CN113866524B - Three-phase power unbalance degree change trend measuring method and system - Google Patents
Three-phase power unbalance degree change trend measuring method and system Download PDFInfo
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Abstract
The invention discloses a three-phase power unbalance degree change trend measuring method and a system, wherein the measuring method comprises the following steps: s1, acquiring a three-phase electric sinusoidal signal; s2, converting the sinusoidal electric signal into a three-phase electric digital signal; s3, storing the digital signals in a data caching module; s4, adding a time stamp to the digital signal; s5, screening out a plurality of data with the minimum occurrence probability from the data corresponding to all the digital signals with the time stamps, and eliminating the data; s6, respectively storing the rest data after the elimination into three arrays according to the same data, copying the last data of the eliminated time point to the eliminated time point, and generating a time point array; s7, vector summation is carried out on the three groups of each time point; s8, taking the current time point as a cut-off, taking the vector summation value corresponding to all data as a period, and calculating the average value N of the current period; s9, calculating the difference ratio of the current period data to the mean value of the previous period data to obtain the change trend of the unbalanced degree of the three-phase power.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a three-phase power unbalance degree change trend measuring method and system.
Background
In recent years, the power grid scale is continuously enlarged, clean energy such as wind energy, solar energy and the like is accessed, and the AC/DC parallel operation is developed, and the power system in China has the characteristics of huge overall scale, various operation modes, rapid trend change, complex operation control and the like. In order to ensure the safety and reliability of the power distribution equipment of the power grid, the real-time sensing and health state assessment of the running state of the substation equipment are realized by monitoring the substation equipment on line through a hardware and sensor acquisition technology and a computer communication data management technology, and meanwhile, the equipment with faults is timely arranged for maintenance.
The index 3I0 for measuring the three-phase unbalance degree is one of important indexes in the power quality monitoring, phase angle difference exists at a three-phase point under the working condition, fluctuation exists at the 3I0, the smaller the fluctuation is, the smaller the three-phase unbalance degree is, the higher the power quality is relatively, but when the fluctuation degree is gradually increased or a larger mutation occurs, the condition that high-capacity asymmetric load access is possible or the harmonic wave in a power grid has a harmful effect on the three-phase electric phase is indicated, and meanwhile, the increase of the three-phase unbalance fluctuation can also indicate the power quality reduction or the failure or damage of a collecting device. The problem existing at present is that a statistical parameter capable of measuring the size of the 3I0 variation trend is lacking, and the variation trend of the three-phase unbalance degree needs to be observed manually, which is not beneficial to accurate quantification. Therefore, it is necessary to provide a method for measuring the variation trend of the unbalance degree of the three-phase power.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a three-phase power unbalance degree change trend measuring method and a system, wherein an acquisition device acquires electric signals at regular time through a current transformer, eliminates abrupt signals, performs vector summation on data acquired at each time point, performs vector sum averaging on a specified period, calculates the statistical parameter for measuring the three-phase unbalance degree change trend, realizes accurate measurement of the power three-phase unbalance degree change trend, ensures that a user can more conveniently and directly observe three-phase unbalance change of a power grid, avoids misjudgment caused by subjective factors, and is more convenient for additionally arranging an early warning function.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a three-phase power unbalance degree change trend measuring method comprises the following steps:
s1, acquiring a three-phase electric sinusoidal electric signal of a current transformer of a transformer substation through a signal acquisition board;
s2, converting the acquired sinusoidal electric signals into three-phase electric digital signals through a continuous time ADC module;
s3, storing the converted digital signals in a data buffer module integrated on a signal acquisition board;
s4, adding a time stamp to the stored digital signal through a Python time module;
s5, screening out a plurality of data with the minimum occurrence probability from the data corresponding to all the digital signals with the time stamps through a MapReduce programming model, and eliminating the screened data;
s6, respectively storing the rest data after the elimination into three arrays according to the same data, copying the last data of the eliminated time point to the eliminated time point, and generating a time point array;
s7, vector summation is carried out on three groups of data at each time point through a function ufunc provided by NumPy;
s8, taking the current time point as a cut-off, taking the vector summation value corresponding to all the data in the step S5 as a period, and calculating the average value N of the current period;
s9, calculating the difference ratio description deviation regression characteristic of the current time data and the last period data mean value, and obtaining the change trend of the three-phase power unbalance degree.
Further, the three-phase electric digital signal in the step S2 is three current values on the three-phase electric time domain collected every two hours by the collecting board.
Further, the data buffer module in step S3 communicates with a PC through a 485 protocol, and the PC is configured to invoke the digital signal stored in the data buffer module.
Further, the length of the array in the step S6 is 6, where the elements of the array respectively include: a phase current value, a phase angle, a phase current value, and a phase angle.
Further, in the step S7, vector summation is performed on the three sets of data at each time point, which is expressed as:
wherein A, B, C each represents A, B, C three-phase current values;each of which represents the phase angles of the three phases A, B, C.
Further, in the step S9, the deviation regression characteristic η is expressed as:
η＝{(n 1 -N)/N}*100％
wherein n is 1 Zero sequence current for representing the unbalance degree of three-phase power at the current moment; l (L) i And representing 120 three-phase power unbalance degree zero-sequence currents of 10 days before the current moment, wherein i=1, 2, … … and 199,120.
Correspondingly, the utility model also provides a three-phase power unbalance degree trend of change system, include:
the acquisition module is used for acquiring three-phase electric sinusoidal electric signals of the current transformer of the transformer substation through the signal acquisition board;
the continuous time ADC module is used for converting the acquired sinusoidal electric signals into three-phase electric digital signals;
the data caching module is used for storing the converted digital signals in the data caching module integrated on the signal acquisition board;
the adding module is used for adding a time stamp to the stored digital signal through the Python time module;
the screening module is used for screening out a plurality of data with the minimum occurrence probability from the data corresponding to all the digital signals with the time stamps through a MapReduce programming model, and rejecting the screened data;
the copying module is used for respectively storing the data left after the elimination into three arrays according to the same, copying the last data of the eliminated time point to the eliminated time point and generating a time point array;
the summation module is used for vector summation of the three groups of data at each time point through a function ufunc provided by NumPy;
the first calculation module is provided with a vector summation value corresponding to all data in the step S5 which takes the current time point as a cut-off as a period, and calculates the average value N of the current period;
and the second calculation module is used for calculating the difference ratio description deviation regression characteristic of the current moment data and the last period data mean value, and obtaining the change trend of the three-phase power unbalance degree.
Further, the device also comprises a timer timing module for setting the starting time and the acquisition period.
Further, the summing module performs vector summation on three groups of data at each time point, which is expressed as:
wherein A, B, C each represents A, B, C three-phase current values;each of which represents the phase angles of the three phases A, B, C.
Further, the deviation regression characteristic η in the second calculation module is expressed as:
η＝{(n 1 -N)/N}*100％
wherein n is 1 Zero sequence current for representing the unbalance degree of three-phase power at the current moment; l (L) i Representing 120 three-phase power unbalance degrees 10 days before current momentZero sequence current, i=1, 2, … …,199,120.
Compared with the prior art, the invention has the following beneficial effects:
1. the three-phase unbalance degree is accurately quantized, and compared with the artificial observation of the change trend, the three-phase unbalance degree forms more convenient and practical statistical parameters;
2. the statistical parameters in the invention can more directly reflect the reliability of the acquisition device, and the maintenance equipment has more pertinence;
3. accurate quantification of the three-phase imbalance degree is more convenient and a warning function is directly added.
Drawings
Fig. 1 is a flowchart of a three-phase power unbalance degree variation trend measuring method according to a first embodiment;
FIG. 2 is a schematic diagram of data acquisition according to a first embodiment;
fig. 3 is a schematic diagram of data processing according to a first embodiment.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
The invention aims at overcoming the defects of the prior art and provides a three-phase power unbalance degree change trend measuring method and system.
Example 1
The embodiment provides a three-phase power unbalance degree change trend measuring method, as shown in fig. 1, including:
s1, acquiring a three-phase electric sinusoidal electric signal of a current transformer of a transformer substation through a signal acquisition board;
s2, converting the acquired sinusoidal electric signals into three-phase electric digital signals through a continuous time ADC module;
s3, storing the converted digital signals in a data buffer module integrated on a signal acquisition board;
s4, adding a time stamp to the stored digital signal through a Python time module;
s5, screening out a plurality of data with the minimum occurrence probability from the data corresponding to all the digital signals with the time stamps through a MapReduce programming model, and eliminating the screened data;
s6, respectively storing the rest data after the elimination into three arrays according to the same data, copying the last data of the eliminated time point to the eliminated time point, and generating a time point array;
s7, vector summation is carried out on three groups of data at each time point through a function ufunc provided by NumPy;
s8, taking the current time point as a cut-off, taking the vector summation value corresponding to all the data in the step S5 as a period, and calculating the average value N of the current period;
s9, calculating the difference ratio description deviation regression characteristic of the current time data and the last period data mean value, and obtaining the change trend of the three-phase power unbalance degree.
In this embodiment, the three-phase power unbalance degree variation trend measuring method includes a data acquisition section and a data processing section.
The data acquisition part is shown in fig. 2 and comprises a timer timing module, a continuous time ADC module, a data caching module and a 485 communication module.
The method further comprises the following steps before the step S1:
s0. the timer timing module sets the on time and the acquisition period.
In step S1, a three-phase electric sinusoidal electrical signal of a substation current transformer is collected by a signal collection board.
In step S2, the acquired sinusoidal electrical signal is converted into a three-phase electrical digital signal by a continuous-time ADC module.
The continuous time ADC module is connected with the timer timing module so as to convert the three-phase electric sinusoidal electric signals acquired by the current transformer into digital signals.
In this embodiment, the three-phase electric digital signal is three current values on the three-phase electric time domain collected every two hours by the collection board, the collection board is started to collect first data from the zero point setting start, then one data is recorded every two hours, and after the PC and the collection board realize communication, each data is time stamped through the time base of Python.
In step S3, the converted digital signal is stored in a data buffer module integrated on the signal acquisition board.
The data buffer module is connected with the continuous time ADC module so as to store the digital signal in the buffer area module and wait for further processing of the digital signal.
In this embodiment, the device further includes a data buffer module connected to the 485 communication module, so that when the acquisition board completes communication with the PC through the 485 communication module, the digital signal stored in the data buffer module can be invoked for further processing.
The data processing part is shown in fig. 3, and specifically comprises:
in step S4, the stored digital signal is time stamped by the PythonTime module.
The acquired three-phase electrical digital signal is time stamped by PythonTime.
In step S5, several data with the smallest occurrence probability in the data corresponding to all the time-stamped digital signals are screened out through a MapReduce programming model, and the screened data are removed.
And counting a few data with the smallest occurrence probability in 120 times of collected data through MapReduce, and eliminating the data.
In this embodiment, the probability of occurrence of the acquired data is that the probability of occurrence of the list of the key corresponding value generated for the Map method in the MapReduce is small when the list is traversed by the Reduce method, and conversely the probability of occurrence of the data corresponding to the plurality of elements in the list is large.
In step S6, the remaining data after the removal is stored into three arrays respectively according to the same, and the last data of the removed time point is copied to the removed time point to generate the time point array.
And respectively storing the three-phase power data after the mutation rejection into three arrays arr according to the same, copying one data at the time point of rejection to the time point of rejection, and generating the time point array.
The array arr is a one-dimensional array of length 6, wherein the elements respectively include: a phase current value, a phase angle, a phase current value, a phase angle, a phase current value, and a phase angle; the array of the removed time points is the same as the array of the previous time point.
In step S7, the three sets of data for each time point are vector summed by the function ufunc provided by NumPy.
The three sets of data at each time point are vector summed by a function ufunc provided by NumPy.
The NumPy library may implement vector summation of the data in the digital arr, with the summation result being a nominal value, referred to as 3I0, for measuring the degree of three-phase imbalance.
Vector summation is carried out on three groups of each time point, namely a three-phase power unbalance degree 3I0 calculation formula is expressed as follows:
wherein A, B, C each represents A, B, C three-phase current values;each of which represents the phase angles of the three phases A, B, C.
In step S8, taking the current time point as a cutoff, taking the vector summation value corresponding to all the data in step S5 as a period, and calculating the average value N of the current period.
Taking the current time point as a cut-off, taking the previous 120 vector summation values as a period, and calculating the average value N of the period.
In step S9, a difference ratio description of the current time data and the last period data average value is calculated to deviate from the regression characteristic, so as to obtain a variation trend of the three-phase power unbalance degree.
Calculating the change trend of the three-phase power unbalance degree uses a DRF deviation regression algorithm (based on deviation of the previous period mean value from the current period data and regression calculation) to describe the deviation regression characteristic by using the difference ratio of the current period data and the previous period data mean value.
The deviation regression characteristic is a characteristic describing the change trend of 3I0 at a specified time point relative to the mean value of 3I0 in the first ten days, and a cycle of calculating the mean value for the first data of the following day is reserved for 10 days when the deviation regression characteristic is calculated.
Deviation regression characteristic η, expressed as:
η＝{(n 1 -N)/N}*100％
wherein n is 1 Zero sequence current for representing the unbalance degree of three-phase power at the current moment; l (L) i And representing 120 three-phase power unbalance degree zero-sequence currents of 10 days before the current moment, wherein i=1, 2, … … and 199,120.
Example two
The embodiment provides a three-phase power unbalance degree change trend measurement system, which comprises:
the acquisition module is used for acquiring three-phase electric sinusoidal electric signals of the current transformer of the transformer substation through the signal acquisition board;
the continuous time ADC module is used for converting the acquired sinusoidal electric signals into three-phase electric digital signals;
the data caching module is used for storing the converted digital signals in the data caching module integrated on the signal acquisition board;
the adding module is used for adding a time stamp to the stored digital signal through the Python time module;
the screening module is used for screening out a plurality of data with the minimum occurrence probability from the data corresponding to all the digital signals with the time stamps through a MapReduce programming model, and rejecting the screened data;
the copying module is used for respectively storing the data left after the elimination into three arrays according to the same, copying the last data of the eliminated time point to the eliminated time point and generating a time point array;
the summation module is used for vector summation of the three groups of data at each time point through a function ufunc provided by NumPy;
the first calculation module is provided with a vector summation value corresponding to all data in the step S5 which takes the current time point as a cut-off as a period, and calculates the average value N of the current period;
and the second calculation module is used for calculating the difference ratio description deviation regression characteristic of the current moment data and the last period data mean value, and obtaining the change trend of the three-phase power unbalance degree.
Further, the device also comprises a timer timing module for setting the starting time and the acquisition period.
Further, the summing module performs vector summation on three groups of data at each time point, which is expressed as:
wherein A, B, C each represents A, B, C three-phase current values;each of which represents the phase angles of the three phases A, B, C.
Further, the deviation regression characteristic η in the second calculation module is expressed as:
η＝{(n 1 -N)/N}*100％
wherein n is 1 Representing a three-phase power imbalance at a current timeA degree zero sequence current; l (L) i And representing 120 three-phase power unbalance degree zero-sequence currents of 10 days before the current moment, wherein i=1, 2, … … and 199,120.
It should be noted that, the three-phase power unbalance degree variation trend measuring system provided in this embodiment is similar to that of the embodiment, and will not be described herein.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (6)
1. The three-phase power unbalance degree change trend measuring method is characterized by comprising the following steps of:
s1, acquiring three-phase electric sinusoidal signals of a current transformer of a transformer substation through a signal acquisition board;
s2, converting the acquired sinusoidal electric signals into three-phase electric digital signals through a continuous time ADC module;
s3, storing the converted digital signals in a data buffer module integrated on a signal acquisition board;
s4, adding a time stamp to the stored digital signal through a Python time module;
s5, screening out a plurality of data with the minimum occurrence probability from the data corresponding to all the digital signals with the time stamps through a MapReduce programming model, and eliminating the screened data;
s6, respectively storing the rest data after the elimination into three arrays according to the same data, copying the last data of the eliminated time point to the eliminated time point, and generating a time point array;
s7, vector summation is carried out on three groups of each time point through a function ufunc provided by NumPy;
in the step S7, vector summation is performed on the three groups at each time point, which is expressed as:
wherein A, B, C each represents A, B, C three-phase current values;respectively represent the phase angles of A, B, C three phases;
s8, taking the current time point as a cut-off, taking the vector summation value corresponding to all the data in the step S5 as a period, and calculating the average value N of the current period;
s9, calculating the difference ratio description deviation regression characteristic of the current time data and the previous period data mean value, and obtaining the change trend of the three-phase power unbalance degree;
the deviation regression characteristic η in the step S9 is expressed as:
η＝{(n 1 -N)/N}*100％
wherein n is 1 Zero sequence current for representing the unbalance degree of three-phase power at the current moment; l (L) i And representing 120 three-phase power unbalance degree zero-sequence currents of 10 days before the current moment, wherein i=1, 2, … … and 199,120.
2. The method according to claim 1, wherein the three-phase electric digital signal in step S2 is three current values in three-phase electric time domain collected every two hours by the collection board.
3. The method for measuring the variation trend of the three-phase power unbalance degree according to claim 2, wherein the data buffer module in the step S3 communicates with a PC through a 485 protocol, and the PC is used for calling the digital signal stored in the data buffer module.
4. The method for measuring the variation trend of three-phase power unbalance according to claim 1, wherein the array in the step S6 has a length of 6, and the elements of the array respectively include: a phase current value, a phase angle, a phase current value, and a phase angle.
5. A three-phase power unbalance degree change trend measuring system, characterized by comprising:
the acquisition module is used for acquiring three-phase electric sinusoidal electric signals of the current transformer of the transformer substation through the signal acquisition board;
the continuous time ADC module is used for converting the acquired sinusoidal electric signals into three-phase electric digital signals;
the data caching module is used for storing the converted digital signals in the data caching module integrated on the signal acquisition board;
the adding module is used for adding a time stamp to the stored digital signal through the Python time module;
the screening module is used for screening out a plurality of data with the minimum occurrence probability from the data corresponding to all the digital signals with the time stamps through a MapReduce programming model, and rejecting the screened data;
the copying module is used for respectively storing the data left after the elimination into three arrays according to the same, copying the last data of the eliminated time point to the eliminated time point and generating a time point array;
the summation module is used for vector summation of the three groups of data at each time point through a function ufunc provided by NumPy;
vector summation is carried out on three groups of each time point in the summation module, and the vector summation is expressed as follows:
wherein A, B, C each represents A, B, C three-phase current values;respectively represent the phase angles of A, B, C three phases;
the first calculation module is provided with a vector summation value corresponding to all data with the current time point as a cut-off as a period, and calculates the average value N of the current period;
the second calculation module is used for calculating the difference ratio description deviation regression characteristic of the current moment data and the last period data mean value to obtain the change trend of the three-phase power unbalance degree;
the second calculation module deviates from the regression characteristic η, expressed as:
η＝{(n 1 -N)/N}*100％
wherein n is 1 Zero sequence current for representing the unbalance degree of three-phase power at the current moment; l (L) i And representing 120 three-phase power unbalance degree zero-sequence currents of 10 days before the current moment, wherein i=1, 2, … … and 199,120.
6. The system of claim 5, further comprising a timer timing module for setting a start-up time and a collection period.
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