GPSS Automatic Switching Method and Device Based on Online Identification of Oscillation Modes

Abstract

The present invention discloses a method and device for automatically putting on and taking off GPSS based on online identification of oscillation modes. After initializing the parameters for online identification of oscillation modes, it is detected whether the ultra-low frequency oscillation flag is 1. If it is not 1, frequency sampling data with a preset time window length is taken for online identification of oscillation modes until the ultra-low frequency oscillation condition is met, at which time the ultra-low frequency oscillation flag is set to 1. When the ultra-low frequency oscillation flag is 1, the GPSS function is put on, and when the GPSS exit condition is met, the GPSS function is taken off. This realizes the targeted automatic putting on and taking off of the GPSS function, avoids the problem of frequent operation of the oil pump that may be caused by long-term activation of the GPSS, and at the same time ensures that the GPSS operates within the set effective frequency band of ultra-low frequency oscillation, avoiding negative impacts on oscillations in other frequency bands caused by the GPSS.

Description

Technical Field

[0001] The present invention relates to the technical field of power devices, and in particular, to a method and device for automatically switching on and off GPSS based on online identification of oscillation modes. Background Art

[0002] Currently, the power system stabilizer (PSS) is the most widely used, most economical, and technically mature measure for suppressing low-frequency oscillations in the world. In fact, PSS can also be installed on the speed control device side of a synchronous generator set, and this type of PSS can be abbreviated as GPSS (governor power system stabilizer). The main principle of GPSS is that when ultra-low-frequency oscillations occur, it can generate a mechanical power (torque) increment opposite to the frequency difference, which is equivalent to adding positive mechanical damping to the device, thereby playing a role in suppressing ultra-low-frequency oscillations. However, GPSS has the problem of frequent operation of the speed control oil pump, which causes serious overheating and a decrease in oil pressure. Therefore, the present invention provides a method and device for automatically switching on and off GPSS based on online identification of oscillation modes, which is used to realize the targeted automatic switching on and off of the GPSS function, avoid the problem of frequent operation of the oil pump that may be caused by long-term input of GPSS, and at the same time ensure that GPSS operates within the set effective frequency band of ultra-low-frequency oscillations, and avoid negative impacts of GPSS on oscillations in other frequency bands. Summary of the Invention

[0003] The present invention provides a method and device for automatically switching on and off GPSS based on online identification of oscillation modes, which is used to realize the targeted automatic switching on and off of the GPSS function, avoid the problem of frequent operation of the oil pump that may be caused by long-term input of GPSS, and at the same time ensure that GPSS operates within the set effective frequency band of ultra-low-frequency oscillations, and avoid negative impacts of GPSS on oscillations in other frequency bands.

[0004] In view of this, the first aspect of the present invention provides a method for automatically switching on and off GPSS based on online identification of oscillation modes, including the following steps:

[0005] S1. Initialize the first parameters for online identification of GPSS oscillation modes. The first parameters include the current time identifier, ultra-low-frequency oscillation identifier, ultra-low-frequency oscillation counter, and online identification timer for oscillation modes;

[0006] S2. Detect whether the ultra-low-frequency oscillation identifier is 1. If so, jump to step S8; otherwise, jump to step S3;

[0007] S3. Taking the current time as the base point, obtain the frequency sampling data for the preset analysis time window length period in the past;

[0008] S4. Perform online identification of oscillation modes for the frequency sampling data in the preset analysis time window length period in the past;

[0009] S5. Determine whether the ultra-low frequency oscillation condition is satisfied according to the online identification result of the oscillation mode. If so, jump to step S6; otherwise, jump to step S7;

[0010] S6. Set the ultra-low frequency oscillation flag to 1 and return to step S2;

[0011] S7. Add the oscillation analysis sliding step size to both the current time flag and the online identification timer of the oscillation mode, and return to step S3;

[0012] S8. Activate the GPSS function, perform initialization of the second parameters, and jump to step S9. The second parameters include the GPSS continuous action timer and the GPSS output dead zone counter;

[0013] S9. Taking the current time as the base point, obtain the GPSS output quantity sampling data in the period that is half of the preset analysis time window length in the past;

[0014] S10. Determine whether the GPSS exit condition is satisfied according to the GPSS output quantity sampling data. If so, jump to step S12; otherwise, jump to step S11;

[0015] S11. Increment the current time flag by 1 and increment the GPSS continuous action timer by 1, and return to step S9;

[0016] S12. Exit the GPSS function and return to step S1.

[0017] Optionally, step S10 specifically includes:

[0018] S101. Calculate the average value of positive values and the average value of negative values in the GPSS output quantity sampling data respectively, and take the one with the larger absolute value of the average value of positive values and the average value of negative values as the target average value;

[0019] S102. Determine whether the absolute value of the target average value satisfies the condition of being greater than the GPSS stop dead zone × the GPSS maximum action time. If so, jump to step S12; otherwise, jump to step S103;

[0020] S103. Calculate the maximum value and the minimum value of the GPSS output quantity sampling data respectively, and jump to step S104;

[0021] S104. Determine whether the absolute value of the maximum value of the sampled data of the GPSS output quantity is less than the GPSS stop dead zone, and whether the absolute value of the minimum value of the sampled data of the GPSS output quantity is less than the GPSS stop dead zone. If so, it is determined that the GPSS output is approximately 0 and has entered the dead zone, and jump to step S107; otherwise, jump to step S105;

[0022] S105. Increment the current time identifier by 1, increment the GPSS continuous action timer by 1, and jump to step S106;

[0023] S106. Determine whether the GPSS continuous action timer is greater than the GPSS maximum action time. If so, jump to step S12; otherwise, jump to step S9;

[0024] S107. Increment the GPSS output dead zone counter by 1, and jump to step S108;

[0025] S108. Determine whether the GPSS output dead zone counter is greater than half of the past preset analysis time window length. If so, jump to step S12; otherwise, jump to step S105.

[0026] Optionally, in step S4, the Prony analysis method is used to perform online oscillation mode identification on the frequency sampling data in the past preset analysis time window length period.

[0027] Optionally, step S5 includes:

[0028] S51. Denote the peak-to-peak value of the frequency sampling data in the time window [T - TW, T] as PPV, where T is the current time identifier and TW is the preset analysis time window length;

[0029] S52. Determine whether PPV is greater than twice the frequency oscillation dead zone. If so, jump to step S53; otherwise, jump to step S511;

[0030] S53. Screen out the modes whose amplitude results in the online oscillation mode identification are greater than TH2×PPV / 2 and rank among the top TH3, where TH2 is the minimum amplitude of the mode and TH3 is the upper limit of the number of modes;

[0031] S54. Determine whether there is a mode among the screened modes whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency. If so, jump to step S55; if not, jump to step S511;

[0032] S55. Determine whether the damping ratio of the mode whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency is less than the mode damping ratio threshold. If so, jump to step S56; otherwise, jump to step S511;

[0033] S56. Increment the ultra-low frequency oscillation counter by 1 and jump to step S57;

[0034] S57. Determine whether the ultra-low frequency oscillation counter changes from 0 to 1. If so, jump to step S510; otherwise, jump to step S58;

[0035] S58. Determine whether the ultra-low frequency oscillation counter is greater than the oscillation times threshold. If so, jump to step S59; otherwise, jump to step S511;

[0036] S59. Set the ultra-low frequency oscillation flag to 1 and jump to step S2;

[0037] S510. Set the oscillation mode online identification timer to 0 and jump to step S511;

[0038] S511. Add the oscillation analysis sliding step to the current time flag and add the oscillation analysis sliding step to the oscillation mode online identification timer, then jump to step S512;

[0039] S512. Determine whether the oscillation mode online identification timer is greater than the maximum time for resetting to zero. If so, jump to step S513; otherwise, jump to step S2;

[0040] S513. Set the ultra-low frequency oscillation counter to 0 and jump to step S2.

[0041] Optionally, step S6 specifically includes:

[0042] S61. Determine whether the parameter switching condition is satisfied according to the oscillation frequency. If so, jump to step S62; otherwise, jump to step S63;

[0043] S62. Switch the GPSS control link parameters and jump to step S63;

[0044] S63. Add the oscillation analysis sliding step to the current time flag and add the oscillation analysis sliding step to the oscillation mode online identification timer, then return to step S3;

[0045] S63. Set the ultra-low frequency oscillation flag to 1 and return to step S2.

[0046] The second aspect of the present invention provides a GPSS automatic switching-on and switching-off device based on online identification of oscillation modes, including a control module;

[0047] The control module is used to execute the following steps:

[0048] S1. Initialize the first parameters for online identification of the GPSS oscillation mode. The first parameters include the current time flag, the ultra-low frequency oscillation flag, the ultra-low frequency oscillation counter, and the oscillation mode online identification timer;

[0049] S2. Detect whether the ultra-low frequency oscillation flag is 1. If so, jump to step S8; otherwise, jump to step S3.

[0050] S3. Taking the current time as the base point, obtain the frequency sampling data for the preset analysis time window length period in the past.

[0051] S4. Perform online identification of oscillation modes on the frequency sampling data for the preset analysis time window length period in the past.

[0052] S5. Determine whether the ultra-low frequency oscillation condition is satisfied according to the online identification result of the oscillation mode. If so, jump to step S6; otherwise, jump to step S7.

[0053] S6. Set the ultra-low frequency oscillation flag to 1 and return to step S2.

[0054] S7. Add the oscillation analysis sliding step length to both the current time flag and the online identification timer of the oscillation mode, and return to step S3.

[0055] S8. Activate the GPSS function, perform initialization of the second parameters, and jump to step S9. The second parameters include the GPSS continuous action timer and the GPSS output dead zone counter.

[0056] S9. Taking the current time as the base point, obtain the GPSS output quantity sampling data for the period that is half of the preset analysis time window length in the past.

[0057] S10. Determine whether the GPSS exit condition is satisfied according to the GPSS output quantity sampling data. If so, jump to step S12; otherwise, jump to step S11.

[0058] S11. Increment the current time flag by 1 and increment the GPSS continuous action timer by 1, and return to step S9.

[0059] S12. Exit the GPSS function and return to step S1.

[0060] Optionally, step S10 specifically includes:

[0061] S101. Calculate the average value of positive values and the average value of negative values in the GPSS output quantity sampling data respectively, and take the one with the larger absolute value of the average value of positive values and the average value of negative values as the target average value.

[0062] S102. Determine whether the absolute value of the target average value satisfies the condition of being greater than the GPSS stop dead zone × the GPSS maximum action time. If so, jump to step S12; otherwise, jump to step S103.

[0063] S103. Calculate the maximum value and the minimum value of the GPSS output quantity sampling data respectively, and jump to step S104.

[0064] S104. Determine whether the absolute value of the maximum value of the GPSS output amount sampling data is less than the GPSS stop dead zone, and whether the absolute value of the minimum value of the GPSS output amount sampling data is less than the GPSS stop dead zone. If so, determine that the GPSS output is approximately 0 and has entered the dead zone, and jump to step S107; otherwise, jump to step S105.

[0065] S105. Increment the current time identifier by 1, increment the GPSS continuous action timer by 1, and jump to step S106.

[0066] S106. Determine whether the GPSS continuous action timer is greater than the GPSS maximum action time. If so, jump to step S12; otherwise, jump to step S9.

[0067] S107. Increment the GPSS output dead zone counter by 1, and jump to step S108.

[0068] S108. Determine whether the GPSS output dead zone counter is greater than half of the past preset analysis time window length. If so, jump to step S12; otherwise, jump to step S105.

[0069] Optionally, in step S4, the Prony analysis method is used to perform online identification of the oscillation mode for the frequency sampling data in the past preset analysis time window length period.

[0070] Optionally, step S5 includes:

[0071] S51. Denote the peak-to-peak value of the frequency sampling data in the time window [T - TW, T] as PPV, where T is the current time identifier and TW is the preset analysis time window length.

[0072] S52. Determine whether PPV is greater than twice the frequency oscillation dead zone. If so, jump to step S53; otherwise, jump to step S511.

[0073] S53. Screen out the modes whose amplitude results in the online identification of the oscillation mode are greater than TH2×PPV / 2 and rank among the top TH3, where TH2 is the minimum amplitude of the mode and TH3 is the upper limit of the number of modes.

[0074] S54. Determine whether there is a mode among the screened modes whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency. If so, jump to step S55; if not, jump to step S511.

[0075] S55. Determine whether the damping ratio of the mode whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency is less than the mode damping ratio threshold. If so, jump to step S56; otherwise, jump to step S511.

[0076] S56. Increment the ultra-low frequency oscillation counter by 1 and jump to step S57;

[0077] S57. Determine whether the ultra-low frequency oscillation counter changes from 0 to 1. If so, jump to step S510; otherwise, jump to step S58;

[0078] S58. Determine whether the ultra-low frequency oscillation counter is greater than the oscillation times threshold. If so, jump to step S59; otherwise, jump to step S511;

[0079] S59. Set the ultra-low frequency oscillation flag to 1 and jump to step S2;

[0080] S510. Set the oscillation mode online identification timer to 0 and jump to step S511;

[0081] S511. Add the oscillation analysis sliding step to the current time flag and add the oscillation analysis sliding step to the oscillation mode online identification timer, then jump to step S512;

[0082] S512. Determine whether the oscillation mode online identification timer is greater than the maximum time for resetting to zero. If so, jump to step S513; otherwise, jump to step S2;

[0083] S513. Set the ultra-low frequency oscillation counter to 0 and jump to step S2.

[0084] Optionally, step S6 specifically includes:

[0085] S61. Determine whether the parameter switching condition is satisfied according to the oscillation frequency. If so, jump to step S62; otherwise, jump to step S63;

[0086] S62. Switch the GPSS control link parameters and jump to step S63;

[0087] S63. Set the ultra-low frequency oscillation flag to 1 and return to step S2.

[0088] It can be seen from the above technical solutions that the GPSS automatic switching-on and switching-off method and device based on online identification of oscillation mode provided by the present invention have the following advantages:

[0089] The GPSS automatic switching-on and switching-off method based on online identification of oscillation modes provided by the present invention, after initializing the parameters for online identification of oscillation modes, detects whether the ultra-low frequency oscillation flag is 1. If it is not 1, it takes the frequency sampling data of the preset time window length for online identification of oscillation modes until the ultra-low frequency oscillation condition is met, and then sets the ultra-low frequency oscillation flag to 1. When the ultra-low frequency oscillation flag is 1, the GPSS function is switched on, and when the GPSS exit condition is met, the GPSS function is switched off again, realizing the targeted automatic switching-on and switching-off of the GPSS function, avoiding the problem of frequent operation of the oil pump that may be caused by long-term activation of the GPSS, and at the same time ensuring that the GPSS operates within the set effective frequency band of ultra-low frequency oscillation, avoiding negative impacts on oscillations in other frequency bands caused by the GPSS.

[0090] At the same time, two sets of GPSS control parameters are configured in the GPSS, and the GPSS parameters can be automatically switched according to the results of ultra-low frequency oscillation analysis to better adapt to the entire ultra-low frequency oscillation frequency band.

[0091] The GPSS automatic switching-on and switching-off device based on online identification of oscillation modes provided by the present invention is used to execute the GPSS automatic switching-on and switching-off method based on online identification of oscillation modes provided by the present invention. Its principle and the achieved technical effects are the same as those of the GPSS automatic switching-on and switching-off method based on online identification of oscillation modes provided by the present invention, and will not be elaborated here. Description of the Drawings

[0092] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other relevant drawings can also be obtained based on these drawings.

[0093] Figure 1 It is a schematic flowchart of an embodiment of a GPSS automatic switching-on and switching-off method based on online identification of oscillation modes provided by the present invention;

[0094] Figure 2 It is a schematic flowchart of another embodiment of a GPSS automatic switching-on and switching-off method based on online identification of oscillation modes provided by the present invention;

[0095] Figure 3 It is a schematic diagram of the ultra-low frequency oscillation determination condition provided by the present invention;

[0096] Figure 4 It is a schematic diagram of the GPSS exit condition provided by the present invention. Detailed Embodiments

[0097] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solution in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0098] For ease of understanding, please refer to Figure 1 , an embodiment of a GPSS automatic switching-on and switching-off method based on online identification of oscillation modes is provided in the present invention, including:

[0099] Step S1: Initialize the first parameters for online identification of the GPSS oscillation mode. The first parameters include the current time identifier, ultra-low frequency oscillation identifier, ultra-low frequency oscillation counter, and online identification timer for the oscillation mode.

[0100] It should be noted that in the embodiments of the present invention, first, the first parameters for online identification of the GPSS oscillation mode need to be initialized, and the description of the first parameters is shown in Table 1.

[0101] Table 1

[0102]

[0103] Among them, if the Prony analysis method is used for online identification of the oscillation mode, the corresponding description of TIME_Count is the Prony analysis timer. The current time identifier is represented by T, the ultra-low frequency oscillation identifier is represented by SLFO_FLAG. When the value of SLFO_FLAG is 1, it means that the online identification function of the oscillation mode monitors the occurrence of ultra-low frequency oscillation. The ultra-low frequency oscillation counter is represented by SLFO_Count. When the online identification result of the oscillation mode meets the threshold parameter, SLFO_Count is incremented by 1. The online identification timer for the oscillation mode is represented by TIME_Count. When SLFO_Count changes from 0 to 1, TIME_Count is cleared.

[0104] Step S2: Detect whether the ultra-low frequency oscillation identifier is 1. If so, jump to step S8; otherwise, jump to step S3.

[0105] It should be noted that detect whether the ultra-low frequency oscillation identifier SLFO_FLAG is 1. If the ultra-low frequency oscillation identifier SLFO_FLAG is 1, then turn on the GPSS function and jump to step S8; otherwise, jump to step S3.

[0106] Step S3: Taking the current time as the base point, obtain the frequency sampling data for the past preset analysis time window length period.

[0107] It should be noted that if the ultra-low frequency oscillation identifier SLFO_FLAG is not 1, then taking the current time as the base point, frequency sampling data for a preset analysis time window length in the past is taken, where the preset analysis time window length is represented by TW, and TW can be set according to the actual situation.

[0108] Step S4: Perform on-line identification of oscillation modes for the frequency sampling data for a preset analysis time window length in the past.

[0109] It should be noted that commonly used signal analysis methods such as the Fourier algorithm, fast Fourier transform algorithm, wavelet analysis, etc. are widely used, but there are still limitations such as difficulty in extracting attenuation characteristics when analyzing oscillation problems. The Prony analysis method uses a linear combination of exponential functions to describe the mathematical model of equally spaced sampling data, and then solves the eigenvalues of the model polynomial to obtain information such as different modal frequencies, amplitudes, initial phases, and attenuation factors of a given signal. Using the Prony analysis method, the characteristics of oscillation signals can be directly extracted, providing a basis for oscillation mode and damping analysis. Since the Prony method does not require establishing a system mathematical model, it has unique advantages for analyzing the oscillation modes of large power grids. Therefore, in the embodiments of the present invention, the Prony analysis method is used to identify ultra-low frequency oscillations.

[0110] Step S5: Determine whether the ultra-low frequency oscillation condition is satisfied according to the on-line identification result of the oscillation mode. If so, jump to step S6; otherwise, jump to step S7.

[0111] It should be noted that if the result of performing Prony analysis on the frequency sampling data obtained in step S4 satisfies the ultra-low frequency oscillation condition, then the ultra-low frequency oscillation identifier SLFO_FLAG is set to 1, and return to step S2. If the result of performing Prony analysis on the frequency sampling data obtained in step S4 does not satisfy the ultra-low frequency oscillation condition, then step S7 is executed.

[0112] In the embodiments of the present invention, according to the frequency, amplitude, and damping ratio information of the oscillation modes obtained by Prony analysis, the dominant ultra-low frequency oscillation mode is extracted to determine whether the ultra-low frequency oscillation condition is satisfied. The main parameters of the ultra-low frequency oscillation condition are shown in Table 2.

[0113] Table 2

[0114] Parameter Type Unit Description TH1 Floating point type Hz Frequency oscillation dead zone TH2 Floating point type p.u. Modal minimum amplitude TH3 Integer type - Upper limit of the number of modes TH4 Floating point type Hz Lower limit of modal frequency TH5 Floating point type Hz Upper limit of modal frequency TH6 Floating point type - Modal damping ratio threshold TH7 Integer type - Threshold of the number of oscillations TH8 Integer type s Maximum time to zero

[0115] Therefore, in one embodiment, as Figure 3 shown, the specific steps of step S5 are:

[0116] Step S51: Denote the peak-to-peak value of the frequency sampling data in the time window [T - TW, T] as PPV, where T is the current time identifier and TW is the preset analysis time window length.

[0117] Step S52: Determine whether PPV is greater than twice the frequency oscillation dead zone TH1, that is, whether PPV > 2 × TH1 is satisfied. If so, jump to Step S53; otherwise, jump to Step S511. This step can avoid the influence of small frequency fluctuations on oscillation analysis.

[0118] Step S53: Screen out the modes whose amplitude results in online oscillation mode identification are greater than TH2 × PPV / 2 and rank among the top TH3. This step can filter out the high-frequency components with small amplitudes in the Prony analysis results and reduce the influence of Prony analysis overfitting on the analysis results.

[0119] Step S54: Determine whether there is a mode among the screened modes whose frequency is within the range of the modal frequency lower limit TH4 to the modal frequency upper limit TH5. If so, jump to Step S55; if not, jump to Step S511. The setting of the TH4 parameter is on the one hand to filter out the influence of the DC mode, and on the other hand to set the lower limit of the oscillation frequency that the current GPSS module can effectively suppress. TH5 is the upper limit of the modal selection frequency. When the oscillation frequency is lower than TH5, it is considered that the system has ultra-low frequency oscillation.

[0120] Step S55: Determine whether the damping ratio of the mode whose frequency is within the range of the modal frequency lower limit to the modal frequency upper limit is less than the modal damping ratio threshold TH6. If so, it is considered that the damping ratio of the dominant oscillation mode is low, and it is determined that ultra-low frequency oscillation has occurred at this time, and jump to Step S56; otherwise, jump to Step S511.

[0121] Step S56: Increment the ultra-low frequency oscillation counter SLFO_Count by 1 and jump to Step S57.

[0122] Step S57: Determine whether the ultra-low frequency oscillation counter SLFO_Count changes from 0 to 1. If so, jump to Step S510; otherwise, jump to Step S58.

[0123] Step S58: Determine whether the ultra-low frequency oscillation counter SLFO_Count is greater than the oscillation times threshold TH7. If so, jump to Step S59; otherwise, jump to Step S511. This step can implement multiple rolling Prony analyses to confirm that the system has ultra-low frequency oscillation.

[0124] Step S59: Set the ultra-low frequency oscillation flag SLFO_FLAG to 1 and jump to Step S2.

[0125] Step S510, set the oscillation mode online identification timer TIME_Count to 0, and jump to step S511.

[0126] Step S511, add the current time mark T to the oscillation analysis sliding step TI, add the oscillation mode online identification timer TIME_Count to the oscillation analysis sliding step TI, and jump to step S512.

[0127] Step S512, determine whether the oscillation mode online identification timer TIME_Count is greater than the maximum zeroing time TH8, if so, jump to step S513, otherwise jump to step S2. This step can prevent the ultra-low frequency oscillation counter SLFO_Count from accumulating more than TH7 in a long period of time, causing GPSS to be misactivated.

[0128] Step S513, set the ultra low frequency oscillation counter SLFO_Count to 0, and jump to step S2.

[0129] At this point, the judgment of the ultra-low frequency oscillation condition is completed.

[0130] Step S6, set the ultra-low frequency oscillation flag to 1, and return to step S2.

[0131] It should be noted that after the ultra-low frequency oscillation condition is met, the ultra-low frequency oscillation flag SLFO_FLAG is set to 1, and the process returns to step S2. In one embodiment, in order to avoid that a single set of GPSS parameters may not be able to adapt to the entire ultra-low frequency oscillation frequency band (0.01Hz to 0.1Hz), two sets of GPSS control parameters can be built into GPSS. After the ultra-low frequency oscillation condition is met, the following steps are performed:

[0132] S61, judging whether the parameter switching condition is met according to the oscillation frequency, if so, jumping to step S62, otherwise, jumping to step S63;

[0133] S62, switch GPSS control link parameters, and jump to step S63;

[0134] S63, set the ultra-low frequency oscillation flag to 1, and return to step S2.

[0135] Step S7, add the oscillation analysis sliding step length to the current time mark and the oscillation mode online identification timer, and return to step S3.

[0136] It should be noted that if the result of the Prony analysis of the frequency sampling data obtained in step S4 does not meet the ultra-low frequency oscillation condition, the current time identifier T and the oscillation mode online identification timer TIME_Count are both added with the oscillation analysis sliding step TI, and the process returns to step S3, thereby realizing the sliding time window online Prony analysis.

[0137] Step S8: Activate the GPSS function, perform the initialization of the second parameter, and jump to Step S9. The second parameter includes the GPSS continuous action timer and the GPSS output dead zone counter.

[0138] It should be noted that the second parameter needs to be initialized before activating the GPSS function. The information of the second parameter is shown in Table 3.

[0139] Table 3

[0140] Parameter Type Unit Description Initial value GPSS_Count Integer type - GPSS continuous action timer GPSS_Count ZERO_Count Integer type - GPSS output dead zone counter ZERO_Count

[0141] Step S9: Taking the current time as the base point, sample the GPSS output data for a time period that is half of the preset analysis time window length in the past.

[0142] It should be noted that after the initialization of the second parameter, taking the current time as the base point, sample the GPSS output data for the TW / 2 time period.

[0143] Step S10: Determine whether the GPSS output data sampling meets the GPSS exit condition based on the GPSS output data sampling. If so, jump to Step S12; otherwise, jump to Step S11.

[0144] It should be noted that the main parameters of the GPSS exit condition are shown in Table 4 in detail.

[0145] Table 4

[0146] Parameter Type Unit Description TH9 Floating point type p.u. GPSS exit limiting coefficient TH10 Floating point type ％ GPSS output limit value TH11 Floating point type ％ GPSS stop dead zone TH12 Integer type s GPSS maximum action time

[0147] As Figure 4 shown, the specific execution process of Step S10 in the embodiment of the present invention is as follows:

[0148] Step S101: Calculate the average value of positive values and the average value of negative values in the GPSS output data sampling respectively. Take the one with the larger absolute value among the average value of positive values and the average value of negative values as the target average value, denoted as Mean, and then jump to execute Step S102;

[0149] Step S102: Determine whether the absolute value of the target average value Mean meets the condition of being greater than the GPSS stop dead zone × the GPSS maximum action time, that is, whether the absolute value of Mean is greater than TH9 × TH10. If so, jump to Step S12; otherwise, jump to Step S103. This step can prevent the GPSS output from continuously exceeding the limit amplitude.

[0150] Step S103: Calculate the maximum value and the minimum value of the GPSS output data sampling respectively, denoted as Max and Min, and then jump to Step S104.

[0151] Step S104: Determine whether the absolute value of the maximum value of the GPSS output quantity sampling data is less than the GPSS stop dead zone, and whether the absolute value of the minimum value of the GPSS output quantity sampling data is less than the GPSS stop dead zone, that is, whether |Max| < TH11 and |Min| < TH11 are satisfied. If so, it is determined that the GPSS output is approximately 0 and has entered the dead zone, and jump to step S107; otherwise, jump to step S105.

[0152] Step S105: Increment the current time identifier T by 1, increment the GPSS continuous action timer GPSS_Count by 1, and jump to step S106.

[0153] Step S106: Determine whether the GPSS continuous action timer GPSS_Count is greater than the GPSS maximum action time TH12. If so, jump to step S12; otherwise, jump to step S9. This step setting can avoid the negative impact on the unit caused by the long-term operation of GPSS.

[0154] Step S107: Increment the GPSS output dead zone counter ZERO_Count by 1, and jump to step S108.

[0155] Step S108: Determine whether the GPSS output dead zone counter ZERO_Count is greater than half of the past preset analysis time window length, that is, TW / 2. If so, jump to step S12; otherwise, jump to step S105.

[0156] So far, the judgment on whether GPSS meets the exit condition is completed.

[0157] Step S11: Increment the current time identifier by 1, increment the GPSS continuous action timer by 1, and return to step S9.

[0158] It should be noted that if the result of step S10 does not meet the GPSS exit condition, the current time identifier is incremented by 1, the GPSS continuous action timer is incremented by 1, and return to step S9.

[0159] Step S12: Exit the GPSS function and return to step S1.

[0160] It should be noted that if the result of step S10 meets the GPSS exit condition, the GPSS function is exited and return to step S1.

[0161] The GPSS automatic switching-on and -off method based on online identification of oscillation modes provided by the present invention, after initializing the parameters for online identification of oscillation modes, detects whether the ultra-low frequency oscillation flag is 1. If it is not 1, it takes the frequency sampling data of the preset time window length for online identification of oscillation modes until the ultra-low frequency oscillation condition is met, then sets the ultra-low frequency oscillation flag to 1. When the ultra-low frequency oscillation flag is 1, it switches on the GPSS function, and when the GPSS exit condition is met, it switches off the GPSS function, realizing the targeted automatic switching-on and -off of the GPSS function, avoiding the problem of frequent operation of the oil pump that may be caused by long-term activation of the GPSS, and at the same time ensuring that the GPSS operates within the set effective frequency band of ultra-low frequency oscillation, avoiding negative impacts of the GPSS on oscillations in other frequency bands.

[0162] Meanwhile, two sets of GPSS control parameters are configured in the GPSS, and the GPSS parameters can be automatically switched according to the results of ultra-low frequency oscillation analysis to better adapt to the entire ultra-low frequency oscillation frequency band.

[0163] For the sake of easy understanding, an embodiment of a GPSS automatic switching-on and -off device based on online identification of oscillation modes is provided in the present invention, including a control module;

[0164] The control module is used to execute the following steps:

[0165] S1. Initialize the first parameters for online identification of the GPSS oscillation mode. The first parameters include the current time flag, the ultra-low frequency oscillation flag, the ultra-low frequency oscillation counter, and the online identification timer for oscillation modes;

[0166] S2. Detect whether the ultra-low frequency oscillation flag is 1. If it is, jump to step S8; otherwise, jump to step S3;

[0167] S3. Taking the current time as the base point, obtain the frequency sampling data of the past preset analysis time window length period;

[0168] S4. Conduct online identification of the oscillation mode for the frequency sampling data of the past preset analysis time window length period;

[0169] S5. Judge whether the ultra-low frequency oscillation condition is met according to the online identification result of the oscillation mode. If it is, jump to step S6; otherwise, jump to step S7;

[0170] S6. Set the ultra-low frequency oscillation flag to 1 and return to step S2;

[0171] S7. Add the oscillation analysis sliding step size to both the current time flag and the online identification timer for oscillation modes, and return to step S3;

[0172] S8. Activate the GPSS function, perform the initialization of the second parameter, and jump to step S9. The second parameter includes the GPSS continuous action timer and the GPSS output dead zone counter;

[0173] S9. Taking the current time as the base point, sample the GPSS output data for the time period that is half of the preset analysis time window length in the past;

[0174] S10. Determine whether the GPSS exit condition is met based on the sampled GPSS output data. If so, jump to step S12; otherwise, jump to step S11;

[0175] S11. Increment the current time identifier by 1 and increment the GPSS continuous action timer by 1, then return to step S9;

[0176] S12. Exit the GPSS function and return to step S1.

[0177] Step S10 specifically includes:

[0178] S101. Calculate the average value of the positive values and the average value of the negative values in the sampled GPSS output data respectively, and take the one with the larger absolute value as the target average value;

[0179] S102. Determine whether the absolute value of the target average value meets the condition of being greater than the GPSS stop dead zone × the GPSS maximum action time. If so, jump to step S12; otherwise, jump to step S103;

[0180] S103. Calculate the maximum value and the minimum value of the sampled GPSS output data respectively, and then jump to step S104;

[0181] S104. Determine whether the absolute value of the maximum value of the sampled GPSS output data is less than the GPSS stop dead zone and whether the absolute value of the minimum value of the sampled GPSS output data is less than the GPSS stop dead zone. If so, it is judged that the GPSS output is approximately 0 and has entered the dead zone, then jump to step S107; otherwise, jump to step S105;

[0182] S105. Increment the current time identifier by 1 and increment the GPSS continuous action timer by 1, and then jump to step S106;

[0183] S106. Determine whether the GPSS continuous action timer is greater than the GPSS maximum action time. If so, jump to step S12; otherwise, jump to step S9;

[0184] S107. Increment the GPSS output dead zone counter by 1, and then jump to step S108;

[0185] S108. Determine whether the dead zone counter output by the GPS is greater than half of the length of the past preset analysis time window. If so, jump to step S12; otherwise, jump to step S105.

[0186] In step S4, the Prony analysis method is used to perform online identification of oscillation modes for the frequency sampling data in the past preset analysis time window period.

[0187] Step S5 includes:

[0188] S51. Denote the peak-to-peak value of the frequency sampling data in the time window [T - TW, T] as PPV, where T is the current time identifier and TW is the length of the preset analysis time window;

[0189] S52. Determine whether PPV is greater than twice the frequency oscillation dead zone. If so, jump to step S53; otherwise, jump to step S511;

[0190] S53. Screen out the modes whose amplitude results in the online identification of oscillation modes are greater than TH2 × PPV / 2 and rank among the top TH3, where TH2 is the minimum amplitude of the mode and TH3 is the upper limit of the number of modes;

[0191] S54. Determine whether there is a mode among the screened modes whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency. If so, jump to step S55; if not, jump to step S511;

[0192] S55. Determine whether the damping ratio of the mode whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency is less than the mode damping ratio threshold. If so, jump to step S56; otherwise, jump to step S511;

[0193] S56. Increment the ultra-low frequency oscillation counter by 1 and jump to step S57;

[0194] S57. Determine whether the ultra-low frequency oscillation counter changes from 0 to 1. If so, jump to step S510; otherwise, jump to step S58;

[0195] S58. Determine whether the ultra-low frequency oscillation counter is greater than the oscillation times threshold. If so, jump to step S59; otherwise, jump to step S511;

[0196] S59. Set the ultra-low frequency oscillation flag to 1 and jump to step S2;

[0197] S510. Set the online identification timer of the oscillation mode to 0 and jump to step S511;

[0198] S511. Add the oscillation analysis sliding step to the current time identifier and add the oscillation analysis sliding step to the online identification timer of the oscillation mode, and then jump to step S512;

[0199] S512. Determine whether the online identification timer for the oscillation mode is greater than the maximum time for resetting to zero. If so, jump to step S513; otherwise, jump to step S2.

[0200] S513. Set the ultra-low frequency oscillation counter to 0 and jump to step S2.

[0201] Step S6 specifically includes:

[0202] S61. Determine whether the parameter switching condition is satisfied according to the oscillation frequency. If so, jump to step S62; otherwise, jump to step S63.

[0203] S62. Switch the parameters of the GPSS control link and jump to step S63.

[0204] S63. Set the ultra-low frequency oscillation flag to 1 and return to step S2.

[0205] The GPSS automatic switching-on and switching-off device based on online identification of oscillation mode provided by the present invention is used to execute the GPSS automatic switching-on and switching-off method based on online identification of oscillation mode provided by the present invention. Its principle and the obtained technical effects are the same as those of the GPSS automatic switching-on and switching-off method based on online identification of oscillation mode provided by the present invention, and will not be elaborated here.

[0206] As mentioned above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An automatic switching-on and switching-off method for GPSS based on online identification of oscillation modes, characterized in that It includes the following steps: S1. Initialize the first parameter for online identification of the GPSS oscillation mode. The first parameter includes the current time identifier, the ultra-low frequency oscillation identifier, the ultra-low frequency oscillation counter, and the online identification timer for the oscillation mode; S2. Detect whether the ultra-low frequency oscillation identifier is 1. If it is, jump to step S8; otherwise, jump to step S3; S3. Taking the current time as the base point, obtain the frequency sampling data for the preset analysis time window length period in the past; S4. Conduct online identification of the oscillation mode for the frequency sampling data in the preset analysis time window length period in the past; S5. Judge whether the ultra-low frequency oscillation condition is met according to the online identification result of the oscillation mode. If it is, jump to step S6; otherwise, jump to step S7; S6. Set the ultra-low frequency oscillation identifier to 1 and return to step S2; S7. Add the oscillation analysis sliding step length to both the current time identifier and the online identification timer for the oscillation mode, and return to step S3; S8. Activate the GPSS function, perform initialization of the second parameter, and jump to step S9. The second parameter includes the GPSS continuous action timer and the GPSS output dead zone counter; S9. Taking the current time as the base point, obtain the GPSS output quantity sampling data for the period that is half of the preset analysis time window length in the past; S10. Judge whether the GPSS exit condition is met according to the GPSS output quantity sampling data. If it is, jump to step S12; otherwise, jump to step S11; S11. Increment the current time identifier by 1 and increment the GPSS continuous action timer by 1, and return to step S9; S12. Exit the GPSS function and return to step S1.

2. The GPSS automatic switching-on and switching-off method based on online identification of oscillation mode according to claim 1, wherein Step S10 specifically includes: S101. Calculate the average value of positive values and the average value of negative values in the GPSS output quantity sampling data respectively, and take the one with the larger absolute value among the average value of positive values and the average value of negative values as the target average value; S102. Determine whether the absolute value of the target average value meets the condition of being greater than the GPSS stop dead zone × the GPSS maximum action time. If it is, jump to step S12; otherwise, jump to step S103; S103. Calculate the maximum value and the minimum value of the GPSS output quantity sampling data respectively, and jump to step S104; S104. Determine whether the absolute value of the maximum value of the GPSS output quantity sampling data is less than the GPSS stop dead zone, and whether the absolute value of the minimum value of the GPSS output quantity sampling data is less than the GPSS stop dead zone. If it is, judge that the GPSS output is approximately 0 and has entered the dead zone, and jump to step S107; otherwise, jump to step S105; S105. Increment the current time identifier by 1 and increment the GPSS continuous action timer by 1, and jump to step S106; S106. Determine whether the GPSS continuous action timer is greater than the GPSS maximum action time. If it is, jump to step S12; otherwise, jump to step S9; S107. Increment the GPSS output dead zone counter by 1 and jump to step S108; S108. Determine whether the dead zone counter output by GPSS is greater than half of the length of the past preset analysis time window. If so, jump to step S12; otherwise, jump to step S105.

3. The automatic switching-on and switching-off method of GPSS based on online identification of oscillation mode according to claim 1, characterized in that In step S4, the Prony analysis method is used to perform online identification of oscillation modes on the frequency sampling data in the past preset analysis time window length period.

4. The automatic switching-on and switching-off method of GPSS based on online identification of oscillation mode according to claim 3, characterized in that, Step S5 includes: S51. Denote the peak-to-peak value of the frequency sampling data in the time window [T - TW, T] as PPV, where T is the current time identifier and TW is the preset analysis time window length. S52. Determine whether PPV is greater than twice the frequency oscillation dead zone. If so, jump to step S53; otherwise, jump to step S511. S53. Screen out the modes whose amplitude results in the online identification of oscillation modes are greater than TH2×PPV / 2 and rank among the top TH3, where TH2 is the minimum amplitude of the mode and TH3 is the upper limit of the number of modes. S54. Determine whether there is a mode among the screened modes whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency. If so, jump to step S55; if not, jump to step S511. S55. Determine whether the damping ratio of the mode whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency is less than the mode damping ratio threshold. If so, jump to step S56; otherwise, jump to step S511. S56. Increment the ultra-low frequency oscillation counter by 1 and jump to step S57. S57. Determine whether the ultra-low frequency oscillation counter changes from 0 to 1. If so, jump to step S510; otherwise, jump to step S58. S58. Determine whether the ultra-low frequency oscillation counter is greater than the oscillation times threshold. If so, jump to step S59; otherwise, jump to step S511. S59. Set the ultra-low frequency oscillation flag to 1 and jump to step S2. S510. Set the online identification timer of the oscillation mode to 0 and jump to step S511. S511. Add the oscillation analysis sliding step to the current time identifier and add the oscillation analysis sliding step to the online identification timer of the oscillation mode, and jump to step S512. S512. Determine whether the online identification timer of the oscillation mode is greater than the maximum time to return to zero. If so, jump to step S513; otherwise, jump to step S2. S513. Set the ultra-low frequency oscillation counter to 0 and jump to step S2.

5. A GPSS automatic switching-on and switching-off method based on online identification of oscillation modes according to claim 1, characterized in that Step S6 specifically includes: S61. Determine whether the parameter switching condition is satisfied according to the oscillation frequency. If so, jump to step S62; otherwise, jump to step S63. S62. Switch the parameters of the GPSS control link and jump to step S63. S63. Set the ultra-low frequency oscillation flag to 1 and return to step S2.

6. A GPSS automatic switching device based on online identification of oscillation modes, characterized in that, It includes a control module; The control module is used to execute the following steps: S1. Initialize the first parameters for the online identification of the GPSS oscillation mode. The first parameters include the current time identifier, the ultra-low frequency oscillation flag, the ultra-low frequency oscillation counter, and the online identification timer of the oscillation mode. S2. Detect whether the ultra-low frequency oscillation flag is 1. If so, jump to step S8; otherwise, jump to step S3. S3. Taking the current time as the base point, obtain the frequency sampling data for the past preset analysis time window length period; S4. Conduct online identification of the oscillation mode for the frequency sampling data of the past preset analysis time window length period; S5. Determine whether the ultra-low frequency oscillation condition is satisfied according to the online identification result of the oscillation mode. If so, jump to step S6; otherwise, jump to step S7; S6. Set the ultra-low frequency oscillation flag to 1 and return to step S2; S7. Increment both the current time flag and the online identification timer of the oscillation mode by the oscillation analysis sliding step length, and return to step S3; S8. Activate the GPSS function, perform initialization of the second parameters, and jump to step S9. The second parameters include the GPSS continuous action timer and the GPSS output dead zone counter; S9. Taking the current time as the base point, obtain the GPSS output quantity sampling data for the past half of the preset analysis time window length period; S10. Determine whether the GPSS exit condition is satisfied according to the GPSS output quantity sampling data. If so, jump to step S12; otherwise, jump to step S11; S11. Increment the current time flag by 1 and increment the GPSS continuous action timer by 1, and return to step S9; S12. Exit the GPSS function and return to step S1.

7. An automatic switching-in and switching-out device for GPSS based on online identification of oscillation modes according to claim 6, characterized in that Step S10 specifically includes: S101. Calculate the average value of the positive values and the average value of the negative values in the GPSS output quantity sampling data respectively, and take the one with the larger absolute value of the average value of the positive values and the average value of the negative values as the target average value; S102. Determine whether the absolute value of the target average value satisfies the condition of being greater than the GPSS stop dead zone × the GPSS maximum action time. If so, jump to step S12; otherwise, jump to step S103; S103. Calculate the maximum value and the minimum value of the GPSS output quantity sampling data respectively, and jump to step S104; S104. Determine whether the absolute value of the maximum value of the GPSS output quantity sampling data is less than the GPSS stop dead zone, and whether the absolute value of the minimum value of the GPSS output quantity sampling data is less than the GPSS stop dead zone. If so, it is judged that the GPSS output is approximately 0 and has entered the dead zone, and jump to step S107; otherwise, jump to step S105; S105. Increment the current time flag by 1 and increment the GPSS continuous action timer by 1, and jump to step S106; S106. Determine whether the GPSS continuous action timer is greater than the GPSS maximum action time. If so, jump to step S12; otherwise, jump to step S9; S107. Increment the GPSS output dead zone counter by 1 and jump to step S108; S108. Determine whether the GPSS output dead zone counter is greater than half of the past preset analysis time window length. If so, jump to step S12; otherwise, jump to step S105.

8. The GPSS automatic switching device based on online identification of oscillation mode according to claim 6, characterized in that In step S4, the Prony analysis method is used to conduct online identification of the oscillation mode for the frequency sampling data of the past preset analysis time window length period.

9. The GPSS automatic switching device based on online identification of oscillation mode according to claim 8, characterized in that, Step S5 includes: S51. Denote the peak-to-peak value of the frequency sampling data in the time window [T - TW, T] as PPV, where T is the current time identifier and TW is the preset analysis time window length; S52. Determine whether PPV is greater than twice the frequency oscillation dead zone. If so, jump to step S53; otherwise, jump to step S511; S53. Screen out the modes whose amplitude results in the online identification of oscillation modes are greater than TH2×PPV / 2 and rank among the top TH3, where TH2 is the minimum amplitude of the mode and TH3 is the upper limit of the number of modes; S54. Determine whether there is a mode among the screened modes whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency. If so, jump to step S55; if not, jump to step S511; S55. Determine whether the damping ratio of the mode whose frequency is within the range of the lower limit of the mode frequency to the upper limit of the mode frequency is less than the mode damping ratio threshold. If so, jump to step S56; otherwise, jump to step S511; S56. Increment the ultra-low frequency oscillation counter by 1 and jump to step S57; S57. Determine whether the ultra-low frequency oscillation counter changes from 0 to 1. If so, jump to step S510; otherwise, jump to step S58; S58. Determine whether the ultra-low frequency oscillation counter is greater than the oscillation times threshold. If so, jump to step S59; otherwise, jump to step S511; S59. Set the ultra-low frequency oscillation flag to 1 and jump to step S2; S510. Set the online identification timer of the oscillation mode to 0 and jump to step S511; S511. Add the oscillation analysis sliding step to the current time identifier and add the oscillation analysis sliding step to the online identification timer of the oscillation mode, and jump to step S512; S512. Determine whether the online identification timer of the oscillation mode is greater than the maximum time for resetting to zero. If so, jump to step S513; otherwise, jump to step S2; S513. Set the ultra-low frequency oscillation counter to 0 and jump to step S2.

10. The GPSS automatic switching device based on online identification of oscillation mode according to claim 6, characterized in that, Step S6 specifically includes: S61. Determine whether the parameter switching condition is satisfied according to the oscillation frequency. If so, jump to step S62; otherwise, jump to step S63; S62. Switch the parameters of the GPSS control link and jump to step S63; S63. Set the ultra-low frequency oscillation flag to 1 and return to step S2.

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