CN110704800A - Power signal reconstruction method and system based on expansion coefficient - Google Patents

Power signal reconstruction method and system based on expansion coefficient Download PDF

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CN110704800A
CN110704800A CN201910867472.XA CN201910867472A CN110704800A CN 110704800 A CN110704800 A CN 110704800A CN 201910867472 A CN201910867472 A CN 201910867472A CN 110704800 A CN110704800 A CN 110704800A
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power signal
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翟明岳
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Guangdong University of Petrochemical Technology
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Abstract

The embodiment of the invention discloses a power signal reconstruction method and a system based on an expansion coefficient, wherein the method comprises the following steps: step 1, inputting an actually measured power signal sequence S; step 2, carrying out data reconstruction on the power signal sequence S, wherein the reconstructed power signal sequence is SNEW. The method specifically comprises the following steps: sNEW＝SOPT[STS]‑1(ii) a Wherein SOPTIs the best approximation vector.

Description

Power signal reconstruction method and system based on expansion coefficient
Technical Field
The present invention relates to the field of power, and in particular, to a method and a system for reconstructing a power signal.
Background
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-invasive load decomposition algorithm, the detection of the switching event of the electrical equipment is the most important link. The initial switch event detection takes the change value of the active power P as the judgment basis of the switch 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. The method needs to set a reasonable threshold value of the power change value, and also needs to solve the problems existing in the practical application of the event detection method, for example, a large peak appears in the instantaneous power value at the starting time of some electric appliances (the starting current of a motor is far larger than the rated current), which causes the inaccurate steady-state power change value of the electric appliances, thereby influencing the judgment of the detection of the switching event; 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. Meanwhile, in the process of acquiring and transmitting the power signal, the operation state of the related instrument and equipment may be temporarily in an abnormal state, which often causes the loss of the power signal.
Therefore, the actual measurement power signal used in the switching event detection process is often incomplete, and the switching event detection cannot be performed correctly by using the incomplete power signal. Therefore, how to effectively reconstruct the incomplete power signal is the key to the success of this method. The existing common method has insufficient attention to the problem, and no effective measure is taken to solve the problem.
Disclosure of Invention
The invention aims to provide a power signal reconstruction method and a power signal reconstruction system based on a coefficient of expansion. The method has the advantages of good robustness and simple calculation.
In order to achieve the purpose, the invention provides the following scheme:
a method for power signal reconstruction based on a coefficient of expansion, comprising:
step 1, inputting an actually measured power signal sequence S;
step 2, carrying out data reconstruction on the power signal sequence S, wherein the reconstructed power signal sequence is SNEW. The method specifically comprises the following steps: sNEW＝SOPT[STS]-1(ii) a Wherein SOPTIs the best approximation vector.
A coefficient of expansion based power signal reconstruction system comprising:
the acquisition module inputs an actually measured power signal sequence S;
a reconstruction module for performing data reconstruction on the power signal sequence S, wherein the reconstructed power signal sequence is SNEW. The method specifically comprises the following steps: sNEW＝SOPT[STS]-1(ii) a Wherein SOPTIs the best approximation vector.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
although the switching event detection method has wide application in non-invasive load decomposition and is relatively mature in technology, the power signal is often lost in the acquisition and transmission process and is often submerged in pulse noise with strong amplitude, and the switching event detection cannot be correctly performed by using the incomplete power signal. Therefore, how to effectively reconstruct the incomplete power signal is the key to the success of this method. The existing common method has insufficient attention to the problem, and no effective measure is taken to solve the problem.
The invention aims to provide a power signal reconstruction method and a power signal reconstruction system based on a coefficient of expansion. The method has the advantages of good robustness and simple calculation.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic diagram of the system of the present invention;
FIG. 3 is a flow chart illustrating an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
FIG. 1 is a schematic flow chart of a power signal reconstruction method based on expansion coefficients
Fig. 1 is a schematic flow chart of a power signal reconstruction method based on an expansion coefficient according to the present invention. As shown in fig. 1, the power signal reconstruction method based on the expansion coefficient specifically includes the following steps:
step 1, inputting an actually measured power signal sequence S;
step 2, carrying out data reconstruction on the power signal sequence S, wherein the reconstructed power signal sequence is SNEW. The method specifically comprises the following steps: sNEW＝SOPT[STS]-1(ii) a Wherein SOPTIs the best approximation vector.
Before the step 2, the method further comprises:
step 3, solving the best approximate vector SOPT。
The step 3 comprises the following steps:
step 301, initialization, specifically
u1As S: iterationVariables of
n is 1: iterative control parameter
Step 302, performing iterative update, specifically:
Figure BDA0002201679700000041
wherein:
un+1: step (n + 1) iteration parameter
Figure BDA0002201679700000042
Conversion factor
x＝[x1,x2,…,xN]Intermediate parameter vector
Θj[un]＝<S，ζj(S)>: projection vector of the signal sequence S
A projection matrix of the signal sequence S
Expansion factor matrix
Stretch factor matrix
Figure BDA0002201679700000046
Expansion factor
Figure BDA0002201679700000047
Stretch factor
S＝[s1,s2,…,sN]The signal sequence
N: length of the signal sequence S
Step 303, ending the iteration, specifically:
adding 1 to the iteration control parameter N, and returning to step 302 until the difference between the two adjacent iteration results is less than one thousandth, at which time the iteration control parameter N is equal to N, and obtaining the optimal approximation vector SOPT＝uN+1。
FIG. 2 is a structural diagram of a power signal reconstruction system based on expansion coefficients
Fig. 2 is a schematic structural diagram of a power signal reconstruction system based on an expansion coefficient according to the present invention. As shown in fig. 2, the power signal reconstruction system based on the expansion coefficient includes the following structures:
the acquisition module 401 inputs an actually measured power signal sequence S;
a reconstruction module 402, configured to perform data reconstruction on the power signal sequence S, where the reconstructed power signal sequence is SNEW. The method specifically comprises the following steps: sNEW＝SOPT[STS]-1(ii) a Wherein SOPTIs the best approximation vector.
The system further comprises:
a calculation module 403 for obtaining the best approximation vector SOPT。
The calculation module 403 further includes the following units:
an initialization unit 4031, initialization, specifically, initialization
u1As S: iterative variables
n is 1: iterative control parameter
The updating unit 4032 performs iterative updating, specifically:
Figure BDA0002201679700000051
wherein:
un+1: step (n + 1) iteration parameter
Figure BDA0002201679700000052
Conversion factor
x＝[x1,x2,…,xN]In the middleParameter vector
Θj[un]＝<S，ζj(S)>: projection vector of the signal sequence S
Figure BDA0002201679700000061
A projection matrix of the signal sequence S
Figure BDA0002201679700000062
Expansion factor matrix
Figure BDA0002201679700000063
Stretch factor matrix
Figure BDA0002201679700000064
Expansion factor
Figure BDA0002201679700000065
Stretch factor
S＝[s1,s2,…,sN]The signal sequence
N: length of the signal sequence S
The ending unit 4033 ends the iteration, specifically:
adding 1 to the iteration control parameter N, and returning to the updating unit 4032 until the difference between two adjacent iteration results is less than one thousandth, wherein the iteration control parameter N is equal to N, and the optimal approximation vector S is obtainedOPT＝uN+1。
The following provides an embodiment for further illustrating the invention
FIG. 3 is a flow chart illustrating an embodiment of the present invention. As shown in fig. 3, the method specifically includes the following steps:
1. inputting a sequence of measured power signals
S＝[s1,s2,…,sN-1,sN]
Wherein:
s: real vibration and sound signal data sequence with length N
siI is 1,2, …, N is measured vibration sound signal with serial number i
2. Iterative initialization
u1As S: iterative variables
n is 1: iterative control parameter
3. Iterative updating
Figure BDA0002201679700000071
Wherein:
un+1: step (n + 1) iteration parameter
Figure BDA0002201679700000072
Conversion factor
x＝[x1,x2,…,xN]Intermediate parameter vector
Θj[un]＝＜S，ζj(S) >: projection vector of the signal sequence S
Figure BDA0002201679700000073
A projection matrix of the signal sequence S
Figure BDA0002201679700000074
Expansion factor matrix
Figure BDA0002201679700000075
Stretch factor matrix
Expansion factor
Figure BDA0002201679700000077
Stretch factor
S＝[s1,s2,…,sN]The signal sequence
N: length of the signal sequence S
4. End of iteration
Adding 1 to the iteration control parameter N, and returning to the updating step until the difference between the two adjacent iteration results is less than one thousandth, wherein the iteration control parameter N is equal to N, and the optimal approximation vector S is obtainedOPT＝uN+1。
5. Data reconstruction
Carrying out data reconstruction on the power signal sequence S, wherein the reconstructed power signal sequence is SNEW. The method specifically comprises the following steps: sNEW＝SOPT[STS]-1(ii) a Wherein SOPTIs the best approximation vector.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is simple because the system corresponds to the method disclosed by the embodiment, and the relevant part can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (5)

1. A power signal reconstruction method based on expansion coefficients is characterized by comprising the following steps:
step 1, inputting an actually measured power signal sequence S;
step 2, carrying out data reconstruction on the power signal sequence S, wherein the reconstructed power signal sequence is SNEW. The method specifically comprises the following steps: sNEW＝SOPT[STS]-1(ii) a Wherein SOPTIs the best approximation vector.
2. The method of claim 1, wherein prior to step 2, the method further comprises:
step 3, solving the best approximate vector SOPT。
3. The method of claim 2, wherein step 3 comprises:
step 301, initialization, specifically
u1As S: iterative variables
n is 1: iterative control parameter
Step 302, performing iterative update, specifically:
Figure FDA0002201679690000011
wherein:
un+1: step (n + 1) iteration parameter
Figure FDA0002201679690000012
Conversion factor
x＝[x1,x2,…,xN]Intermediate parameter vector
Θj[un]＝<S，ζj(S)>: projection vector of the signal sequence S
Figure FDA0002201679690000013
A projection matrix of the signal sequence S
Figure FDA0002201679690000014
Expansion factor matrix
Figure FDA0002201679690000015
Stretch factor matrix
Figure FDA0002201679690000021
Expansion factor
Figure FDA0002201679690000022
Stretch factor
S＝[s1,s2,…,sN]The signal sequence
N: length of the signal sequence S
Step 303, ending the iteration, specifically:
adding 1 to the iteration control parameter N, and returning to step 302 until the difference between the two adjacent iteration results is less than one thousandth, at which time the iteration control parameter N is equal to N, and obtaining the optimal approximation vector SOPT＝uN+1。
4. A power signal reconstruction method system based on expansion coefficients is characterized by comprising the following steps:
the acquisition module inputs an actually measured power signal sequence S;
a reconstruction module for performing data reconstruction on the power signal sequence S, wherein the reconstructed power signal sequence is SNEW. The method specifically comprises the following steps: sNEW＝SOPT[STS]-1(ii) a Wherein SOPTIs the best approximation vector.
5. The system of claim 4, further comprising:
a calculation module for calculating the best approximation vector SOPT。
CN201910867472.XA 2019-09-12 2019-09-12 Power signal reconstruction method and system based on expansion coefficient Withdrawn CN110704800A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111756408A (en) * 2020-06-28 2020-10-09 广东石油化工学院 PLC signal reconstruction method and system using model prediction

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111756408A (en) * 2020-06-28 2020-10-09 广东石油化工学院 PLC signal reconstruction method and system using model prediction
CN111756408B (en) * 2020-06-28 2021-05-04 广东石油化工学院 PLC signal reconstruction method and system using model prediction

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