An electric energy information measurement method and device, computer equipment and storage medium

Abstract

The application relates to an electric energy information measurement method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a variable-frequency low-frequency electric signal of an industrial motor in a predetermined period to obtain an initial time sequence electric signal; performing low-pass filtering on the initial time sequence electric signal by using a digital filter to obtain a first time sequence electric signal; performing filtering processing on the first time sequence signal by using an adaptive filter to obtain a second time sequence electric signal; and determining a signal instantaneous frequency of a target signal cycle in the predetermined period according to the second time sequence signal. The measurement scheme can realize online design of the digital filter, has a wide frequency measurement range and high frequency measurement accuracy, lays a foundation for measurement of other electrical quantities, meets the accuracy requirement of a power system on a measurement device, can measure electrical quantities of a high-harmonic variable-frequency low-frequency signal, and is fast, accurate and effective in electrical quantity measurement, and meets the accuracy requirement of the power system on the measurement device.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of motor electric energy monitoring, and in particular to an electric energy information measurement method and device, computer equipment and a storage medium. BACKGROUND

[0002] In some industrial motors, the electric signals generated by the motor usually have the characteristics of frequency conversion and low frequency. At present, for the measurement of the electric signals of frequency conversion and low frequency, the frequency conversion and low frequency electric signals are first converted into square waves through a shaping circuit, and then the time interval of the adjacent rising edges or falling edges of the square waves is obtained to calculate the frequency signal, so as to monitor the electric energy information of the key measurement point in real time.

[0003] However, in the actual operation process of industrial motors, the frequency conversion and low frequency electric signals often contain a large amount of harmonics. For example, in a permanent magnet direct drive wind power generation system, the intermittency of wind power and the power quality of the power grid bring great challenges to the normal operation of the wind turbine, resulting in a large amount of harmonics in the low frequency signal of the wind turbine, causing fluctuations around the zero-crossing point, i.e. multiple zero-crossing points around the zero-crossing point, so that the measurement error of the frequency is large, thereby affecting the accuracy of the electric energy information of the subsequent current, voltage and power signals. SUMMARY

[0004] Therefore, it is necessary to provide an electric energy information measurement method and device, computer equipment and a storage medium capable of reducing error and improving accuracy in view of the above technical problems.

[0005] In a first aspect, the present application provides an electric energy information measurement method. The method comprises:

[0006] obtaining a frequency conversion and low frequency electric signal of an industrial motor in a predetermined period to obtain an initial time sequence electric signal;

[0007] performing low-pass filtering on the initial time sequence electric signal by using a digital filter to obtain a first time sequence electric signal;

[0008] performing filtering processing on the first time sequence signal by using an adaptive filter to obtain a second time sequence electric signal;

[0009] determining a signal instantaneous frequency of a target signal cycle in the predetermined period according to the second time sequence signal.

[0010] In one embodiment, the method further comprises:

[0011] The digital filter is an IIR digital filter, and before the low-pass filtering on the initial time sequence electric signal by using the digital filter to obtain the first time sequence electric signal, the method comprises:

[0012] acquire a sampling period, a sampling requirement and a signal characteristic of the initial time-series electrical signal;

[0013] determine an index parameter of the digital filter according to the sampling period, the sampling requirement, the signal characteristic and a processing performance of the IIR digital filter, wherein the index parameter comprises an order, a passband cutoff frequency, a shear frequency and a stopband cutoff frequency;

[0014] determine a discrete transfer function of the IIR digital filter according to the index parameter, wherein the discrete transfer function is used for low-pass filtering the initial time-series electrical signal.

[0015] In one of the embodiments, the step of determining a signal instantaneous frequency of a target signal period within the predetermined period according to the second time-series electrical signal comprises:

[0016] determining three adjacent signal zero-crossing points in time sequence according to the electrical signal values of the sampling points in the second time-series signal, wherein the three adjacent signal zero-crossing points in time sequence comprise a first signal zero-crossing point, a second signal zero-crossing point and a third signal zero-crossing point in ascending order of time; the first signal zero-crossing point and the third signal zero-crossing point are used for representing a start point and an end point of the target signal period;

[0017] determining a time of the first signal zero-crossing point according to the two adjacent sampling points before and after the first signal zero-crossing point, and determining a time of the third signal zero-crossing point according to the two adjacent sampling points before and after the third signal zero-crossing point;

[0018] acquiring a number of sampling points of the target signal period according to the time of the first signal zero-crossing point, the time of the third signal zero-crossing point and a sampling period of the second time-series signal;

[0019] obtaining a signal instantaneous frequency of the target signal period according to a sampling frequency of the second time-series signal and the number of sampling points.

[0020] In one of the embodiments, the step of determining a time of the first signal zero-crossing point according to the two adjacent sampling points before and after the first signal zero-crossing point, and determining a time of the third signal zero-crossing point according to the two adjacent sampling points before and after the third signal zero-crossing point adopts a least square method to perform linear fitting, so as to obtain the time of the first signal zero-crossing point and the time of the third signal zero-crossing point.

[0021] In one of the embodiments, the step of determining three adjacent signal zero-crossing points in time sequence according to the electrical signal values of the sampling points in the second time-series signal comprises:

[0022] comparing, in sequence, whether the electrical signal values of the two adjacent sampling points are of the same sign;

[0023] If the signs of the electrical signal values of the two adjacent sampling points are opposite, it is determined whether it is a noise point according to a preset noise threshold value;

[0024] If it is not a noise point, it is determined that there is a signal zero-crossing point between the two adjacent sampling points.

[0025] In one of the embodiments, the method further comprises determining a full-wave effective value, a full-wave apparent power, a full-wave active power and a full-wave reactive power in combination with the number of sampling points of the target signal period and the electrical signal values of the target signal period.

[0026] In one of the embodiments, the filtering processing of the first time sequence signal by the adaptive filter to obtain the second time sequence signal comprises:

[0027] obtaining a difference value between the initial time sequence electrical signal and the first time sequence electrical signal;

[0028] optimizing parameters of the adaptive filter according to the difference value;

[0029] filtering processing of the first time sequence signal by the adaptive filter to obtain the second time sequence signal.

[0030] In a second aspect, the present application further provides an electric energy information measuring device. The device comprises:

[0031] an acquisition module for acquiring a variable-frequency low-frequency electrical signal of an industrial motor in a predetermined period to obtain an initial time sequence electrical signal;

[0032] a first filtering module for filtering the initial time sequence electrical signal by a digital filter to obtain a first time sequence electrical signal;

[0033] a second filtering module for filtering processing of the first time sequence signal by an adaptive filter to obtain a second time sequence electrical signal;

[0034] a frequency determination module for determining a signal instantaneous frequency of a target signal period in the predetermined period according to the second time sequence signal.

[0035] In a third aspect, the present application further provides a computer device. The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the electric energy information measuring method provided by the first aspect of the present application when executing the computer program.

[0036] In a fourth aspect, the present application further provides a computer readable storage medium. The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the electric energy information measuring method provided by the first aspect of the present application.

[0037] In a fifth aspect, the present application provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the power information measurement method according to the first aspect of the present application.

[0038] The power information measurement method, device, computer device and storage medium described above, by obtaining a variable-frequency low-frequency electrical signal of an industrial motor in a predetermined period, obtaining an initial time sequence electrical signal, performing low-pass filtering on the initial time sequence electrical signal by using a digital filter to obtain a first time sequence electrical signal, performing filtering processing on the first time sequence signal by using an adaptive filter to obtain a second time sequence electrical signal, and determining a signal instantaneous frequency of a target signal cycle in the predetermined period according to the second time sequence electrical signal, the measurement scheme can realize online design of the digital filter, has a wide frequency measurement range and high frequency measurement accuracy, lays a foundation for measurement of other electrical quantities, meets the accuracy requirement of a power system on a measurement device, can measure electrical quantities of a high-harmonic variable-frequency low-frequency signal, and meets the accuracy requirement of the power system on the measurement device. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 An application environment diagram of the power information measurement method in an embodiment;

[0040] Figure 2 A flowchart of the power information measurement method in an embodiment;

[0041] Figure 3 A schematic diagram of a phase voltage waveform before shutdown in an embodiment;

[0042] Figure 4 A schematic diagram of a phase voltage waveform during shutdown in an embodiment;

[0043] Figure 5 A schematic diagram of a phase voltage waveform after shutdown in an embodiment;

[0044] Figure 6 A schematic diagram of a comparison before and after filtering of a 5Hz signal phase voltage in an embodiment;

[0045] Figure 7 A schematic diagram of a comparison before and after filtering of a 10Hz signal phase voltage in an embodiment;

[0046] Figure 8 A structural block diagram of the power information measurement device in an embodiment;

[0047] Figure 9 An internal structure diagram of the computer device in an embodiment. DETAILED DESCRIPTION

[0048] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not intended to limit the present application.

[0049] The electric energy information measuring method provided by the embodiments of the present application can be applied in an application environment as shown in Figure 1 The terminal 102 communicates with the server 104 through a network. The data storage system can store data required to be processed by the server 104. The data storage system can be integrated on the server 104, or placed on a cloud or other network server. The data storage system can be used to store the variable-frequency low-frequency electric signals of the industrial motor collected in real time. The terminal 102 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart sound boxes, smart televisions, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0050] In one embodiment, as shown in Figure 2 , an electric energy information measuring method is provided. Taking the server in Figure 1 as an example, the method comprises the following steps:

[0051] Step 201: Obtain the variable-frequency low-frequency electric signals of the industrial motor in a predetermined period to obtain an initial time-series electric signal.

[0052] The predetermined period can refer to a predetermined period with the start of electric energy information measurement as the starting point, or the predetermined period can also refer to a predetermined period before the current time in the process of collecting the variable-frequency low-frequency electric signals of the industrial motor in real time.

[0053] The embodiments of the present application obtain the variable-frequency low-frequency electric signals of the industrial motor collected in a predetermined period to obtain an initial time-series electric signal. The initial time-series electric signal comprises the sampling time of each sampling point and the initial electric signal value corresponding to the sampling time.

[0054] Step 202: Perform low-pass filtering on the initial time-series electric signal by using a digital filter to obtain a first time-series electric signal.

[0055] For the variable-frequency low-frequency electric signal containing high harmonics, the embodiments of the present application perform low-pass filtering on the initial time-series electric signal through the design and implementation of the digital filter.

[0056] In an implementation, the digital filter can be an IIR digital filter, and the parameter design of the IIR digital filter can adopt an online calculation method or a lookup table method.

[0057] For example, the embodiment of the present application can acquire a sampling period, sampling requirement and signal characteristic of an initial time sequence electrical signal, determine index parameters of a digital filter in combination with the sampling period, sampling requirement and signal characteristic and processing performance of the IIR digital filter, wherein the index parameters include order, passband cutoff frequency, shear frequency and stopband cutoff frequency, etc., determine a discrete transfer function of the IIR digital filter according to the index parameters, and the discrete transfer function is used for low-pass filtering of the initial time sequence electrical signal.

[0058] For example, it is assumed that the initial electrical signal output characteristic includes a PWM wave of a voltage signal, a voltage harmonic content between 80% and 120%, a current harmonic content between 2% and 7%, and a frequency fluctuating between 4 Hz and 11 Hz, and an IIR digital filter signal frequency range of 5 Hz to 15 Hz can be designed. Table 1 is an attenuation rate of a 25 Hz signal under different shear frequencies, and the preset cutoff frequency is 80 Hz by comprehensively considering the signal attenuation rate and filtering effect.

[0059] Table 1 Comparison of attenuation rates of 25 Hz signals under different shear frequencies

[0060] Shear frequency 60 Hz 70 Hz 80 Hz 90 Hz 100 Hz 25 Hz signal decay rate 1.5％ 0.8％ 0.47％ 0.30％ 0.18％

[0061] The core chip of the measuring device is ADSP-21489, and the filter index designed according to the performance of the reference control chip is shown in Table 2:

[0062] Table 2 Filter design index

[0063]

[0064] The designed digital filter is converted into a discrete equation, and a bilinear transformation method is adopted. When the index of the filter is given, the discrete transfer function of the filter is as follows:

[0065]

[0066] Similarly, the discrete equation of a three-order low-pass digital filter is as follows:

[0067] H3(z) = H 31 (z)·H 32 (z);

[0068] Wherein:

[0069]

[0070] Similarly, the discrete equation of a four-order filter is as follows:

[0071] H4(z) = H 41 (z) · H 42 (z) ;

[0072] wherein:

[0073]

[0074]

[0075] The parameter design of the filter can adopt an online calculation method or a table lookup method in the application process with reference to the program calculation time, and the online calculation method is adopted above.

[0076] In step 203, the first time sequence electrical signal is filtered by using the adaptive filter to obtain a second time sequence electrical signal.

[0077] The adaptive filter refers to a filter capable of automatically adjusting the filtering characteristic, and can automatically adjust the coefficient of the filter according to the real-time change of the input signal to achieve the optimal filtering effect. Common adaptive filter algorithms include a least mean square (LMS) method, a least mean square error (LMS) method, an adaptive linear prediction (ALP) method and the like. The LMS method is the most commonly used algorithm, which adjusts the filter weight in the form of real-time updating of the mean square error, and also has the advantages of simplicity and easy implementation.

[0078] In the embodiment of the application, since the first time sequence electrical signal is obtained by low-pass filtering the initial time sequence electrical signal, it can be understood that the difference between the initial time sequence electrical signal and the first time sequence electrical signal has a positive correlation with the noise in the initial time sequence electrical signal, and the adaptive filter is used to filter the noise, so that the parameter of the adaptive filter can be adjusted according to the corresponding relationship between the noise and the difference.

[0079] Specifically, the difference between the initial time sequence electrical signal and the first time sequence electrical signal is obtained, the parameter of the adaptive filter is optimized according to the difference, and the first time sequence signal is filtered by using the optimized adaptive filter to obtain a second time sequence signal.

[0080] In an implementation manner, the model can be established in advance according to actual conditions, or historical sample data in actual operation can be obtained, including historical variable-frequency low-frequency electric signal sample data of the industrial motor, noise of the variable-frequency low-frequency electric signal sample data, historical first time sequence electric signal sample data obtained by low-pass filtering of the historical initial time sequence electric signal through the digital filter, and the corresponding relationship between the noise and the difference value is trained from the sample data set, so that in actual measurement, the noise is determined according to the difference value between the initial time sequence electric signal and the first time sequence electric signal, and the relationship between the noise and the parameters of the adaptive filter is preset, so that the parameters of the adaptive filter are optimized according to the noise.

[0081] It can be understood that the parameters of the adaptive filter are a process of continuous updating and optimization, the initial time sequence electric signal and the corresponding first time sequence electric signal in the time domain close to the current time can be obtained, the parameters are updated through the difference value in the time domain, and the parameters are continuously updated through the difference value in the next time domain.

[0082] In step 204, the signal instantaneous frequency of the target signal period in the predetermined period is determined according to the second time sequence electric signal.

[0083] In S2041, the first three adjacent signal zero-crossing points in time sequence are determined according to the electric signal values of the sampling points in the second time sequence signal.

[0084] The second time sequence signal can be the filtered electric signal obtained in real time from the start of the electric energy information measurement to the current time.

[0085] In the embodiment of the application, the first three adjacent signal zero-crossing points in the second time sequence signal are determined, and the first three adjacent signal zero-crossing points in time sequence include the first signal zero-crossing point, the second signal zero-crossing point and the third signal zero-crossing point in ascending order of time, and the first signal zero-crossing point and the third signal zero-crossing point are used to represent the starting point and the end point of the target signal period.

[0086] In an implementation manner, the electric signal values of the adjacent two sampling points can be compared in sequence, if the electric signal values of the adjacent two sampling points are opposite in sign, it is determined whether it is a noise point according to the preset noise threshold; if it is not a noise point, it is determined that there is a signal zero-crossing point between the adjacent two sampling points.

[0087] It can be understood that for the frequency measurement of the sine signal without bias voltage, the key is the detection of the voltage zero-crossing point. Assuming that the filtered signal is an ideal signal (such as a signal generated by a signal generator, which can be understood as a signal with little noise), the determination of the zero-crossing point is relatively simple, and it can be realized by determining the data point of the voltage reversal.

[0088] For example, the frequency measurement function compares the product of the current value and the value at the previous time with zero, and if it is less than zero, it is considered that there is a zero-crossing point between the two data. The voltage and current signals in the ADSP-21489 are floating-point type, and there is no case of being equal to zero.

[0089] S2042, the time of the first signal zero-crossing point is determined according to two adjacent sampling points before and after the first signal zero-crossing point, and the time of the third signal zero-crossing point is determined according to two adjacent sampling points before and after the third signal zero-crossing point.

[0090] Among them, the two adjacent sampling points before and after the first signal zero-crossing point refer to the adjacent sampling point before the first signal zero-crossing point and the adjacent sampling point after the first signal zero-crossing point.

[0091] It can be understood that the two adjacent sampling points before and after the first signal zero-crossing point are also continuous or adjacent.

[0092] The embodiment of the application determines the time of the first signal zero-crossing point and the time of the third signal zero-crossing point by using the least square method for linear fitting according to the sampling time of the two sampling points and the electrical signal value corresponding to the sampling time.

[0093] S2043, the sampling point number of the target signal period is obtained in combination with the first signal zero-crossing point, the third signal zero-crossing point, and the sampling period of the second time sequence signal.

[0094] Among them, the sampling period of the second time sequence signal can refer to the sampling period of the variable frequency low frequency electrical signal of the industrial motor, that is, the sampling period of the initial electrical signal.

[0095] In combination with the first signal zero-crossing point and the third signal zero-crossing point, the time of the target signal period, that is, the time of a complete period, is determined, and according to the time of the target signal period and the sampling period, the sampling point number of the target signal period can be obtained.

[0096] S2044, the signal instantaneous frequency of the target signal period is obtained in combination with the sampling frequency and the sampling point number of the second time sequence signal.

[0097] Among them, the signal instantaneous frequency of the target signal period can be the sampling frequency divided by the sampling point number.

[0098] After determining the sampling point number, the embodiment of the application can also determine the full-wave effective value, the full-wave apparent power, the full-wave active power, and the full-wave reactive power and other electrical energy information in combination with the sampling point number of the target signal period and the electrical signal value of the target signal period.

[0099] In one embodiment, an electrical energy information measurement method is provided, which is based on electronic technology.

[0100] Regarding the frequency signal measurement, the main feature of the industrial motor electric signal is low frequency and variable frequency, and the embodiment of the application can adopt the frequency measurement scheme based on the electronic counter. In order to improve the frequency measurement accuracy, the following four problems should be solved in the calculation, which are the determination of noise points, the initial value of frequency calculation, the elimination of noise signals and the data processing of zero-crossing points.

[0101] For the determination of noise points, the signal on the generator side of the wind power generation system is low frequency and variable frequency, and the frequency range is generally 4-11 Hz. Because of the large harmonic content, high frequency signal disturbance may occur near the zero-crossing point, which is the noise point described in the embodiment of the application. The noise signal is the main factor affecting the frequency measurement. First, a noise threshold is determined, which can be set according to the field situation. According to engineering experience, it is recommended to set the noise threshold frequency to about 10 times the test signal, and the value of the embodiment of the application can be set to 100 Hz. If the frequency is detected to be 100 Hz or more, it is considered that the point is a noise point, indicating that this frequency calculation is invalid, and the calculation result is marked as a noise point, so that the noise signal can be processed subsequently.

[0102] For the initial value of frequency calculation, in order to improve the calculation speed and adapt to the variable frequency test working condition, the initial value of the frequency needs to be accurately calculated. The first two zero-crossing points detected after the program starts are used to solve the initial value of the electronic counter and the initial value of the average value of the count in the half cycle. The frequency value, voltage effective value, current effective value and power value are output after two reserved periods.

[0103] Taking the A-phase voltage as an example, it is judged whether the current value and the previous value of the filtered A-phase voltage are the same in each sampling period. If they are the same, the electronic counter NFreCnt takes 0 as the initial value and increases by 1. If they are opposite, it should be first judged whether it is a noise point. If it is a noise point, the electronic counter NFreCnt continues to increase by 1, ignoring the zero-crossing point. If it is not a noise point, the initial value of the electronic counter is calculated.

[0104]

[0105] Among them, Ua and Ua- are the current value and the previous value of the filtered A-phase voltage, and there is a zero-crossing point between them. Based on the principle of least squares, a straight line is used to fit the zero-crossing point near the sine curve, and the zero-crossing point coordinates are obtained to calculate the measured frequency.

[0106] After determining the initial value of the electronic counter, the initial value of the counter in half a cycle is calculated based on the value. The judgment method is: in each sampling period, judge whether the current value and the previous value of the filtered A-phase voltage are the same in sign, if they are the same, the electronic counter is increased by 1 with the initial value of ΔUacnt, if they are opposite, it is judged whether it is a noise point, if it is a noise point, the zero-crossing point is ignored, NFreCnt continues to increase by 1, if it is not a noise point, the initial value of the counter in half a cycle is calculated, and the calculation formula is as follows:

[0107] N FreCntMean = N FreCnt + Δ' Uacnt ;

[0108]

[0109] Wherein, NFreCntMean represents the initial value of the counter in half a cycle, which can be converted into the initial value of frequency calculation, NFreCnt represents the value of the electronic counter with the initial value of Δ Uacnt .

[0110] For the elimination of noise signals, when there is a noise point, the electronic counter value corresponding to the noise point needs to be continuously accumulated. The specific implementation is that if the frequency is detected to be 100 Hz or more, the point is considered to be a noise signal, and the electronic counter value NFreCnt continues to increase by 1, otherwise, if the electronic counter value is greater than the noise threshold, it is considered to capture a reasonable zero-crossing point.

[0111] For the processing of the zero-crossing point value, after detecting the system zero-crossing point, the current data needs to be processed, and the electronic counter value is processed by sliding average, which is equivalent to a first-order filter link of the output frequency, effectively reducing the frequency fluctuation. Assuming that the sampling frequency is Fs, the output instantaneous frequency value in a cycle is:

[0112]

[0113] As to other electric energy information, the voltage signal has high harmonic content, and the phase voltage amplitude fluctuates between 0V and 700V during the starting and stopping of the unit. Only when the voltage amplitude is greater than a certain voltage amplitude threshold, the root mean square of the filtered current data can be used to calculate the full-wave effective value of the voltage based on the frequency of the voltage signal. The harmonic content of the loop current signal is low during normal operation, but during the starting and stopping of the unit, the current amplitude is low and the harmonic content is large. When the current amplitude is greater than a certain current amplitude threshold, the root mean square of the filtered current data can be used to calculate the full-wave effective value of the current based on the frequency of the current signal. The apparent power of the A, B and C three-phase can be the full-wave voltage effective value of each phase multiplied by the full-wave current effective value. The signal frequency calculation module can obtain the electronic counter count value in one cycle, which is a floating point type and helps to improve the accuracy of the full-wave active power. The full-wave active power value calculation formula is as follows:

[0114]

[0115] Wherein, N = 2 x NFreCntMean, the number of data sampling points in a single cycle; u n and i n are the instantaneous values of the voltage and current signals measured by the sensor.

[0116] According to the active power and the apparent power, the reactive power formula can be derived as follows:

[0117]

[0118] The sign of the reactive power is determined by the instantaneous reactive power value:

[0119]

[0120] Wherein, if Q>0, the sign of the reactive power is "+", and vice versa.

[0121] In another embodiment, to verify the filtering effect and measurement accuracy of the embodiments of the application, simulation and experimental verification will be described in detail below.

[0122] As to the filtering effect verification, the embodiments of the application use the measured data of a certain permanent magnet direct drive wind turbine to verify the control strategy. The unit capacity is 1.5MW, the test data is the measured data of the entire process from starting to stopping of the fan, the frequency variation range is 5Hz-12Hz, the designed sampling frequency is 12.8kHz, the digital filter cut-off frequency is designed as 80Hz, and the test data is imported into Matlab / Simulink for analysis. The test results are shown in Figure 3 、 Figure 4 、 Figure 5 、 Figure 6 ​

[0123] In Figure 3 , the lower is the phase voltage before filtering before shutdown, and the upper is the waveform after filtering; in Figure 4 , the lower is the phase voltage before filtering during shutdown, and the upper is the waveform after filtering; in Figure 5 , the lower is the phase voltage before filtering after shutdown, and the upper is the waveform after filtering; in Figure 6 , the lower is the phase voltage before filtering of the 5Hz signal, and the upper is the waveform after filtering; in Figure 7 , the lower is the phase voltage before filtering of the 10Hz signal, and the upper is the waveform after filtering.

[0124] It can be seen that the harmonic components in various operating conditions of the unit can be effectively filtered out by the filter, thereby providing a basis for the subsequent calculation of the frequency of the electrical quantity.

[0125] The influence of different sampling frequencies on the filtering effect is compared and analyzed, and the test data is imported into Matlab / Simulink for Fourier analysis, and the test results are shown in Table 3:

[0126] Table 3 Comparison of the influence of different sampling frequencies on the filtering effect

[0127]

[0128] It can be seen from Table 3 that the attenuation rate of the 25Hz signal mainly depends on the shear frequency of the filter, and the change of the sampling frequency has little effect on it; with the increase of the sampling frequency, the filtering effect can be effectively improved, but the specific sampling frequency setting needs to be comprehensively considered according to the processing capacity of the core chip and the measurement requirements.

[0129] Regarding the measurement accuracy verification, the standard signal generating device is used to input a 10.01Hz frequency given signal to verify the accuracy of the algorithm, and the test results are shown in Table 4:

[0130] Table 4 Filtering effect verification

[0131]

[0132]

[0133] It can be seen from Table 4 that in the high power segment, the electrical quantity measurement accuracy is within 0.5%; in the low power segment, the electrical quantity measurement accuracy is within 1.7%. The reason why the measurement accuracy is slightly low in the low power segment includes that the accuracy of the data recording software is relatively low, the power value does not contain decimal places, which will cause a certain deviation; the wind turbine generator set is in a nonlinear working state in the low power segment, and the voltage and current signals contain high harmonic components, and the control accuracy of the wind turbine generator set itself is also reduced, which causes a certain measurement error.

[0134] The feasibility of the algorithm is verified by importing the measured data of high harmonic low frequency into Matlab / Simulink for simulation, and an experimental platform based on ADSP-21489 is built to verify the measurement accuracy. The measurement scheme can realize online design of the digital filter, has wide frequency measurement range and high frequency measurement accuracy, lays a foundation for measurement of other electrical quantities, meets the accuracy requirements of the power system on the measuring device, can measure electrical quantities of high harmonic low frequency signals, and is fast, accurate and effective in electrical quantity measurement, and meets the accuracy requirements of the power system on the measuring device.

[0135] According to the relevant regulations of the power system, the new energy grid connection must have primary frequency modulation function, and the requirements of each regional power grid are slightly different. The system frequency accuracy requirement is 0.001 Hz, the test cycle is 100 ms, and the existing frequency test instrument has the problems of small measurement range, test accuracy and response speed not meeting the requirements, and high cost. The embodiment of the application meets the power grid test requirements through the design of the filter, can be used as a customized test instrument in the later period, or cooperate with the power station to complete software upgrading, and reduce the frequency transformation cost of the new energy field station. At the same time, the improvement of the frequency measurement speed can gain time for the active output response of the new energy.

[0136] It should be understood that, although each step in the flowchart involved in each of the above embodiments is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, at least part of the steps in the flowchart involved in each of the above embodiments can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least part of other steps or steps or stages in other steps.

[0137] Based on the same inventive concept, the embodiment of the application also provides an electric energy information measurement device for implementing the above-mentioned electric energy information measurement method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more electric energy information measurement device embodiments provided below can refer to the limitations of the electric energy information measurement method in the above text, which will not be repeated here.

[0138] In one embodiment, as Figure 7As shown in the figure, an electric energy information measuring device is provided, comprising: an acquisition signal module 801, a first filtering module 802, a second filtering module 803 and a frequency determination module 804, wherein:

[0139] The acquisition signal module 801 is configured to acquire a variable-frequency low-frequency electric signal of an industrial motor in a predetermined period to obtain an initial time sequence electric signal.

[0140] The first filtering module 802 is configured to perform low-pass filtering on the initial time sequence electric signal by using a digital filter to obtain a first time sequence electric signal.

[0141] The second filtering module 803 is configured to perform filtering processing on the first time sequence signal by using an adaptive filter to obtain a second time sequence electric signal.

[0142] The frequency determination module 804 is configured to determine a signal instantaneous frequency of a target signal cycle in the predetermined period according to the second time sequence signal.

[0143] The above-mentioned various modules in the electric energy information measuring device can be realized by software, hardware and combinations thereof in whole or in part. The above-mentioned various modules can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in a computer device in software form, so as to be called and executed by a processor to perform the operations corresponding to the above-mentioned various modules.

[0144] In one embodiment, a computer device is provided, which can be a server, and an internal structure diagram thereof can be as shown in the figure. Figure 8 The computer device comprises a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium to run. The database of the computer device is configured to store electric signal data. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through network connection. The computer program is executed by the processor to implement an electric energy information measuring method.

[0145] Those skilled in the art can understand that, Figure 8The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0146] In an embodiment, a computer device is provided, including a memory and a processor, the memory has stored therein a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0147] In an embodiment, a computer readable storage medium is provided, having stored thereon a computer program, and the computer program implements the steps in the above method embodiments when executed by a processor.

[0148] In an embodiment, a computer program product is provided, including a computer program, and the computer program implements the steps in the above method embodiments when executed by a processor.

[0149] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0150] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0151] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0152] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent of the present application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for measuring electrical energy information, characterized in that, The method includes: Acquire the variable frequency low-frequency electrical signal of the industrial motor within a predetermined time period to obtain the initial timing electrical signal; The initial timing signal is low-pass filtered using a digital filter to obtain a first timing signal; the digital filter is an IIR digital filter, and the parameters of the IIR digital filter are designed using an online calculation method; the online calculation method includes: The sampling period, sampling requirements, and signal characteristics of the initial time-series electrical signal are obtained. Based on the sampling period, sampling requirements, signal characteristics, and the processing performance of the IIR digital filter, the index parameters of the digital filter are determined. The index parameters include the order, passband cutoff frequency, cutoff frequency, and stopband cutoff frequency. According to the index parameters, the discrete transfer function of the IIR digital filter is determined. The discrete transfer function is used to perform low-pass filtering on the initial time-series electrical signal. The designed digital filter is converted into a discrete equation, and the bilinear transform method is used. Given the filter specifications, the discrete transfer function of the filter is as follows: Similarly, the discrete equation for a third-order low-pass digital filter is derived as follows: H3(z)=H 31 (z)·H 32 (With); in: Similarly, the discrete equation for the fourth-order filter is derived as follows: H4(z)=H 41 (z)·H 42 (z); in: An adaptive filter is used to filter the first time-series signal to obtain the second time-series electrical signal. Based on the second timing signal, the instantaneous frequency of the target signal period within the predetermined time period is determined.

2. The method according to claim 1, characterized in that, The digital filter is an IIR digital filter. Before applying the digital filter to the initial time-series electrical signal for low-pass filtering to obtain the first time-series electrical signal, the process includes: Obtain the sampling period, sampling requirements, and signal characteristics of the initial timing electrical signal; Based on the sampling period, the sampling requirements, the signal characteristics, and the processing performance of the IIR digital filter, the performance parameters of the digital filter are determined, including the order, passband cutoff frequency, cutoff frequency, and stopband cutoff frequency. Based on the aforementioned index parameters, the discrete transfer function of the IIR digital filter is determined, and the discrete transfer function is used to perform low-pass filtering on the initial timing electrical signal.

3. The method according to claim 1, characterized in that, The step of determining the instantaneous frequency of the target signal period within the predetermined time period based on the second time-series electrical signal includes: Based on the electrical signal values ​​of each sampling point in the second time-series signal, the first three adjacent signal zero-crossing points in time are determined. The first three adjacent signal zero-crossing points, in ascending order of time, include the first signal zero-crossing point, the second signal zero-crossing point, and the third signal zero-crossing point. The first signal zero-crossing point and the third signal zero-crossing point are used to characterize the start and end points of the target signal period. The time of the first signal crossing zero is determined based on two adjacent sampling points before and after the first signal crossing zero; and the time of the third signal crossing zero is determined based on two adjacent sampling points before and after the third signal crossing zero. By combining the zero-crossing time of the first signal, the zero-crossing time of the third signal, and the sampling period of the second time-series signal, the number of sampling points of the target signal period is obtained; By combining the sampling frequency of the second timing signal and the number of sampling points, the instantaneous frequency of the target signal period is obtained.

4. The method according to claim 3, characterized in that, In the step of determining the time of the zero-crossing of the first signal based on two adjacent sampling points before and after the zero-crossing of the first signal, and determining the time of the zero-crossing of the third signal based on two adjacent sampling points before and after the zero-crossing of the third signal, the least squares method is used to perform linear fitting to obtain the time of the zero-crossing of the first signal and the time of the zero-crossing of the third signal.

5. The method according to claim 3, characterized in that, The step of determining the three consecutive zero-crossing points of the first three signals in time based on the electrical signal values ​​of each sampling point in the second time-series signal includes: Compare the signs of the electrical signal values ​​of two adjacent sampling points sequentially; If the electrical signal values ​​of two adjacent sampling points have opposite signs, then it is determined whether it is a noise point based on the preset noise threshold. If it is not a noise point, then it is determined that there is a zero-crossing point between two adjacent sampling points.

6. The method according to claim 3, characterized in that, The method further includes determining the full-wave RMS value, full-wave apparent power, full-wave active power, and full-wave reactive power by combining the number of sampling points of the target signal period and the electrical signal value of the target signal period.

7. The method according to claim 1, characterized in that, The step of filtering the first time-series signal using an adaptive filter to obtain the second time-series signal includes: Obtain the difference between the initial timing electrical signal and the first timing electrical signal; The parameters of the adaptive filter are optimized based on the difference. The first time-series signal is filtered using an optimized adaptive filter to obtain the second time-series signal.

8. An electrical energy information measuring device, characterized in that, The device includes: The signal acquisition module is used to acquire the variable frequency low-frequency electrical signal of the industrial motor within a predetermined time period to obtain the initial timing electrical signal; The first filtering module is used to perform low-pass filtering on the initial timing electrical signal using a digital filter to obtain the first timing electrical signal; the digital filter is an IIR digital filter, and the parameters of the IIR digital filter are designed using an online calculation method; the online calculation method includes: The sampling period, sampling requirements, and signal characteristics of the initial time-series electrical signal are obtained. Based on the sampling period, sampling requirements, signal characteristics, and the processing performance of the IIR digital filter, the index parameters of the digital filter are determined. The index parameters include the order, passband cutoff frequency, cutoff frequency, and stopband cutoff frequency. According to the index parameters, the discrete transfer function of the IIR digital filter is determined. The discrete transfer function is used to perform low-pass filtering on the initial time-series electrical signal. The designed digital filter is converted into a discrete equation, and the bilinear transform method is used. Given the filter specifications, the discrete transfer function of the filter is as follows: Similarly, the discrete equation for a third-order low-pass digital filter is derived as follows: H3(z)=H 31 (z)·H 32 (With); in: Similarly, the discrete equation for the fourth-order filter is derived as follows: H4(z)=H 41 (z)·H 42 (z); in: The second filtering module is used to filter the first time-series signal using an adaptive filter to obtain a second time-series electrical signal. The frequency determination module is used to determine the instantaneous frequency of the target signal period within the predetermined time period based on the second timing signal.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

Images