CN112180153A - Load switch event detection method and system by using KULLBACK-Leibler distance - Google Patents

Load switch event detection method and system by using KULLBACK-Leibler distance Download PDF

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Publication number
CN112180153A
CN112180153A CN202011068035.0A CN202011068035A CN112180153A CN 112180153 A CN112180153 A CN 112180153A CN 202011068035 A CN202011068035 A CN 202011068035A CN 112180153 A CN112180153 A CN 112180153A
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signal sequence
load switch
switch event
kullback
window
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翟明岳
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Guangdong University of Petrochemical Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R21/00—Arrangements for measuring electric power or power factor
    • G01R21/001—Measuring real or reactive component; Measuring apparent energy
    • G01R21/002—Measuring real component
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract

The embodiment of the invention discloses a load switch event detection method and system by utilizing a KULLBACK-Leibler distance, wherein the method comprises the following steps: step 101, acquiring a signal sequence S acquired according to a time sequence; step 102, generating N window signal sequences; step 103, calculating N Kullback-Leibler distances; step 104, obtaining a load switch event judgment threshold; step 105 detects a load switch event.

Description

Load switch event detection method and system by using KULLBACK-Leibler distance
Technical Field
The invention relates to the field of electric power, in particular to a load switch event detection method and system.
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 event detection takes the change value 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. The intensity of (impulse) noise is large and background noise has a large impact on the correct detection of switching events.
Load switching events that are now commonly used are often determined using changes in power data: when the power change value exceeds a preset threshold value, a load switch event is considered to occur. This approach, while simple and easy to implement, results in a significant drop in the accuracy of the switching event detection due to the impulse noise and the common use of non-linear loads.
Therefore, in the switching event detection process, how to improve the switching event detection accuracy is very important. Load switch event detection is the most important step in energy decomposition, and can detect the occurrence of an event and determine the occurrence time of the event. However, the accuracy of the detection of the switching event is greatly affected by noise in the power signal (power sequence), and particularly, impulse noise generally exists in the power signal, which further affects the detection accuracy. Therefore, it is currently a very important task to effectively improve the detection accuracy of the load switch event.
Disclosure of Invention
Load switching events that are now commonly used are often determined using changes in power data: when the power change value exceeds a preset threshold value, a load switch event is considered to occur. This approach, while simple and easy to implement, results in a significant drop in the accuracy of the switching event detection due to the impulse noise and the common use of non-linear loads.
The invention aims to provide a load switch event detection method and system by utilizing a KULLBACK-Leibler distance. The method has good switching event detection performance and is simple in calculation.
In order to achieve the purpose, the invention provides the following scheme:
a load switch event detection method using a KULLBACK-Leibler distance comprises the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 generates N window signal sequences, specifically: the Kth window signal sequence is bKThe nth element thereof is
Figure BDA0002714427020000021
The formula is obtained as follows:
Figure BDA0002714427020000022
wherein:
Figure BDA00027144270200000210
is the | K + n-M |' of the signal sequence SNAn element;
k is 1,2, N is a window serial number;
n is the length of the signal sequence S;
|K+n-M|Nrepresenting the residue removal of K + N-M by taking N as a modulus;
Figure BDA0002714427020000023
is a delay factor;
Figure BDA0002714427020000029
represents rounding on;
is any parameter;
σ0: the mean square error of the signal sequence S;
SNR: the signal-to-noise ratio of the signal sequence S;
step 103, calculating N Kullback-Leibler distances, specifically: the Kth window signal sequence bKThe corresponding Kullback-Leibler distance is LKThe calculation formula is as follows:
Figure BDA0002714427020000024
wherein:
m＝1,2,···,Niis a summation serial number;
Figure BDA0002714427020000025
for the K window signal sequence bKThe m-th element of (1);
vKfor the K window signal sequence bKThe mean value of (a);
Figure BDA0002714427020000026
is the window signal sequence mean;
σKfor the K window signal sequence bKThe mean square error of (d);
Figure BDA0002714427020000027
for the K window signal sequence bK1 st element in (1);
Figure BDA0002714427020000028
for the K window signal sequence bKThe nth element of (1);
step 104, obtaining a load switch event judgment threshold, specifically: the load switch event judgment threshold is as follows:
Figure BDA0002714427020000031
wherein:
snr is the signal-to-noise ratio of the signal sequence S;
step 105, detecting a load switch event, specifically: if the K-th Kullback-Leibler distance LKIf the judgment threshold value is greater than or equal to the load switch event judgment threshold value, detecting a load switch event at the Kth point of the signal sequence S; otherwise no load switch event is detected.
A load switch event detection system using KUllback-Leibler distance, comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 generates N window signal sequences, specifically: the Kth window signal sequence is bKThe nth element thereof is
Figure BDA0002714427020000032
The formula is obtained as follows:
Figure BDA0002714427020000033
wherein:
Figure BDA0002714427020000038
is the | K + n-M |' of the signal sequence SNAn element;
k is 1,2, N is a window serial number;
n is the length of the signal sequence S;
|K+n-M|Nrepresenting the residue removal of K + N-M by taking N as a modulus;
Figure BDA0002714427020000034
is a delay factor;
Figure BDA0002714427020000037
represents rounding on;
is any parameter;
σ0: the mean square error of the signal sequence S;
SNR: the signal-to-noise ratio of the signal sequence S;
the module 203 calculates N Kullback-Leibler distances, specifically: the Kth window signal sequence bKThe corresponding Kullback-Leibler distance is LKThe calculation formula is as follows:
Figure BDA0002714427020000035
wherein:
m＝1,2,···,Niis a summation serial number;
Figure BDA0002714427020000036
for the K window signal sequence bKThe m-th element of (1);
vKfor the K window signal sequence bKThe mean value of (a);
Figure BDA0002714427020000041
is the window signal sequence mean;
σKfor the K window signal sequence bKThe mean square error of (d);
Figure BDA0002714427020000042
for the K window signal sequence bK1 st element in (1);
Figure BDA0002714427020000043
for the K window signal sequence bKThe nth element of (1);
the module 204 finds a load switch event judgment threshold, specifically: the load switch event judgment threshold is as follows:
Figure BDA0002714427020000044
wherein:
snr is the signal-to-noise ratio of the signal sequence S;
the module 205 detects a load switch event, specifically: if the K-th Kullback-Leibler distance LKIf the judgment threshold value is greater than or equal to the load switch event judgment threshold value, detecting a load switch event at the Kth point of the signal sequence S; otherwise no load switch event is detected.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
load switching events that are now commonly used are often determined using changes in power data: when the power change value exceeds a preset threshold value, a load switch event is considered to occur. This approach, while simple and easy to implement, results in a significant drop in the accuracy of the switching event detection due to the impulse noise and the common use of non-linear loads.
The invention aims to provide a load switch event detection method and system by utilizing a KULLBACK-Leibler distance. The method has good switching event detection performance and is simple in 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 load switch event detection method using a KULLBACK-Leibler distance
Fig. 1 is a schematic flow chart of a load switch event detection method using a KUllback-Leibler distance according to the present invention. As shown in fig. 1, the load switch event detection method using the KUllback-Leibler distance specifically includes the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 generates N window signal sequences, specifically: the Kth window signal sequence is bKThe nth element thereof is
Figure BDA0002714427020000051
The formula is obtained as follows:
Figure BDA0002714427020000052
wherein:
Figure BDA00027144270200000510
is the | K + n-M |' of the signal sequence SNAn element;
k is 1,2, N is a window serial number;
n is the length of the signal sequence S;
|K+n-M|Nrepresenting the residue removal of K + N-M by taking N as a modulus;
Figure BDA0002714427020000053
is a delay factor;
Figure BDA0002714427020000059
represents rounding on;
is any parameter;
σ0: the mean square error of the signal sequence S;
SNR: the signal-to-noise ratio of the signal sequence S;
step 103, calculating N Kullback-Leibler distances, specifically: the Kth window signal sequence bKThe corresponding Kullback-Leibler distance is LKThe calculation formula is as follows:
Figure BDA0002714427020000054
wherein:
m＝1,2,···,Niis a summation serial number;
Figure BDA0002714427020000055
for the K window signal sequence bKThe m-th element of (1);
vKfor the K window signal sequence bKThe mean value of (a);
Figure BDA0002714427020000056
is the window signal sequence mean;
σKfor the K window signal sequence bKThe mean square error of (d);
Figure BDA0002714427020000057
for the K window signal sequence bK1 st element in (1);
Figure BDA0002714427020000058
for the K window signal sequence bKThe nth element of (1);
step 104, obtaining a load switch event judgment threshold, specifically: the load switch event judgment threshold is as follows:
Figure BDA0002714427020000061
wherein:
snr is the signal-to-noise ratio of the signal sequence S;
step 105, detecting a load switch event, specifically: if the K-th Kullback-Leibler distance LKIf the judgment threshold value is greater than or equal to the load switch event judgment threshold value, detecting a load switch event at the Kth point of the signal sequence S; otherwise no load switch event is detected.
FIG. 2 is a structural view of a load switch event detection system using a KULLBACK-Leibler distance
Fig. 2 is a schematic structural diagram of a load switch event detection system using a KUllback-Leibler distance according to the present invention. As shown in fig. 2, the load switch event detection system using the KUllback-Leibler distance includes the following structures:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 generates N window signal sequences, specifically: the Kth window signal sequence is bKThe nth element thereof is
Figure BDA0002714427020000062
The formula is obtained as follows:
Figure BDA0002714427020000063
wherein:
Figure BDA0002714427020000067
is the | K + n-M |' of the signal sequence SNAn element;
k is 1,2, N is a window serial number;
n is the length of the signal sequence S;
|K+n-M|Nrepresenting the residue removal of K + N-M by taking N as a modulus;
Figure BDA0002714427020000064
is a delay factor;
Figure BDA0002714427020000065
represents rounding on;
is any parameter;
σ0: the mean square error of the signal sequence S;
SNR: the signal-to-noise ratio of the signal sequence S;
the module 203 calculates N Kullback-Leibler distances, specifically: the Kth window signal sequence bKThe corresponding Kullback-Leibler distance is LKThe calculation formula is as follows:
Figure BDA0002714427020000066
wherein:
m＝1,2,···,Niis a summation serial number;
Figure BDA0002714427020000071
for the K window signal sequence bKThe m-th element of (1);
vKfor the K window signal sequence bKThe mean value of (a);
Figure BDA0002714427020000072
is the window signal sequence mean;
σKfor the K window signal sequence bKThe mean square error of (d);
Figure BDA0002714427020000073
for the K window signal sequence bK1 st element in (1);
Figure BDA0002714427020000074
for the K window signal sequence bKThe nth element of (1);
the module 204 finds a load switch event judgment threshold, specifically: the load switch event judgment threshold is as follows:
Figure BDA0002714427020000075
wherein:
snr is the signal-to-noise ratio of the signal sequence S;
the module 205 detects a load switch event, specifically: if the K-th Kullback-Leibler distance LKIf the signal is greater than or equal to the load switch event judgment threshold value, detecting a load at the Kth point of the signal sequence SA switching event; otherwise no load switch event is detected.
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:
step 301, acquiring a signal sequence S acquired according to a time sequence;
step 302 generates N window signal sequences, specifically: the Kth window signal sequence is bKThe nth element thereof is
Figure BDA0002714427020000076
The formula is obtained as follows:
Figure BDA0002714427020000077
wherein:
Figure BDA00027144270200000710
is the | K + n-M |' of the signal sequence SNAn element;
k is 1,2, N is a window serial number;
n is the length of the signal sequence S;
|K+n-M|Nrepresenting the residue removal of K + N-M by taking N as a modulus;
Figure BDA0002714427020000078
is a delay factor;
Figure BDA0002714427020000079
represents rounding on;
is any parameter;
σ0: the mean square error of the signal sequence S;
SNR: the signal-to-noise ratio of the signal sequence S;
step 303 finds NThe Kullback-Leibler distance specifically comprises the following steps: the Kth window signal sequence bKThe corresponding Kullback-Leibler distance is LKThe calculation formula is as follows:
Figure BDA0002714427020000081
wherein:
m＝1,2,···,Niis a summation serial number;
Figure BDA0002714427020000082
for the K window signal sequence bKThe m-th element of (1);
vKfor the K window signal sequence bKThe mean value of (a);
Figure BDA0002714427020000083
is the window signal sequence mean;
σKfor the K window signal sequence bKThe mean square error of (d);
Figure BDA0002714427020000084
for the K window signal sequence bK1 st element in (1);
Figure BDA0002714427020000085
for the K window signal sequence bKThe nth element of (1);
step 304, obtaining a load switch event judgment threshold, specifically: the load switch event judgment threshold is as follows:
Figure BDA0002714427020000086
wherein:
snr is the signal-to-noise ratio of the signal sequence S;
step 305 detects a load switch event, specifically: if the K-th Kullback-Leibler distance LKIf the judgment threshold value is greater than or equal to the load switch event judgment threshold value, detecting a load switch event at the Kth point of the signal sequence S; otherwise no load switch event is detected.
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 (2)

1. A load switch event detection method using a KULLBACK-Leibler distance is characterized by comprising the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102 generates N window signal sequences, specifically: the Kth window signal sequence is bKThe nth element thereof is
Figure FDA0002714427010000011
The formula is obtained as follows:
Figure FDA0002714427010000012
wherein:
Figure FDA0002714427010000013
is the | K + n-M |' of the signal sequence SNAn element;
k is 1,2, N is a window serial number;
n is the length of the signal sequence S;
|K+n-M|Nrepresenting the residue removal of K + N-M by taking N as a modulus;
Figure FDA0002714427010000014
is a delay factor;
Figure FDA0002714427010000015
represents rounding on;
is any parameter;
σ0: the mean square error of the signal sequence S;
SNR: the signal-to-noise ratio of the signal sequence S;
step 103, calculating N Kullback-Leibler distances, specifically: the Kth window signal sequence bKThe corresponding Kullback-Leibler distance is LKThe calculation formula is as follows:
Figure FDA0002714427010000016
wherein:
m＝1,2,···,Niis a summation serial number;
Figure FDA0002714427010000017
for the K window signal sequence bKThe m-th element of (1);
vKfor the K window signal sequence bKThe mean value of (a);
Figure FDA0002714427010000018
is the window signal sequence mean;
σKfor the K window signal sequence bKThe mean square error of (d);
Figure FDA0002714427010000019
for the K window signal sequence bK1 st element in (1);
Figure FDA00027144270100000110
for the K window signal sequence bKThe nth element of (1);
step 104, obtaining a load switch event judgment threshold, specifically: the load switch event judgment threshold is as follows:
Figure FDA00027144270100000111
wherein:
snr is the signal-to-noise ratio of the signal sequence S;
step 105, detecting a load switch event, specifically: if the K-th Kullback-Leibler distance LKIf the judgment threshold value is greater than or equal to the load switch event judgment threshold value, detecting a load switch event at the Kth point of the signal sequence S; otherwise no load switch event is detected.
2. A load switch event detection system using KUllback-Leibler distance, comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 generates N window signal sequences, specifically: the Kth window signal sequence is bKThe nth element thereof is
Figure FDA0002714427010000021
The formula is obtained as follows:
Figure FDA0002714427010000022
wherein:
Figure FDA0002714427010000023
is the | K + n-M |' of the signal sequence SNAn element;
k is 1,2, N is a window serial number;
n is the length of the signal sequence S;
|K+n-M|Nrepresenting the residue removal of K + N-M by taking N as a modulus;
Figure FDA0002714427010000024
is a delay factor;
Figure FDA0002714427010000025
represents rounding on;
is any parameter;
σ0: the mean square error of the signal sequence S;
SNR: the signal-to-noise ratio of the signal sequence S;
the module 203 calculates N Kullback-Leibler distances, specifically: the Kth window signal sequence bKThe corresponding Kullback-Leibler distance is LKThe calculation formula is as follows:
Figure FDA0002714427010000026
wherein:
m＝1,2,···,Niis a summation serial number;
Figure FDA0002714427010000027
for the K window signal sequence bKThe m-th element of (1);
vKfor the K window signal sequence bKThe mean value of (a);
Figure FDA0002714427010000028
is the window signal sequence mean;
σKfor the K window signal sequence bKThe mean square error of (d);
Figure FDA0002714427010000029
for the K window signal sequence bK1 st element in (1);
Figure FDA00027144270100000210
for the K window signal sequence bKThe nth element of (1);
the module 204 finds a load switch event judgment threshold, specifically: the load switch event judgment threshold is as follows:
Figure FDA00027144270100000211
wherein:
snr is the signal-to-noise ratio of the signal sequence S;
the module 205 detects a load switch event, specifically: if the K-th Kullback-Leibler distance LKIf the judgment threshold value is greater than or equal to the load switch event judgment threshold value, detecting a load switch event at the Kth point of the signal sequence S; otherwise no load switch event is detected.
CN202011068035.0A 2020-10-08 2020-10-08 Load switch event detection method and system by using KULLBACK-Leibler distance Withdrawn CN112180153A (en)

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