CN111948477A - Load switch event detection method and system by utilizing fixed B sampling - Google Patents

Abstract

The embodiment of the invention discloses a load switch event detection method and a system by utilizing fixed B sampling, wherein the method comprises the following steps: step 101, acquiring a signal sequence S acquired according to a time sequence; step 102, generating a signal first-order difference sequence; step 103, obtaining N fixed B sampling factors; step 104, obtaining N fixed B sampling translation factors; step 105, obtaining N fixed B sampling envelope factors; step 106, obtaining N fixed B sampling functions; step 107, obtaining a load switch event judgment threshold; step 108 determines a load switch event.

Description

Load switch event detection method and system by utilizing fixed B sampling

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 fixed B sampling. 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 method of load switch event detection with fixed B sampling, comprising:

step 101, acquiring a signal sequence S acquired according to a time sequence;

step 102 generates a first order difference sequence of signals, specifically: the first order difference sequence of the signal is Delta S, and the ith element is Delta S_iThe calculation formula is

Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; s_iIs the ith element of the signal sequence S;

is the | i +1| > th of the signal sequence S_NAn element; i +1| non-woven hair_NRepresenting the remainder operation modulo N;

step 103, obtaining N fixed B sampling factors, specifically: the nth fixed B sampling factor is q_nHaving a value of

Wherein m is₀Is the mean of the signal sequence S; m is_ΔSIs the signal first order difference sequence; Δ f is the sampling frequency of the signal sequence S; sigma₀Is the mean square error of the signal sequence S;

step 104, obtaining N fixed B sampling translation factors, specifically: the nth fixed B sample shift factor is m_nHaving a value of

Wherein snr is the signal-to-noise ratio of the signal sequence S;

step 105, obtaining N fixed B-sample envelope factors, specifically: the nth fixed B-sample envelope factor is g_nHaving a value of

Step 106, obtaining N fixed B sampling functions, specifically: the nth fixed B sampling function is H_nThe calculation formula is

Step 107, obtaining a load switch event judgment threshold, specifically: the threshold for judging the load switch event is recorded as₀The calculation formula is

Step 108, judging a load switch event, specifically: if the nth fixed B sampling function H_nGreater than or equal to the load switch event judgment threshold₀Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.

A load switch event detection system using fixed B sampling, comprising:

the module 201 acquires a signal sequence S acquired in time sequence;

the module 202 generates a first order difference sequence of signals, specifically: first order of signalThe differential sequence is Δ S, and the ith element is Δ S_iThe calculation formula is

Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; s_iIs the ith element of the signal sequence S;

is the | i +1| > th of the signal sequence S_NAn element; i +1| non-woven hair_NRepresenting the remainder operation modulo N;

the module 203 finds N fixed B sampling factors, specifically: the nth fixed B sampling factor is q_nHaving a value of

Wherein m is₀Is the mean of the signal sequence S; m is_ΔSIs the signal first order difference sequence; Δ f is the sampling frequency of the signal sequence S; sigma₀Is the mean square error of the signal sequence S;

the module 204 finds N fixed B sample translation factors, specifically: the nth fixed B sample shift factor is m_nHaving a value of

Wherein snr is the signal-to-noise ratio of the signal sequence S;

the module 205 finds N fixed B-sample envelope factors, specifically: the nth fixed B-sample envelope factor is g_nHaving a value of

Module 206 finds N fixed B sampling functions, specifically: the nth fixed B sampling function is H_nThe calculation formula is

The module 207 finds a load switch event judgment threshold, specifically: the threshold for judging the load switch event is recorded as₀The calculation formula is

The module 208 determines a load switch event, specifically: if the nth fixed B sampling function H_nGreater than or equal to the load switch event judgment threshold₀Detecting a load switch event at the nth point of the signal sequence; 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 fixed B sampling. 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 flow diagram of a load switch event detection method using fixed B samples

Fig. 1 is a flow chart illustrating a load switch event detection method using fixed B sampling according to the present invention. As shown in fig. 1, the load switch event detection method using fixed B sampling specifically includes the following steps:

step 101, acquiring a signal sequence S acquired according to a time sequence;

step 102 generates a first order difference sequence of signals, specifically: the first order difference sequence of the signal is Delta S, and the ith element is Delta S_iThe calculation formula is

Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; s_iIs the ith element of the signal sequence S;

is the | i +1| > th of the signal sequence S_NAn element; i +1| non-woven hair_NRepresenting the remainder operation modulo N;

step 103 of obtaining N number of solidsB sampling factors are determined, and specifically: the nth fixed B sampling factor is q_nHaving a value of

Wherein m is₀Is the mean of the signal sequence S; m is_ΔSIs the signal first order difference sequence; Δ f is the sampling frequency of the signal sequence S; sigma₀Is the mean square error of the signal sequence S;

step 104, obtaining N fixed B sampling translation factors, specifically: the nth fixed B sample shift factor is m_nHaving a value of

Wherein snr is the signal-to-noise ratio of the signal sequence S;

step 105, obtaining N fixed B-sample envelope factors, specifically: the nth fixed B-sample envelope factor is g_nHaving a value of

Step 106, obtaining N fixed B sampling functions, specifically: the nth fixed B sampling function is H_nThe calculation formula is

Step 107, obtaining a load switch event judgment threshold, specifically: the threshold for judging the load switch event is recorded as₀The calculation formula is

Step 108, judging a load switch event, specifically: if the nth fixed B sampling function H_nGreater than or equal to the load switch event judgment threshold₀Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.

FIG. 2 is a schematic diagram of a load switch event detection system using fixed B samples

Fig. 2 is a schematic diagram of a load switch event detection system using fixed B sampling according to the present invention. As shown in fig. 2, the load switch event detection system using fixed B sampling includes the following structure:

the module 201 acquires a signal sequence S acquired in time sequence;

the module 202 generates a first order difference sequence of signals, specifically: the first order difference sequence of the signal is Delta S, and the ith element is Delta S_iThe calculation formula is

Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; s_iIs the ith element of the signal sequence S;

is the | i +1| > th of the signal sequence S_NAn element; i +1| non-woven hair_NRepresenting the remainder operation modulo N;

the module 203 finds N fixed B sampling factors, specifically: the nth fixed B sampling factor is q_nHaving a value of

Wherein m is₀Is the mean of the signal sequence S; m is_ΔSIs the signal first order difference sequence; Δ f is the sampling frequency of the signal sequence S; sigma₀Is the mean square error of the signal sequence S;

the module 204 finds N fixed B sample translation factors, specifically: the nth fixed B sample shift factor is m_nHaving a value of

Wherein snr is the signal-to-noise ratio of the signal sequence S;

the module 205 finds N fixed B-sample envelope factors, specifically: the nth fixed B-sample envelope factor is g_nHaving a value of

Module 206 finds N fixed B sampling functions, specifically: the nth fixed B sampling function is H_nThe calculation formula is

The module 207 finds a load switch event judgment threshold, specifically: the threshold for judging the load switch event is recorded as₀The calculation formula is

The module 208 determines a load switch event, specifically: if the nth fixed B sampling function H_nGreater than or equal to the load switch event judgment threshold₀Detecting a load switch event at the nth point of the signal sequence; 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 a first order difference sequence of signals, specifically: the first order difference sequence of the signal is Delta S, and the ith element is Delta S_iThe calculation formula is

Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; s_iIs the ith element of the signal sequence S;

is the | i +1| > th of the signal sequence S_NAn element;|i+1|_Nrepresenting the remainder operation modulo N;

step 303 finds N fixed B sampling factors, specifically: the nth fixed B sampling factor is q_nHaving a value of

Wherein m is₀Is the mean of the signal sequence S; m is_ΔSIs the signal first order difference sequence; Δ f is the sampling frequency of the signal sequence S; sigma₀Is the mean square error of the signal sequence S;

step 304, obtaining N fixed B sampling translation factors, specifically: the nth fixed B sample shift factor is m_nHaving a value of

Wherein snr is the signal-to-noise ratio of the signal sequence S;

step 305 finds N fixed B-sample envelope factors, specifically: the nth fixed B-sample envelope factor is g_nHaving a value of

Step 306, obtaining N fixed B sampling functions, specifically: the nth fixed B sampling function is H_nThe calculation formula is

Step 307, obtaining a load switch event judgment threshold, specifically: the threshold for judging the load switch event is recorded as₀The calculation formula is

Step 308, judging a load switch event, specifically: if the nth fixed B sampling function H_nGreater than or equal to the load switch event judgment threshold₀Detecting a load switch event at the nth point of the signal sequence; 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 method of load switch event detection using fixed B samples, comprising:

step 101, acquiring a signal sequence S acquired according to a time sequence;

step 102 generates a first order difference sequence of signals, specifically: the first order difference sequence of the signal is Delta S, and the ith element is Delta S_iThe calculation formula is

Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; s_iIs the ith element of the signal sequence S;

is the | i +1| > th of the signal sequence S_NAn element; i +1| non-woven hair_NRepresenting the remainder operation modulo N;

step 103, obtaining N fixed B sampling factors, specifically: the nth fixed B sampling factor is q_nHaving a value of

Wherein m is₀Is the mean of the signal sequence S; m is_ΔSIs the signal first order difference sequence; Δ f is the sampling frequency of the signal sequence S; sigma₀Is the mean square error of the signal sequence S;

step 104, obtaining N fixed B sampling translation factors, specifically: the nth fixed B sample shift factor is m_nHaving a value of

Wherein snr is the signal-to-noise ratio of the signal sequence S;

step 105, obtaining N fixed B-sample envelope factors, specifically: the nth fixed B-sample envelope factor is g_nHaving a value of

Step 106, obtaining N fixed B sampling functions, specifically: the nth fixed B sampling function is H_nThe calculation formula is

Step 107, obtaining a load switch event judgment threshold, specifically: the threshold for judging the load switch event is recorded as₀The calculation formula is

Step 108, judging a load switch event, specifically: if the nth fixed B sampling function H_nGreater than or equal to the load switch event judgment threshold₀Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.

2. A load switch event detection system using fixed B sampling, comprising:

the module 201 acquires a signal sequence S acquired in time sequence;

the module 202 generates a first order difference sequence of signals, specifically: the first order difference sequence of the signal is Delta S, and the ith element is Delta S_iThe calculation formula is

Wherein, i is an element signal, and the value range of i is 1, ·, N; n is a sequence number of the difference sequence, and the value range of N is 1,2, ·, N; n is the length of the signal sequence S; s_iIs the ith element of the signal sequence S;

is the | i +1| > th of the signal sequence S_NAn element; i +1| non-woven hair_NRepresenting the remainder operation modulo N;

the module 203 finds N fixed B sampling factors, specifically: the nth fixed B sampling factor is q_nHaving a value of

Wherein m is₀Is the mean of the signal sequence S; m is_ΔSIs the signal first order difference sequence; Δ f is the sampling frequency of the signal sequence S; sigma₀Is the mean square error of the signal sequence S;

the module 204 finds N fixed B sample translation factors, specifically: the nth fixed B sample shift factor is m_nHaving a value of

Wherein snr is the signal-to-noise ratio of the signal sequence S;

the block 205 finds N fixed B-sample envelope factors, in particular: the nth fixed B-sample envelope factor is g_nHaving a value of

Module 206 finds N fixed B sampling functions, specifically: the nth fixed B sampling function is H_nThe calculation formula is

The module 207 finds a load switch event judgment threshold, specifically: the threshold for judging the load switch event is recorded as₀The calculation formula is

The module 208 determines a load switch event, specifically: if the nth fixed B sampling function H_nGreater than or equal to the load switch event judgment threshold₀Detecting a load switch event at the nth point of the signal sequence; otherwise, no load switch event is detected.

Images