Method and device for detecting an electric arc in a photovoltaic installation

Patent metadata

Field	Value
Publication number	US-10073129-B2
Application number	US-201414769561-A
Country	US
Kind code	B2
Filing date	Feb 21, 2014
Priority date	Feb 22, 2013
Publication date	Sep 11, 2018
Grant date	Sep 11, 2018

Abstract

Method for detecting an electric arc in a photovoltaic installation, characterized in that it comprises the following steps:
Measurement (E 6 ) of voltage values at at least one site of the electrical circuit of the photovoltaic installation; Digitization (E 8 ) of the measured voltage values so as to form a data sampling x; Computation (E 10 ) of a first indicator of presence of an electric arc, on the basis of a statistical computation on the data sampling x, from among the variance, a value analogous to the variance, or the interquartile range of the data sampling; Computation (E 10 ) of a second indicator of presence of an electric arc, on the basis of a statistical computation on the data sampling based on one or more estimations of the mean and/or of the median of the data sampling; Comparison (E 12 ) of the first and second indicators of presence of an electric arc with respective thresholds so as to deduce therefrom the presence or absence of an electric arc within the photovoltaic installation.

First claim

The invention claimed is:

1. Method for detecting an electric arc in a photovoltaic installation, comprising:
measuring voltage values at at least one site of an electrical circuit of the photovoltaic installation;
digitizing the measured voltage values so as to form a data sampling x;
computing a first indicator of presence of the electric arc, based on a first statistical computation on the data sampling, wherein the first statistical computation is based on one or more estimations selected from the group consisting of a variance, a value analogous to the variance, and an interquartile range of the data sampling;
computing a second indicator of presence of the electric arc, based on a second statistical computation on the data sampling, wherein the second statistical computation is based on one or more estimations selected from the group consisting of a mean and a median of the data sampling;
comparing the first and second indicators of presence of the electric arc with respective first and second thresholds so as to deduce therefrom a presence or absence of the electric arc within the photovoltaic installation.

2. Method for detecting an electric arc in a photovoltaic installation according to claim 1 , which takes into account a forgetting factor Φ, wherein at least one selected from the group consisting of (i) the computing of the first indicator of presence of the electric arc is based on the value analogous to the variance and takes into account the forgetting factor Φ, and (ii) the computing of the second indicator of presence of the electric arc takes into account the forgetting factor Φ.

3. Method for detecting an electric arc in a photovoltaic installation according to claim 2 , wherein the forgetting factor is combined with each sampling datum x so as to make it possible to define an ever smaller weight to the oldest data of the data sampling at each iteration, so as to take into account the history of the measured voltage values and focus an algorithm on a near time period.

4. Method for detecting an electric arc in a photovoltaic installation according to claim 2 , wherein the forgetting factor depends on a sampling frequency.

5. Method for detecting an electric arc in a photovoltaic installation according to claim 4 , wherein the forgetting factor is constant and chosen by complying with the rules defined by the following table:

Sampling frequency F smp
Forgetting factor Φ lies in the interval

 50-300 kHz inclusive
[0.965; 0.975]

301-750 kHz inclusive
[0.975; 0.985]

751 KHz-8 Mhz inclusive
[0.985; 0.995].

6. Method for detecting an electric arc in a photovoltaic installation according to claim 1 , wherein the computing of the first indicator of presence of the electric arc comprises computing three variables a, b, c at each iteration providing a new sampling datum x, by taking account of the history of the variables a, b, c, the square of the new sampling datum x 2 and the new sampling datum x.

7. Method for detecting an electric arc in a photovoltaic installation according to claim 6 , wherein the computation of the first indicator of presence of the electric arc implements the following computations, repeated for each digitized sampling datum x:
the three variables a, b, and c are recomputed in the following manner, based on previous values of the three variables a, b and c:
a←Φa+x 2
b←Φb+x
c←Φc+ 1

thereafter, the first indicator y of presence of the electric arc is computed based on a formula:

y
=

a
-

b
2

/
c

c
-
5

.

8. Method for detecting an electric arc in a photovoltaic installation according to claim 1 , wherein the computation of the second indicator of presence of the electric arc implements the following computations, repeated for each digitized sampling datum x:
two variables b and c are recomputed in the following manner, based on previous values of these variables b and c:
b←Φb+x
c←Φc+ 1

wherein Φ is a forgetting factor lying between 0 and 1 inclusive,
thereafter, the second indicator m of presence of the electric arc is computed based on a formula:
m=b/c.

9. Method for detecting an electric arc in a photovoltaic installation according to claim 1 , wherein the second indicator of presence of the electric arc is computed based on a combination of two high and low frequency estimations of the mean of the sampling data.

10. Method for detecting an electric arc in a photovoltaic installation according to claim 9 , wherein the computation of the second indicator of presence of the electric arc implements the following computations, repeated for each digitized sampling datum x:
two variables b and c are recomputed in the following manner, based on previous values of these variables b and c:
b←Φb+x
c←Φc+ 1

wherein Φ is a forgetting factor lying between 0 and 1 inclusive,
thereafter, a first high-frequency mean estimation m HF is computed based on a formula:

m
HF

=

b
c

and a second low-frequency mean estimation m LF is computed based on a formula:
m LF =ψm LF +(1−ψ) m HF

wherein ψ represents a second forgetting factor lying between 0.9 and 1 inclusive or defined as a function of the sampling frequency by the following table;

Sampling frequency F smp
Forgetting factor Ψ lies in the interval

 50-300 kHz inclusive
[0.9; 1]

301-750 kHz inclusive
[0.95; 1]

751 KHz-8 Mhz
[0.99; 1].

then the second indicator is computed based on a difference between the high-frequency mean estimation m HF and the low-frequency mean estimation m LF .

11. Method for detecting an e

Assignees

• Commissariat Energie Atomique

Inventors

• Chaintreuil Nicolas
• Gouy-Pailler Cédric
• Lespinats Sylvain
• Plissonnier Alexandre

Classifications

• H02H3/16

  responsive to fault current to earth, frame or mass (with balanced or differential arrangement H02H3/26 {; monitoring earth connection H02H5/105}) · CPC title

• H02S50/10 Primary

  Testing of PV devices, e.g. of PV modules or single PV cells (testing of semiconductor devices during manufacturing {H10P74/00}) · CPC title

• G01R31/025 Primary

  Physics · mapped topic

• G01R31/52

  Testing for short-circuits, leakage current or ground faults · CPC title

• Y02E10/50

  Photovoltaic [PV] energy · CPC title