CN109241874B - Power signal filtering method in energy decomposition - Google Patents
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Abstract
The invention provides a power signal filtering method in energy decomposition, which can effectively filter out impulse noise in a power signal. The method comprises the following steps: acquiring a power signal sequence, and converting the power signal sequence into a two-dimensional signal; decomposing the two-dimensional signal to obtain a power signal decomposition coefficient; determining a power signal decomposition coefficient threshold according to the solved power signal decomposition coefficient; judging whether the amplitude of the solved power signal decomposition coefficient is larger than or equal to a power signal decomposition coefficient threshold value or not, if so, taking the decomposition coefficient for filtering noise as the solved power signal decomposition coefficient, and otherwise, taking the decomposition coefficient for filtering noise as a preset value; and generating a noise-free power signal sequence by using the obtained decomposition coefficient for filtering the noise. The invention relates to the field of electric power.
Description
Technical Field
The invention relates to the field of electric power, in particular to a power signal filtering method in energy decomposition.
Background
The energy decomposition is to decompose the power value read at the electric meter into the power value consumed by a single load, as shown in fig. 1, wherein the data in fig. 1 is analog data and non-measured data.
With the development of smart grids, the analysis of household electrical loads becomes more and more important. Through the analysis of the power load, a family user can obtain the power consumption information of each electric appliance and a refined list of the power charge in time; the power department can obtain more detailed user power utilization information, can improve the accuracy of power utilization load prediction, and provides a basis for overall planning for the power department. Meanwhile, the power utilization behavior of the user can be obtained by utilizing the power utilization information of each electric appliance, so that the method has guiding significance for the study of household energy consumption evaluation and energy-saving strategies.
The current electric load decomposition is mainly divided into an invasive load decomposition method and a non-invasive load decomposition method. The non-invasive load decomposition method does not need to install monitoring equipment on internal electric equipment of the load, and can obtain the load information of each electric equipment only according to the total information of the electric load. The non-invasive load decomposition method has the characteristics of less investment, convenience in use and the like, so that the method is suitable for decomposing household load electricity.
In the non-intrusive load decomposition algorithm, the detection of a switching event of an electrical device is the most important link, and the switching event refers to an action of opening a power switch of a load (the electrical device) or closing the power switch. The commonly used event detection takes the change value delta P of the active power P as the judgment basis of the event detection, and is convenient and intuitive. This is because the power consumed by any one of the electric devices changes, and the change is reflected in the total power consumed by all the electric devices. Besides the need to set a reasonable threshold for the power variation value, this method also needs to solve the problem of the event detection method in practical application: a large peak (for example, a motor starting current is much larger than a rated current) appears in an instantaneous power value at the starting time of some electric appliances, so that an electric appliance steady-state power change value is inaccurate, and the judgment of a switching event is influenced, and the peak is actually pulse noise; moreover, the transient process of different household appliances is long or short (the duration and the occurrence frequency of impulse noise are different greatly), so that the determination of the power change value becomes difficult; due to the fact that the active power changes suddenly when the quality of the electric energy changes (such as voltage drop), misjudgment is likely to happen. Fig. 2 is a collected/measured power signal (also referred to as a power data sequence), and it can be seen that the distribution of impulse noise in the power signal is that the instantaneous power of the impulse noise is very large, and it exhibits more obvious non-stationarity and non-gaussian characteristics. In the power sequence shown, there is only one true switching event, whereas the conventional event detection algorithm detects 3 switching events, and it can be seen that impulse noise has a large influence on the correct detection of the switching events.
Therefore, in the process of detecting the switching event, it is an important step to filter the impulse noise of the power signal, and in the prior art, the common impulse noise removing methods are low-pass filters and median filters, which cannot effectively filter the impulse noise in the power signal.
Disclosure of Invention
The invention aims to provide a power signal filtering method in energy decomposition to solve the problem that a low-pass filter and a median filter in the prior art cannot effectively filter pulse noise in a power signal.
To solve the above technical problem, an embodiment of the present invention provides a power signal filtering method in energy decomposition, including:
acquiring a power signal sequence, and converting the power signal sequence into a two-dimensional signal;
decomposing the two-dimensional signal to obtain a power signal decomposition coefficient;
determining a power signal decomposition coefficient threshold according to the solved power signal decomposition coefficient;
judging whether the amplitude of the solved power signal decomposition coefficient is larger than or equal to a power signal decomposition coefficient threshold value or not, if so, taking the decomposition coefficient for filtering noise as the solved power signal decomposition coefficient, and otherwise, taking the decomposition coefficient for filtering noise as a preset value;
and generating a noise-free power signal sequence by using the obtained decomposition coefficient for filtering the noise.
Further, the acquiring the power signal sequence and converting the power signal sequence into a two-dimensional signal comprises:
collecting power signal sequences P (1), P (2), …, P (N), and converting the power signal sequences into a matrix form to obtain a power matrix, wherein N is the length of the power signal sequences;
the power matrix is converted into a two-dimensional signal.
Further, the acquiring the power signal sequences P (1), P (2), …, P (n), and converting them into a matrix form, and obtaining the power matrix includes:
dividing the power signal sequence P (1), P (2), …, P (N) into N according to the sequence of the power signal sequence P (1), P (2), …, P (N)RSegments, each segment containing NCThe number of the data is one,
wherein, the symbol
Representing upper rounding;
if N is present<NR×NCZero-filling the deficient part of the last section;
rearranging the segmented data into a matrix form, wherein one segment of data is one row to obtain a power matrix
Further, the two-dimensional signal obtained after conversion is:
nr＝1,2,…,NR
nc＝1,2,…,NC
wherein the content of the first and second substances,
a two-dimensional signal is represented by,
representing a power matrix
N of (2)rLine, n-thcColumn elements.
Further, the decomposing the two-dimensional signal and the obtaining the power signal decomposition coefficient includes:
by the formula
Decomposing the two-dimensional signal to obtain a power signal decomposition coefficient
Wherein the content of the first and second substances,
representing the power signal transformation operator,
representing power signal transformation operators
The conjugate of (a) to (b),
representing a parameter.
Further, a power signal transformation operator
The calculation formula of (2) is as follows:
wherein the content of the first and second substances,
is composed of
Weight function in the domain, argument being
Is composed of
Weight function in the domain, argument being
Superscript i denotes imaginary units.
Further, the determining a power signal decomposition coefficient threshold according to the solved power signal decomposition coefficient includes:
calculating the mean value c of the amplitude of the power signal decomposition coefficientmean；
Solving the mean square error sigma of the amplitude of the power signal decomposition coefficient;
determining a power signal decomposition coefficient threshold τ: τ ═ cmean+0.712*σ。
Further, the decomposition coefficient for filtering noise is expressed as:
wherein the content of the first and second substances,
is a decomposition coefficient for filtering noise, which represents a decomposition coefficient of the power signal after the noise has been filtered; | indicates the amplitude of the extracted |.
Further, the generating a noise-free power signal sequence by using the obtained decomposition coefficient for filtering noise includes:
according to the obtained decomposition coefficient of the filtered noise
By the formula
Obtaining a noise-free power signal
Based on the obtained noise-free power signal
Constructing a new power matrix
The obtained power matrix
The first line of data is used as a first section, the second line of data is used as a second section, and so on, the last line of data is used as a last section, the sections are connected in sequence, and the front N data are intercepted to form a data sequence, and the data sequence is a noiseless power signal sequence.
Further, the power matrix
Expressed as:
the technical scheme of the invention has the following beneficial effects:
in the scheme, a power signal sequence is collected and converted into a two-dimensional signal; decomposing the two-dimensional signal to obtain a power signal decomposition coefficient; determining a power signal decomposition coefficient threshold according to the solved power signal decomposition coefficient; judging whether the amplitude of the solved power signal decomposition coefficient is larger than or equal to a power signal decomposition coefficient threshold value or not, if so, taking the decomposition coefficient for filtering noise as the solved power signal decomposition coefficient, and otherwise, taking the decomposition coefficient for filtering noise as a preset value; the obtained decomposition coefficient for filtering the noise is utilized to generate a noise-free power signal sequence, so that the pulse noise in the power signal is effectively filtered, but the high-fidelity function is realized on the useful signal, the step characteristic of the power signal is not damaged, and the moment of occurrence of a switching event can be detected more easily and quickly.
Drawings
FIG. 1 is a schematic energy decomposition diagram;
FIG. 2 is a schematic diagram of a power signal collected/measured;
FIG. 3 is a flow chart illustrating a method for filtering a power signal in energy decomposition according to an embodiment of the present invention;
FIG. 4 is a detailed flowchart of a power signal filtering method in energy decomposition according to an embodiment of the present invention;
fig. 5 is a schematic diagram of data segmentation and matrix arrangement provided in the embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
The invention provides a power signal filtering method in energy decomposition, aiming at the problem that the existing low-pass filter and median filter can not effectively filter out pulse noise in a power signal.
As shown in fig. 3, the embodiment of the invention provides a method for filtering a power signal in energy decomposition
S101, acquiring a power signal sequence, and converting the power signal sequence into a two-dimensional signal;
s102, decomposing the two-dimensional signal to obtain a power signal decomposition coefficient;
s103, determining a power signal decomposition coefficient threshold according to the solved power signal decomposition coefficient;
s104, judging whether the amplitude of the solved power signal decomposition coefficient is larger than or equal to a power signal decomposition coefficient threshold value, if so, taking the decomposition coefficient for filtering noise as the solved power signal decomposition coefficient, otherwise, taking the decomposition coefficient for filtering noise as a preset value;
and S105, generating a noise-free power signal sequence by using the obtained decomposition coefficient of the filtered noise.
The power signal filtering method in energy decomposition, provided by the embodiment of the invention, is used for collecting a power signal sequence and converting the power signal sequence into a two-dimensional signal; decomposing the two-dimensional signal to obtain a power signal decomposition coefficient; determining a power signal decomposition coefficient threshold according to the solved power signal decomposition coefficient; judging whether the amplitude of the solved power signal decomposition coefficient is larger than or equal to a power signal decomposition coefficient threshold value or not, if so, taking the decomposition coefficient for filtering noise as the solved power signal decomposition coefficient, and otherwise, taking the decomposition coefficient for filtering noise as a preset value; the obtained decomposition coefficient for filtering the noise is utilized to generate a noise-free power signal sequence, so that the pulse noise in the power signal is effectively filtered, but the high-fidelity function is realized on the useful signal, the step characteristic of the power signal is not damaged, and the moment of occurrence of a switching event can be detected more easily and quickly.
For better understanding of the method for filtering a power signal in energy decomposition according to the embodiment of the present invention, as shown in fig. 4, the method for filtering a power signal in energy decomposition may specifically include the following steps:
a1, collecting power signal sequence
Acquiring power signal sequences P (1), P (2), …, P (N), wherein N is the length of the power signal sequence.
A2, segmenting the power signal sequences P (1), P (2), …, P (N) and rearranging the segmented data into a power matrix P, wherein the data segmentation and matrix arrangement are shown in FIG. 5.
A21, dividing the power signal sequence P (1), P (2), …, P (N) into N according to the sequence of the power signal sequence P (1), P (2), …, P (N)RSegments, each segment containing NCThe number of the data is one,
wherein, the symbol
Meaning that the upper rounding, for example,
the purpose of this is that all data is involved in the operation and not discarded.
In general, N isR256 or 512 or 1024, in practical applications, NRThe value of (a) is determined by the actual application scenario.
A22 if N<NR×NCThe insufficient part of the last segment is zero-filled.
A23, rearranging the segmented data into matrix form, one segment of data is one row, so that the power matrix P has N in totalRLine, NCColumn, power matrix can be expressed as
A3, mixing power matrix
Conversion to two-dimensional signals
nr＝1,2,…,NR
nc＝1,2,…,NC
Wherein the content of the first and second substances,
representing a power matrix
N of (2)rLine, n-thcColumn elements.
A4, for two-dimensional signals
Is decomposed
By the formula
For two-dimensional signals
Decomposing to obtain power signal decomposition coefficient
Wherein the content of the first and second substances,
representing the power signal transformation operator,
representing power signal transformation operators
The conjugate of (a) to (b),
representing a parameter.
In this example, GongRate signal transformation operator
The calculation formula of (2) is as follows:
wherein the content of the first and second substances,
is composed of
Weight function in the domain, argument being
A gaussian function may be selected in general;
is composed of
Weight function in the domain, argument being
The superscript i denotes the imaginary unit whose square is equal to-1.
A5, determining a power signal decomposition coefficient threshold, wherein the specific steps may include:
a51, calculating the average value c of the amplitude of the power signal decomposition coefficientmean；
A52, solving the mean square error sigma of the amplitude of the power signal decomposition coefficient;
a53, determining a power signal decomposition coefficient threshold value tau: τ ═ cmean+0.712*σ。
A6, determining the decomposition coefficient for filtering noise
Wherein the content of the first and second substances,
is a decomposition coefficient for filtering noise, which represents a decomposition coefficient of the power signal after the noise has been filtered; | indicates the amplitude of the extracted |.
A7, obtaining a new power signal
A71, the obtained decomposition coefficient for filtering noise
The power signal corresponding to the decomposition coefficient sequence is the required noise-free power signal. Specifically, the method comprises the following steps:
according to the obtained decomposition coefficient of the filtered noise
By the formula
Obtaining a noise-free power signal
A72, constructing a new power signal matrix
Obtained by
As a new power matrix
N of (2)rLine, n-thcThe column elements, namely:
a8, rearranging data to obtain a noise-free power signal sequence
The obtained power matrix
The first line of data is used as a first section, the second line of data is used as a second section, and so on, the last line of data is used as a last section, the sections are connected in sequence, and the front N data are intercepted to form a data sequence, and the data sequence is a noiseless power signal sequence.
The power signal filtering method in energy decomposition can effectively filter out pulse noise in the power signal. The purpose of noise filtering is to detect the switching event, and after the noise is filtered by the method, the accuracy of the switching event detection can be improved by about 10 percent; the error of the occurrence time of the switching event can be controlled to be about 14 percent.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (1)
1. A method for filtering a power signal in energy decomposition, comprising:
acquiring a power signal sequence, and converting the power signal sequence into a two-dimensional signal;
decomposing the two-dimensional signal to obtain a power signal decomposition coefficient;
determining a power signal decomposition coefficient threshold according to the solved power signal decomposition coefficient;
judging whether the amplitude of the solved power signal decomposition coefficient is larger than or equal to a power signal decomposition coefficient threshold value or not, if so, taking the decomposition coefficient for filtering noise as the solved power signal decomposition coefficient, and otherwise, taking the decomposition coefficient for filtering noise as a preset value;
generating a noise-free power signal sequence by using the obtained decomposition coefficient for filtering the noise;
wherein, the acquiring the power signal sequence and converting the power signal sequence into a two-dimensional signal comprises:
collecting power signal sequences P (1), P (2), …, P (N), and converting the power signal sequences into a matrix form to obtain a power matrix, wherein N is the length of the power signal sequences;
converting the power matrix into a two-dimensional signal;
wherein, the acquiring the power signal sequence P (1), P (2), …, P (n), converting it into a matrix form, and obtaining the power matrix includes:
dividing the power signal sequence P (1), P (2), …, P (N) into N according to the sequence of the power signal sequence P (1), P (2), …, P (N)RSegments, each segment containing NCThe number of the data is one,
wherein, the symbol
Representing upper rounding;
if N is present<NR×NCZero-filling the deficient part of the last section;
rearranging the segmented data into a matrix form, wherein one segment of data is one row to obtain a power matrix
Wherein, the two-dimensional signal obtained after conversion is:
nr＝1,2,…,NR
nc＝1,2,…,NC
wherein the content of the first and second substances,
a two-dimensional signal is represented by,
representing a power matrix
N of (2)rLine, n-thcA column element;
wherein, the decomposing the two-dimensional signal and the obtaining the power signal decomposition coefficient comprises:
by the formula
Decomposing the two-dimensional signal to obtain a power signal decomposition coefficient
Wherein the content of the first and second substances,
representing the power signal transformation operator,
representing power signal transformation operators
The conjugate of (a) to (b),
representing a parameter;
wherein the power signal transformation operator
The calculation formula of (2) is as follows:
wherein the content of the first and second substances,
is composed of
Weight function in the domain, argument being
Is composed of
Weight function in the domain, argument being
Superscript i represents the imaginary unit;
wherein, according to the solved power signal decomposition coefficient, determining the power signal decomposition coefficient threshold value comprises:
calculating the mean value c of the amplitude of the power signal decomposition coefficientmean；
Solving the mean square error sigma of the amplitude of the power signal decomposition coefficient;
determining a power signal decomposition coefficient threshold τ: τ ═ cmean+0.712*σ；
Wherein the decomposition coefficient for filtering noise is expressed as:
wherein the content of the first and second substances,
is a decomposition coefficient for filtering noise, which represents a decomposition coefficient of the power signal after the noise has been filtered; | indicates the amplitude of the extracted |;
wherein, the generating a noise-free power signal sequence by using the obtained decomposition coefficient for filtering noise comprises:
according to the obtained decomposition coefficient of the filtered noise
By the formula
Obtaining a noise-free power signal
Based on the obtained noise-free power signal
Constructing a new power matrix
The obtained power matrix
Taking the first row of data as a first section, taking the second row of data as a second section, and so on, taking the last row of data as a last section, connecting the sections in sequence, and intercepting the front N data to form a data sequence, wherein the data sequence is a noiseless power signal sequence;
wherein the power matrix
Expressed as:
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| CN103209006A (en) * | 2013-04-10 | 2013-07-17 | 华为技术有限公司 | Method and device for eliminating impulse noise |
| CN104007469A (en) * | 2014-05-24 | 2014-08-27 | 长江大学 | Weak seismic signal reconstruction method based on curvelet transform |
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