CN109409726A - A kind of non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number - Google Patents
A kind of non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number Download PDFInfo
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Abstract
The invention discloses a kind of non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number.On the basis of the existing non-intrusion type load identification technique based on the identification of P-Q load characteristic, construct a kind of using finite link in discrete-time fuzzy number as the opinion rating method of foundation；Meanwhile discrete-time fuzzy matrix number is established with the evaluation method based on probability statistics；Associate(d) matrix mass center and the weight proportion of judgment criteria form final evaluation of estimate, by the evaluation of estimate size criterion for being converted to load object apart from criterion of P-Q feature, realize the identification of load.Non-intrusion type by using present invention design and thought meets discrimination method, with the identification mistake decreased or even eliminated between the similar features equipment as caused by the influence of the factors such as voltage, current fluctuation, the integrity problem of non-intrusion type load identification technique is solved, also provides a kind of new solution to promote distribution side smart grid.
Description
Technical field
The invention belongs to electric loads to decompose, load identification algorithm field, and in particular to a kind of fuzzy based on two-dimensional discrete
Several non-intrusion type load discrimination methods.
Background technique
Electric load monitoring can be using intrusive and non-intrusion type device.It is wanted compared to intrusive load monitoring technology
It asks and sensor is installed on each electrical equipment route of subscriber household, non-intrusive electrical load monitoring technology is a kind of by biography
Sensor, which is installed only at custom power entrance, can be obtained the technology of the information such as each electrical equipment switching state, energy consumption.With peace
Fill the advantages that convenient, low in cost, consumers' acceptable degree is high.
Electrical equipment all has unique part throttle characteristics when being turned on or off, such as active and reactive etc., so that load
Decomposition can realize hard measurement by way of " soft com-puting ".Wherein steady state characteristic is that a kind of the most key label of load decomposition is special
Sign.Some researchers identify electrical equipment according to active power single features at first, this is for large power-consuming equipment, tool
There is higher identification capability, however to small-power electrical equipment, identification precision is simultaneously not bery high.It is other such as reactive powers, steady
State harmonic wave etc. is also widely applied in practical projects.
However, the identification of electrical equipment switching, in addition to electrical equipment label characteristics it is closely related other than, also with it is subsequent
Identification algorithm is related.In engineering practice, P-Q (P is active power and Q is reactive power) be characterized in one kind can quick obtaining and
Effective load characteristic label, is approved by numerous researchers.However, because the interference of the factors such as voltage, electric current leads to signal wave
Dynamic, the feature of obtained P-Q feature and practical electrical equipment generates deviation, and the electrical equipment switching similar in feature is caused to recognize
When generate erroneous judgement.For this purpose, introducing two-dimensional discrete fuzzy number discrimination method herein to provide new solution for the above problem.
Summary of the invention
The technical problem to be solved by the present invention is providing a kind of non-intrusion type load identification based on two-dimensional discrete fuzzy number
Method, solving above-mentioned interfere in the identification of non-intrusion type load because of factors such as voltage, electric currents leads to signal fluctuation, so that P-Q is negative
The feature of lotus label characteristics and practical electrical equipment generates deviation, generation when the electrical equipment switching similar in feature being caused to recognize
The defect of erroneous judgement.
Of the invention is mainly just technically characterized in that present invention introduces discrete-time fuzzy number discrimination method, to special based on P-Q
The electric load of sign realizes the identification of non-intrusion type load.
Purpose to realize the present invention, using following steps:
A kind of non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number, which is characterized in that
Step 1: using the power information of the method acquisition electrical equipment of non-intrusion type, and carrying out electric load feature P-Q
The extraction of feature；
Step 2: constructing a kind of using finite link in discrete-time fuzzy number as the opinion rating method of foundation；Meanwhile to be based on
The evaluation method of probability statistics establishes discrete-time fuzzy matrix number；
Step 3: associate(d) matrix mass center and the weight proportion of judgment criteria form final evaluation of estimate, by the distance of P-Q feature
Criterion is converted to the evaluation of estimate size criterion of load object, realizes the identification of load.
In a kind of above-mentioned non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number, step 2, establish discrete
The specific method of Fuzzy number matrix is:
Definition has n electrical equipment A1,A2,…AnNeed to assess, and each equipment is there are P-Q feature, establish two dimension from
Dissipate fuzzy number
Wherein Ai1,Ai2The discrete-time fuzzy number of active P and idle Q are respectively measured, m is evaluation coefficient grade, xijkIt is pair
As Ai(i=1,2 ... evaluation points n)；For Ai1,Ai2Construction, define matrix about discrete-time fuzzy numberFor
In formula: l ij =min k | xijk≠ 0, k=1,2 ... m }, Here it provides
k0It is in set L closest to average value mu (Aij) numerical value, i.e.,
k0={ k ∈ L:| k- μ (Aij) |≤0.5 } formula (3)
Wherein mean μ (Aij) be
It is especially noted that meeting when median of the mean value between k and k+1 | k- μ (Aij) |=0.5 He | k
+1-μ(Aij) |=0.5, at this timeIt may be modified such that:
In a kind of above-mentioned non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number, the step 3, most
The acquisition methods of final review value are:
It is available by formula (2) (3) (4) (5)For
Therefore, to any X=(x1,x2)∈R2, the value for defining i-th of object in a matrix is
The square matrix of m dimension is obtained, i.e.,
Then the mass center of each object is obtained by centroid calculation
In view of practical application, obtained finally in conjunction with mass center and weight (ratio of i.e. active and idle two judgment criteria)
Evaluation of estimate；
V=p1c1+p2c2Formula (10)
The finally v value of more different objects, that maximum object of evaluation of estimate are pair being most likely to occur judged
As the i.e. electrical equipment of switching.
The invention has the benefit that P-Q dimensional feature clustering is carried out by introducing two-dimensional discrete fuzzy number, it can be very
The identification decreased or even eliminated well between the similar features equipment as caused by the influence of the factors such as voltage, current fluctuation is wrong
Accidentally, solve the integrity problem of non-intrusion type load identification technique, also for promoted distribution side smart grid provide it is a kind of new
Solution.
Specific embodiment
The present invention is understood and implemented for the ease of those of ordinary skill in the art, and the present invention is made into one below with reference to example
The detailed description of step, it should be understood that implementation example described herein is merely to illustrate and explain the present invention, and is not used to limit
The present invention.
Fuzzy set be described according to membership function, and based on membership function by Feature Conversion be degree of membership again
It is characterized.In order to preferably describe the load characteristic wave characteristic during electrical equipment switching, the present invention use from
Scattered fuzzy number is constructed.Precondition of the invention is that there are P-Q features for each equipment being identified.Tool of the invention
Body implementation steps are as follows:
It suppose there is n electrical equipment A1,A2,…AnNeed to assess, and each equipment is there are P-Q feature, establish two dimension from
Dissipate fuzzy number
Wherein Ai1,Ai2The discrete-time fuzzy number of active P and idle Q are respectively measured, m is evaluation coefficient grade, xijkIt is pair
As Ai(i=1,2 ... evaluation points n).For Ai1,Ai2Construction, the present invention defines the matrix about discrete-time fuzzy number
For
In formula: Here k is provided0It is in set L closest to average value mu (Aij) element,
I.e.
k0={ k ∈ L:| k- μ (Aij) |≤0.5 } formula (3)
Wherein mean μ (Aij) be
It is especially noted that meeting when median of the mean value between k and k+1 | k- μ (Aij) |=0.5 He | k
+1-μ(Aij) |=0.5, at this timeIt may be modified such that:
It is available by formula (2) (4) (5)For
Therefore, to any X=(x1,x2)∈R2, the value that can define i-th of object in a matrix is
The square matrix of m dimension is obtained, i.e.,
Then the mass center of each object is obtained by centroid calculation
In view of practical application, obtained finally in conjunction with mass center and weight (ratio of i.e. active and idle two judgment criteria)
Evaluation of estimate.
V=p1c1+p2c2Formula (10)
The finally v value of more different objects, that maximum object of evaluation of estimate are pair being most likely to occur judged
As the i.e. electrical equipment of switching.
In order to verify effectiveness of the invention, experiment tests kettle, refrigerator, disinfection cabinet, air-conditioning, electric heater, electricity
The switching of this seven kinds of electrical equipments of rice cooker, television set.It is practical individually to test active and reactive data and difference information such as the following table 1
It is shown.The electrical equipment that previous moment comes into operation in test process has refrigerator, disinfection cabinet, air-conditioning, electric heater, and actual measurement has
Function power is fluctuated in 1785.5W range.Then, after electric kettle being come into operation, due to the rising of power, so that inlet
Voltage is lower, and the measured power for measuring current time at this time is 2905.5W or so fluctuation.By difference, it can be found that power increases
Add the data-base recording value in 1120W or so, and table 1 that deviation has occurred.
Table 1
Load identification is carried out according to P-Q dimension Euclidean distance min cluster, according to 1 difference information of table, then identification result is
Electric heater is generated and is accidentally recognized.
In order to avoid because P and Q feature with voltage, electric current fluctuation but change caused by judge by accident, invention introduces
P-Q dimensional feature carries out the identification of two-dimensional discrete fuzzy number load.
In order to be described in detail two-dimensional discrete fuzzy number load identification realization process, in this example, first acquisition P-Q away from
From two nearest objects, i.e. kettle and electric heater, A is used1, A2It indicates.In order to assess its active-power P and reactive power Q
Part throttle characteristics considers the fuzzy language of nine kinds of grades:
Ω={ EB, VB, B, MB, F, MG, G, VG, EG }
It is described with Chinese are as follows: it does not meet, does not meet completely very much, do not meet, do not meet slightly, generally, slightly meet,
Meet, meet very much, comply fully with, therefore finite link can be described with 1~9, as L=1,2,3,4,5,6,7,8,
9}.Specific testing process are as follows:
Step 1: passing through Difference Calculation fp=1- Δ P/P, fq=1- Δ Q/Q obtains the active and idle of two electrical equipments
Probability.
Kettle: fp=0.793, fq=0.381
Electric heater: fp=0.881, fq=0.143
Step 2: Calculation Estimation grade.According to the probability that kettle and electric heater are active and idle, evaluate in 1~9 grade
In reference point.
Kettle:
Electric heater:
Then by way of generating at random, select before load switching and at the time of point after switching, thus obtain it is active and
Idle change information takes 50 random numbers (being equivalent to expert to differentiate 50 times), with the method statistic random-number distribution to round up
Situation takes 9 if being more than numerical value 9, if being less than numerical value 1 takes 1.
Step 3: generating discrete-time fuzzy number.The numerical result counted in step 2 is recorded, A can be obtained1About
The evaluation points of active-power P generate one-dimensional discrete fuzzy number A11.A similarly can be obtained12, A21, A22。
μ (A can be calculated by formula (2) (3) (4) (5) (6) (11) (12)11)=7.16, μ (A12)=4.7, μ (A21)=
7.66, μ (A22)=2.32.Correspondingly, it obtains
Step 4: construction discrete-time fuzzy matrix number.
In two-dimensional discrete fuzzy number, to arbitrary X=(x1,x2)∈R2All meet following relational expression
Then, available about discrete-time fuzzy number A according to formula (13)1, A2Matrix be
Step 5: solving A1, A2Mass center.By formula (9) it is found that the mass center of object is
Step 6: Calculation Estimation value v.P feature and Q feature are considered as to of equal importance, i.e. p=(p herein1,p2)=(0.5,
0.5), then evaluation of estimate v is finally obtained according to formula (10)1=5.77, v2=5.11.In contrast, because of v2<v1, then final to differentiate
For A1, i.e. the result of load identification is kettle, it is consistent with the equipment actually put into, to demonstrate having for methods described herein
Effect property.
Above example is merely to illustrate design philosophy and feature of the invention, and verifies effectiveness of the invention.Its purpose
It is that those skilled in the art is made to can understand the content of the present invention and implement it accordingly, protection scope of the present invention is not limited to
Examples detailed above, so, equivalent variations or modification made by all principles revealed according to the present invention, mentality of designing, in this hair
Within bright protection scope.
Claims (3)
1. a kind of non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number, which is characterized in that
Step 1: using the power information of the method acquisition electrical equipment of non-intrusion type, and carrying out electric load feature P-Q feature
Extraction；
Step 2: constructing a kind of using finite link in discrete-time fuzzy number as the opinion rating method of foundation；Meanwhile to be based on probability
The evaluation method of statistics establishes discrete-time fuzzy matrix number；
Step 3: associate(d) matrix mass center and the weight proportion of judgment criteria form final evaluation of estimate, by P-Q feature apart from criterion
The evaluation of estimate size criterion for being converted to load object, realizes the identification of load.
2. a kind of non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number according to claim 1, feature
It is, in step 2, the specific method for establishing discrete-time fuzzy matrix number is:
Definition has n electrical equipment A1,A2,…AnIt needs to assess, and there are P-Q features for each equipment, establish two-dimensional discrete mould
Paste number
Wherein Ai1,Ai2The discrete-time fuzzy number of active P and idle Q are respectively measured, m is evaluation coefficient grade, xijkIt is object Ai(i
=1,2 ... evaluation points n)；For Ai1,Ai2Construction, define matrix about discrete-time fuzzy numberFor
In formula:lij =min k | xijk≠ 0, k=1,2 ... m },L=1,2 ... m }；Here k is provided0It is in set L closest to average value mu (Aij) numerical value, i.e.,
k0={ k ∈ L:| k- μ (Aij) |≤0.5 } formula (3)
Wherein mean μ (Aij) be
It is especially noted that meeting when median of the mean value between k and k+1 | k- μ (Aij) |=0.5 He | k+1- μ
(Aij) |=0.5, at this timeIt may be modified such that:
3. a kind of non-intrusion type load discrimination method based on two-dimensional discrete fuzzy number according to claim 1, feature
It is, in the step 3, the acquisition methods of final evaluation of estimate are:
It is available by formula (2) (3) (4) (5)For
Therefore, to any X=(x1,x2)∈R2, the value for defining i-th of object in a matrix is
The square matrix of m dimension is obtained, i.e.,
Then the mass center of each object is obtained by centroid calculation
In view of practical application, finally evaluated in conjunction with mass center and weight (ratio of i.e. active and idle two judgment criteria)
Value；
V=p1c1+p2c2Formula (10)
The finally v value of more different objects, that maximum object of evaluation of estimate are the object being most likely to occur judged, i.e.,
The electrical equipment of switching.
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| CN110907762A (en) * | 2019-12-10 | 2020-03-24 | 深圳供电局有限公司 | Non-invasive load matching identification method |
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Application publication date: 20190301 |