] Figure 2 A flow chart for obtaining the disordered fluctuation value of the rotation speed provided in one embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of an emergency generator set control method and system proposed in accordance with the present application, its specific implementation, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0039] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0040] The following is a detailed description of a specific scheme of an emergency generator set control method and system provided by the present application in conjunction with the accompanying drawings.

[0041] See also Figure 1 , which shows a flowchart of a method for controlling an emergency generator set provided by an embodiment of the present application, the method comprising the following steps:

[0042] Step S1, collecting load power data and speed data of the emergency generator set at each collection moment in each time period.

[0043] This application takes a commonly used diesel generator set as an example. The diesel emergency generator set consists of a diesel engine, a generator, a transmission mechanism and a control module, wherein the diesel engine converts the heat energy generated by diesel combustion into mechanical energy, thereby driving the generator rotor to rotate. The generator converts the mechanical energy output by the diesel engine into electrical energy output through electromagnetic induction. The control module is used for the start and stop, operation monitoring, control regulation and protection of the generator set.

[0044] The electronic speed governor is located in the control module and consists of a speed controller, a speed sensor and an electronic actuator. In order to ensure the normal operation of the diesel generator set, the automatic control system will continuously monitor the operating status of the diesel generator and make continuous adjustments.

[0045] Furthermore, the speed of the diesel generator is very important. This application obtains the speed data of the emergency generator set through a speed sensor. The engine speed will respond to changes in the load, and the power data of the load connected to the emergency generator set when it is running is collected through a power sensor. The time interval for collecting load power data and speed data is 0.1 seconds, and the duration of a single collection is set to 1 minute. In order to more accurately evaluate the fluctuations of power data in the short term, the collection time is evenly divided into 10 time periods, and the implementer can select other numbers according to actual conditions.

[0046] At this point, the load power data and speed data have been obtained.

[0047] Step S2, based on the difference between the load power data and the predicted value of the load power data, obtain the power fluctuation coefficient of each time period; based on the test statistic of the load power data and the number of mutation points of the load power data, obtain the significance of the load sudden change in each time period; based on the power fluctuation coefficient and the significance of the load sudden change, obtain the turbulence coefficient of the generator set in each time period.

[0048] When the main power fails, the emergency generator set will start to take over the main power supply. The speed of the generator needs to be kept constant to ensure the standard power supply frequency. During the power supply process, the connected load will affect the speed of the emergency generator set. For example, when the load of the generator set increases, more motor power is required to maintain the original speed. If the motor power is insufficient, the rotation resistance of the generator set increases, causing the speed to decrease. Conversely, when the load decreases, the speed will increase. Therefore, the more unstable the load, the greater the impact on the speed of the emergency generator.

[0049] Therefore, the stability of the power data of the connected load is analyzed. First, when the load is partially switched from the main power supply to the emergency generator, the operating frequency state of the load usually has a certain degree of fluctuation, which is manifested as an overall increase or decrease in the power data in a short period of time. The magnitude of the increase or decrease will affect the speed of the generator set.

[0050] According to the above analysis, in order to reflect the fluctuation degree of the load power data in each time period, a time series prediction algorithm is used to analyze the load power data in each time period. The time series prediction algorithm selected in this embodiment is the Holt linear trend algorithm. The implementer can select other time series prediction algorithms according to the actual situation. For each time period, all the load power data in the time period are used as the input of the Holt linear trend algorithm, and the output is the load power data prediction value at the preset number of collection moments after each time period; the preset number in this embodiment is 5, and the implementer can select other values ​​according to the actual situation; calculate the mean of all the load power data in the time period, calculate the absolute value of the difference between the predicted value of each load power data and the mean, and use the sum of all the absolute values ​​of the difference as the power fluctuation coefficient of each time period. Among them, the Holt linear trend algorithm is a well-known technology and will not be repeated in this embodiment.

[0051] It should be noted that, for each time period, when the power fluctuation coefficient of the time period is larger, the fluctuation degree of the load power data within the time period is larger; conversely, the fluctuation degree of the load power data within the time period is smaller.

[0052] In addition, the working state of the load when the emergency generator set is connected may be somewhat different from usual. For example, there are instantaneous changes in the start and stop of electrical appliances or changes in operating modes. The frequency and amplitude of these instantaneous changes will affect the stability of the generator set speed. Specifically, the higher the frequency of the changes and the greater the amplitude of the changes, the greater the impact on the generator set speed.

[0053] According to the above analysis, this application adopts a time series data segmentation algorithm for mutation detection. In this embodiment, the time series data segmentation algorithm uses the Bernaola Galvan segmentation algorithm, and the implementer can select other time series segmentation algorithms according to actual conditions. The Bernaola Galvan segmentation algorithm is a well-known technology and will not be described in detail in this embodiment.

[0054] For each time period, all load power data in the time period are used as input to the Bernaola Galvan segmentation algorithm, the significance level is set to 0.95, and the test statistics of all load power data in the time period and the positions of all mutation points in the time period are output.

[0055] It should be noted that the larger the test statistic corresponding to the load power data at the time of collection, the larger the magnitude of the sudden change in the power load at the time of collection. In order to reflect the above characteristics, for each time period, the mean of the test statistic of all load power data in the time period is calculated as the test mean, and the ratio of the total number of mutation points in the time period to the total number of load power data in the time period is calculated as the mutation ratio.

[0056] It should be noted that, the larger the test mean, the larger the amplitude of the drastic change in the load power data, and vice versa, the smaller the amplitude of the drastic change in the load power data; the larger the mutation ratio, the higher the frequency of drastic changes in the load power data, and vice versa, the frequency of drastic changes in the load power data is lower.

[0057] Furthermore, in order to reflect the significance of the sudden change in load power data within each time period, the significance of the sudden change in load for each time period is calculated. For each time period, the product of the test mean and the mutation ratio of the time period is taken as the significance of the sudden change in load for each time period. It should be noted that the larger the value of the significance of the sudden change in load power is, the more significant the sudden change in load power within the time period is; conversely, the smaller the sudden change within the time period is.

[0058] Furthermore, based on the above analysis, in order to reflect the fluctuation and sudden instability of the connected load of the generator set, the generator set turbulence coefficient in each time period is calculated, and the calculation formula is: ; In the formula, represents the turbulence coefficient of the generator set in the i-th time period; represents the power fluctuation coefficient in the i-th time period, Indicates the significance of the load change in the i-th time period.

[0059] It should be noted that for each time period, the larger the values ​​of the power fluctuation coefficient and the load sudden change significance, the stronger the instability of the load within the time period. At this time, the larger the turbulence coefficient of the generator set, the greater the impact on the speed of the generator set; conversely, the smaller the turbulence coefficient of the generator set, the smaller the impact on the speed of the generator set.

[0060] Step S3, based on the magnitude of the values ​​of the peak point and the non-peak point of the speed data, obtain the speed peak steepness coefficient of each time period; based on the autocorrelation of the difference in the collection time of adjacent peak points of the speed data, obtain the speed peak ordered coefficient of each time period; based on the generator set turbulence coefficient, the speed peak steepness coefficient and the speed peak ordered coefficient, obtain the interference obvious coefficient of each time period; based on the difference between the interference obvious coefficients and the autocorrelation of the interference obvious coefficients, obtain the speed disordered fluctuation value of the emergency generator set.

[0061] Furthermore, the diesel emergency generator may have abnormalities in the intake and exhaust systems during use, such as air filter blockage, intake pipe leakage, and excessive exhaust back pressure. These problems will lead to insufficient intake pressure, reduce the combustion effect in the cylinder, and thus fail to provide a stable power supply frequency.

[0062] Specifically, if the intake and exhaust pipes leak or become clogged, the intake and exhaust capacity of the diesel engine will be unstable, causing the emergency generator speed to have more randomly distributed peaks than in normal conditions. The amplitudes of these peaks and non-peak position data are quite different, and the peak positions are also irregular.

[0063] According to the above analysis, for each time period, a peak extraction algorithm is used to obtain the peak point of the speed data in the time period. The peak extraction algorithm selected in this embodiment is the automatic multi-scale peak extraction algorithm (AMPD), and the implementer can select other peak extraction algorithms according to actual conditions; the mean of the speed data of all non-peak points in the time period is calculated as the first mean, and the sum of the absolute values ​​of the differences between the speed data of all peak points in the time period and the first mean is calculated as the speed peak steepness coefficient of each time period; it should be noted that the steeper the peak value of the speed data in each time period, the greater the speed peak steepness coefficient; otherwise, the smaller the speed peak steepness coefficient.

[0064] Furthermore, in order to reflect the randomness of the peak value of the speed data in each time period, for each time period, the absolute value of the difference between the acquisition moments of all two adjacent peak points of the speed data in the time period is calculated as the first absolute value of the difference, and all the first absolute values ​​of the difference in the time period are sorted in chronological order to obtain the time series difference sequence of each time period; the absolute value of the autocorrelation coefficient of the time series difference sequence of each time period is calculated as the speed peak ordered coefficient of each time period; it should be noted that the more random the peak distribution of the speed data in each time period, the smaller the value of the speed peak ordered coefficient; otherwise, the larger the value of the speed peak ordered coefficient. Among them, the calculation method of the autocorrelation coefficient is a well-known technology and will not be repeated in this embodiment.

[0065] Furthermore, if the load is more unstable, the engine needs to adjust the intake and exhaust system to adapt to the new power demand. If there is a problem with the intake and exhaust system, this adjustment may be limited, thus affecting the performance of the engine. Therefore, based on the above analysis, in order to reflect the impact of load changes and the intake and exhaust system on the generator set, the interference coefficient of each time period is calculated, and the calculation formula is: ; In the formula, represents the interference significance coefficient of the i-th time period; is the turbulence coefficient of the generator set in the i-th time period, is the speed peak steepness coefficient of the i-th time period, is the peak speed order coefficient of the i-th time period.

[0066] It should be noted that for each time period, when the speed of the generator set is affected by load changes or greater interference from the intake and exhaust system within the time period, the greater the values ​​of the generator set turbulence coefficient and the speed peak steepness coefficient, the smaller the value of the speed peak order coefficient, and the greater the interference obvious coefficient obtained at this time; conversely, the smaller the interference obvious coefficient obtained.

[0067] Furthermore, under load changes or interference from the intake and exhaust systems, the speed of the diesel generator set exhibits significant irregular fluctuation characteristics. Specifically, when the speed of the emergency generator set is not constant, the greater the difference in the interference coefficients affected by load changes and the intake and exhaust systems in different time periods. According to the above analysis, all interference coefficients of the emergency generator set are sorted in chronological order to obtain the interference coefficient sequence. In order to reflect the instability of the speed of the emergency generator set, the disordered fluctuation value of the speed of the emergency generator set is calculated. The calculation formula is: ; In the formula, It is the disorderly fluctuation value of the speed of the emergency generator set; is the absolute value of the autocorrelation coefficient of the interference-significant coefficient sequence, Indicates the total number of time periods, , They represent the interference coefficients of the i-th and j-th time periods respectively. The flow chart for obtaining the disorderly fluctuation value of the speed is as follows: Figure 2 shown.

[0068] It should be noted that The larger the value, the worse the regularity of the generator speed. The larger the value, the more obvious the irregular fluctuation characteristics of the generator speed are. At this time, the disorderly fluctuation value of the speed of the emergency generator set is obtained. The larger the value, the less constant the generator speed is; on the contrary, the disorderly fluctuation value of the speed of the emergency generator is obtained. The smaller it is, the more constant the generator speed is.

[0069] Step S4, controlling the emergency generator set based on the disorderly speed fluctuation value combined with a PID control algorithm.

[0070] At this point, the speed disorder fluctuation value of the emergency generator set is obtained. If the speed disorder fluctuation value D is larger, it means that the speed of the generator set is less constant, and it is necessary to increase the response speed of the electronic controller to the speed control, that is, increase the proportional term parameter of the PID control in the electronic controller. If the speed disorder fluctuation value D is smaller, it means that the speed of the generator set is more constant, and the proportional term parameter of the PID control in the electronic controller can be reduced to avoid overshoot.

[0071] The parameters of the PID control set in this application are preset as follows: the proportional term is 1, the integral term is 0.85, and the differential term is 0.5. The proportional term will affect the response rate of the control. The proportional term parameters of the next acquisition duration are optimized based on the D value within the current acquisition duration. The specific calculation formula is: , where Y is the optimized proportional term parameter, The normalized value of the disordered speed fluctuation value is used in this application. The Sigmoid function is used for normalization, and the integral term and the differential term remain unchanged. In this way, the PID control parameters are optimized. In the control process of the generator set, the speed controller in the electronic regulator uses the optimized PID control algorithm to adjust the speed of the generator set, and the electronic actuator adjusts the fuel supply, which can improve the control efficiency of the emergency generator set to ensure the stability of the output voltage and frequency of the generator set.

[0072] Based on the same inventive concept as the above method, an embodiment of the present application also provides an emergency generator set control system, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned emergency generator set control methods are implemented.

[0073] It should be noted that the above sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0075] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for controlling an emergency generator set, characterized in that: The method comprises the following steps: Collect the load power data and speed data of the emergency generator set at each collection time in each time period; Based on the difference between the load power data and the predicted value of the load power data, the power fluctuation coefficient of each time period is obtained; Based on the test statistics of the load power data and the number of mutation points of the load power data, the significance of the sudden change of the load in each time period is obtained; Obtain the turbulence coefficient of the generator set in each time period based on the power fluctuation coefficient and the significance of load sudden change; Based on the values ​​of the peak point and the non-peak point of the speed data, the speed peak steepness coefficient of each time period is obtained; Based on the autocorrelation of the difference in the collection time of adjacent peak points of the speed data, the speed peak order coefficient of each time period is obtained; Obtain the interference apparent coefficient of each time period based on the generator set turbulence coefficient, speed peak steepness coefficient and speed peak order coefficient; Based on the differences between the interference obvious coefficients and the autocorrelation of the interference obvious coefficients, the disordered fluctuation value of the speed of the emergency generator set is obtained; Control the emergency generator set based on the disorderly speed fluctuation value combined with the PID control algorithm; The control of the emergency generator set based on the disorderly speed fluctuation value combined with the PID control algorithm includes: The sum of the normalized value of the disorderly speed fluctuation value and the preset constant is calculated as the proportional term parameter of the PID control algorithm to control the emergency generator set.

2. The emergency generator control method according to claim 1, characterized in that: The method for obtaining the power fluctuation coefficient is: For each time period, all load power data within the time period are used as the input of the Holt linear trend algorithm, and the output is the load power data prediction value at a preset number of collection moments after each time period. The mean of all load power data within the time period is calculated, and the absolute value of the difference between the predicted value of each load power data and the mean is calculated. The sum of all the absolute values ​​of the difference is used as the power fluctuation coefficient of each time period.

3. The emergency generator control method according to claim 1, characterized in that: The method for obtaining the significance of the load sudden change is: For each time period, all load power data in the time period are used as the input of the time series data segmentation algorithm, and the test statistics of all load power data in the time period and the positions of all mutation points are output. The mean of the test statistics of all load power data in the time period is calculated as the test mean, and the ratio of the total number of mutation points in the time period to the total number of load power data in the time period is calculated as the mutation ratio; The product of the test mean and the mutation ratio in each time period is taken as the significance of the load sudden change in each time period.

4. The emergency generator set control method according to claim 1, characterized in that: The generator set turbulence coefficient in each time period is the product of the power fluctuation coefficient and the load sudden change significance in each time period.

5. The emergency generator control method according to claim 1, characterized in that: The method for obtaining the speed peak steepness coefficient is: For each time period, a peak extraction algorithm is used to obtain the peak point of the speed data within the time period, the mean of the speed data of all non-peak points in the time period is calculated as the first mean, and the sum of the absolute values ​​of the differences between the speed data of all peak points in the time period and the first mean is calculated as the speed peak steepness coefficient of each time period.

6. The emergency generator control method according to claim 1, characterized in that: The method for obtaining the rotation speed peak ordered coefficient is: For each time period, the absolute value of the difference between the collection times of any two adjacent peak points of the speed data in the time period is calculated as the first difference absolute value, and all the first difference absolute values ​​in the time period are sorted in chronological order to obtain the time series difference sequence of each time period; the absolute value of the autocorrelation coefficient of the time series difference sequence of each time period is calculated as the speed peak order coefficient of each time period.

7. The emergency generator control method according to claim 1, characterized in that: The method for obtaining the interference obvious coefficient is: For each time period, the product of the turbulence coefficient of the generator set and the speed peak steepness coefficient is calculated, and the ratio of the product to the speed peak order coefficient is taken as the interference obvious coefficient of each time period.

8. The emergency generator control method according to claim 1, characterized in that: The method for obtaining the disorderly fluctuation value of the rotation speed is as follows: Sort all interference obvious coefficients in chronological order to obtain an interference obvious coefficient sequence; The calculation formula of the speed disorder fluctuation value is: ; In the formula, It is the disorderly fluctuation value of the speed of the emergency generator set; is the absolute value of the autocorrelation coefficient of the interference-significant coefficient sequence, Indicates the total number of time periods, , They represent the interference significance coefficients of the i-th and j-th time periods respectively.

9. An emergency generator control system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the emergency generator set control method as described in any one of claims 1 to 8 are implemented.

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