CN110784019A - Power signal filtering method and system by using Mercer projection - Google Patents

Power signal filtering method and system by using Mercer projection Download PDF

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CN110784019A
CN110784019A CN201911062091.0A CN201911062091A CN110784019A CN 110784019 A CN110784019 A CN 110784019A CN 201911062091 A CN201911062091 A CN 201911062091A CN 110784019 A CN110784019 A CN 110784019A
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mercer
projection
signal
sequence
signal sequence
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翟明岳
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Guangdong University of Petrochemical Technology
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Indication And Recording Devices For Special Purposes And Tariff Metering Devices (AREA)
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Abstract

The embodiment of the invention discloses a power signal filtering method and a system by utilizing Mercer projection, wherein the method comprises the following steps: step 1, inputting an actually measured signal sequence S; step 2, carrying out noise filtering processing on the signal sequence S according to Mercer projection, wherein the signal sequence after noise filtering is S NEW. The method specifically comprises the following steps: s NEW＝W OPTAnd S. Wherein, W OPTIs the Mercer optimal projection matrix.

Description

Power signal filtering method and system by using Mercer projection
Technical Field
The present invention relates to the field of power, and in particular, to a method and a system for filtering 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.
Therefore, in the switching event detection process, the actually measured power signal used is often affected by noise, and the switching event detection cannot be performed correctly by using the imperfect power signal. Therefore, how to effectively reconstruct the incomplete power signal and filter the influence of noise is the key to the success of the method. The existing common method has insufficient attention to the problem, and no effective measure is taken to solve the problem.
Disclosure of Invention
In the process of detecting the switching event, the actually measured power signal used is often affected by noise, and the detection of the switching event cannot be correctly performed by using the imperfect power signal. Therefore, how to effectively reconstruct the incomplete power signal and filter the influence of noise is the key to the success of the 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 filtering method and a power signal filtering system by using Mercer projection. The method has better robustness and simpler calculation.
In order to achieve the purpose, the invention provides the following scheme:
a method of filtering a power signal using Mercer projection, comprising:
step 001 inputting an actually measured signal sequence S;
step 002, noise filtering processing is carried out on the signal sequence S according to Mercer projection, and the signal sequence after noise filtering is S NEW. The method specifically comprises the following steps: s NEW＝W OPTAnd S. Wherein, W OPTIs the Mercer optimal projection matrix.
A power signal filtering system using Mercer projection, comprising:
an acquisition module inputs an actually measured signal sequence S;
the filtering module carries out noise filtering processing on the signal sequence S according to Mercer projection, and the signal sequence after noise filtering is S NEW. The method specifically comprises the following steps: s NEW＝W OPTAnd S. Wherein, W OPTIs the Mercer optimal projection matrix.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
in the process of detecting the switching event, the actually measured power signal used is often affected by noise, and the detection of the switching event cannot be correctly performed by using the imperfect power signal. Therefore, how to effectively reconstruct the incomplete power signal and filter the influence of noise is the key to the success of the 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 filtering method and a power signal filtering system by using Mercer projection. The method has better robustness and simpler 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 flow chart 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 filtering method using Mercer projection
FIG. 1 is a flow chart of a power signal filtering method using Mercer projection according to the present invention. As shown in fig. 1, the method for filtering a power signal by using Mercer projection specifically includes the following steps:
step 001 inputting an actually measured signal sequence S;
step 002, noise filtering processing is carried out on the signal sequence S according to Mercer projection, and the signal sequence after noise filtering is S NEW. The method specifically comprises the following steps: s NEW＝W OPTAnd S. Wherein, W OPTIs the Mercer optimal projection matrix.
Prior to the step 002, the method further comprises:
step 003 of obtaining theMercer optimal projection matrix W OPT。
The step 003 further includes:
step 301 generates a signal difference sequence Δ S nThe method specifically comprises the following steps:
ΔS n＝[s 2-s 1,s 3-s 2,···,s n-s n-1]
wherein:
ΔS n: the nth signal differential sequence
s n: the nth element of the signal sequence S
n: subscript, N ═ 1,2,. cndot., N
N: length of the signal sequence S
Note that: delta S 1＝0
Step 302 finds the desired sequence
Figure BDA0002258135000000031
The method specifically comprises the following steps:
Figure BDA0002258135000000032
wherein:
Figure BDA0002258135000000033
the nth expected sequence
σ S: mean square error of the signal sequence S
Figure BDA0002258135000000034
The nth signal difference sequence delta S nMean square error of
Figure BDA0002258135000000035
Nth desired weight
Figure BDA0002258135000000036
p: mercer projection order
Figure BDA0002258135000000037
SNR: signal-to-noise ratio of the signal sequence S
Step 303, calculating the Mercer optimal projection matrix W OPTThe method specifically comprises the following steps:
Figure BDA0002258135000000038
wherein:
W n: optimal Mercer shadow weights
α i: mercer matrix A nThe ith characteristic value of
Figure BDA0002258135000000042
Figure BDA0002258135000000043
i: the characteristic value sequence number, i ═ 1,2, ·, n
Z n: nth Mercer matrix A NFeature vector of
n: index of characteristic values, N ═ 1,2, ·, N
FIG. 2 is a schematic diagram of a power signal filtering system using Mercer projection
FIG. 2 is a schematic diagram of a power signal filtering system using Mercer projection according to the present invention. As shown in fig. 2, the power signal filtering system using Mercer projection includes the following structure:
the acquisition module 401 inputs an actually measured signal sequence S;
the filtering module 402 performs noise filtering processing on the signal sequence S according to the Mercer projection,
the signal sequence after noise filtering is S NEW. The method specifically comprises the following steps: s NEW＝W OPTS。
Wherein, W OPTIs the Mercer optimal projection matrix.
The system further comprises:
computing module 403 obtains the Mercer optimal projection matrix W OPT。
The calculation module 403 further includes the following units, which specifically include:
calculation unit 4031 generates signal difference sequence Δ S nThe method specifically comprises the following steps:
ΔS n＝[s 2-s 1,s 3-s 2,···,s n-s n-1]
wherein:
ΔS n: the nth signal differential sequence
s n: the nth element of the signal sequence S
n: subscript, N ═ 1,2,. cndot., N
N: length of the signal sequence S
Note that: delta S 1＝0
Calculation unit 4032 finds the desired sequence The method specifically comprises the following steps:
Figure BDA0002258135000000045
wherein:
Figure BDA0002258135000000051
the nth expected sequence
σ S: mean square error of the signal sequence S
Figure BDA0002258135000000052
The above-mentionedThe nth signal difference sequence delta S nMean square error of
Figure BDA0002258135000000053
Nth desired weight
Figure BDA0002258135000000054
p: mercer projection order
Figure BDA0002258135000000055
SNR: signal-to-noise ratio of the signal sequence S
Calculation unit 4033 finds the Mercer optimal projection matrix W OPTThe method specifically comprises the following steps:
Figure BDA0002258135000000056
wherein:
W n: optimal Mercer shadow weights
Figure BDA0002258135000000057
α i: mercer matrix A nThe ith characteristic value of
Figure BDA0002258135000000058
i: the characteristic value sequence number, i ═ 1,2, ·, n
Z n: nth Mercer matrix A NFeature vector of
n: index of characteristic values, N ═ 1,2, ·, N
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:
0 start: inputting measured signal data sequence
S＝[s 1,s 2,···,s N-1,s N]
Wherein:
s: measured signal sequence of length N
s n: the nth element in the signal sequence S
n: subscript, N ═ 1,2,. cndot., N
1 generating a signal difference sequence deltas nThe method specifically comprises the following steps:
ΔS n＝[s 2-s 1,s 3-s 2,···,s n-s n-1]
wherein:
ΔS n: the nth signal differential sequence
s n: the nth element of the signal sequence S
n: subscript, N ═ 1,2,. cndot., N
N: length of the signal sequence S
Note that: delta S 1＝0
2 finding the desired sequence
Figure BDA0002258135000000061
The method specifically comprises the following steps:
wherein:
Figure BDA0002258135000000063
the nth expected sequence
σ S: mean square error of the signal sequence S
Figure BDA0002258135000000064
The nth signal difference sequence delta S nMean square error of
Figure BDA0002258135000000065
Nth desired weight
Figure BDA0002258135000000066
p: mercer projection order
Figure BDA0002258135000000067
SNR: signal-to-noise ratio of the signal sequence S
3, solving the Mercer optimal projection matrix W OPTThe method specifically comprises the following steps:
Figure BDA0002258135000000068
wherein:
W n: optimal Mercer shadow weights
Figure BDA0002258135000000069
α i: mercer matrix A nThe ith characteristic value of
Figure BDA00022581350000000610
Figure BDA00022581350000000611
i: the characteristic value sequence number, i ═ 1,2, ·, n
Z n: nth Mercer matrix A NFeature vector of
n: index of characteristic values, N ═ 1,2, ·, N
And 4, finishing: filtering process
And carrying out noise filtering processing on the signal sequence S according to Mercer projection, wherein the signal sequence after noise filtering is S NEW. The method specifically comprises the following steps: s NEW＝W OPTAnd S. Wherein, W OPTIs the Mercer optimal projection matrix.
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 method of filtering a power signal using Mercer projection, comprising:
step 001 inputting an actually measured signal sequence S;
step 002, noise filtering processing is carried out on the signal sequence S according to Mercer projection, and the signal sequence after noise filtering is S NEW. The method specifically comprises the following steps: s NEW＝W OPTAnd S. Wherein, W OPTIs the Mercer optimal projection matrix.
2. The method of claim 1, wherein prior to step 2, the method further comprises:
step 003 of obtaining the Mercer optimal projection matrix W OPT。
3. The method of claim 2, wherein step 3 comprises:
step 301 generates a signal difference sequence Δ S nThe method specifically comprises the following steps:
ΔS n＝[s 2-s 1,s 3-s 2,…,s n-s n-1]
wherein:
ΔS n: the nth signal differential sequence
s n: the nth element of the signal sequence S
n: subscript, N ═ 1,2, …, N
N: length of the signal sequence S
Note that: delta S 1＝0
Step 302 finds the desired sequence
Figure FDA0002258134990000011
The method specifically comprises the following steps:
Figure FDA0002258134990000012
wherein:
Figure FDA0002258134990000013
the nth expected sequence
σ S: mean square error of the signal sequence S
Figure FDA0002258134990000014
The nth signal difference sequence delta S nMean square error of
Nth desired weight
Figure FDA0002258134990000016
p: mercer projection order
Figure FDA0002258134990000017
SNR: signal-to-noise ratio of the signal sequence S
Step 303, calculating the Mercer optimal projection matrix W OPTThe method specifically comprises the following steps:
Figure FDA0002258134990000018
wherein:
W n: optimal Mercer shadow weights
α i: mercer matrix A nThe ith characteristic value of
Figure FDA0002258134990000022
Figure FDA0002258134990000023
i: serial number of characteristic value, i ═ 1,2, …, n
Z n: nth Mercer matrix A NFeature vector of
n: the index of characteristic value, N ═ 1,2, …, N.
4. A power signal filtering system using Mercer projection, comprising:
an acquisition module inputs an actually measured signal sequence S;
the filtering module carries out noise filtering processing on the signal sequence S according to Mercer projection, and the signal sequence after noise filtering is S NEW. The method specifically comprises the following steps: s NEW＝W OPTAnd S. Wherein, W OPTIs the Mercer optimal projection matrix.
5. The system of claim 4, further comprising:
calculating the optimal Mercer projection matrix W by a calculation module OPT。
CN201911062091.0A 2019-11-02 2019-11-02 Power signal filtering method and system by using Mercer projection Withdrawn CN110784019A (en)

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