Citation:
@online{DatabaseRTE, author = {Presvôts, Corentin and Prevost, Thibault},
title = {Database of Voltage and Current Samples Values from the French Electricity Transmission Grid, Réseau de Transport d'Electricité (RTE), France}, url = {[https://github.com/rte-france/digital-fault-recording-database/](https://github.com/rte-france/digital-fault-recording-database/)}, year = {2024}, }
As we are presently encountering quota issues with the biggest file download, you can go to : https://dfrdb.rte-france.com/ to download the files.
This database comprises 12053 measured voltage and current waveform signals (phase-ground) on high voltage lines of the French electricity transmission grid during various faults.
All signals are stored in a list DATA_S of shape (12053, 6, 21000)
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12053 number of observed faults
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6 signals per observed fault (v1, v2, v3, i1, i2, i3)
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21000 samples per signal (3.28125s)
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Nominal frequency of the network 50 Hz
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Nominal voltage 90 kV
These signals are only a subset of all faults recorded, selected on waveform shape.
The sampling frequency is 6400 Hz
The number of bits to encode a sample is 16 bits
Quantization levels range from -32767 to 32767
The quantization step size for voltage signals is 18.310 V
The quantization step size for current signals is 4.314 A
The lists DATA_u and DATA_i are vectors of voltage and current signals derived from DATA_S.
DATA_u and DATA_i contain 30000 signals of size 128 samples, corresponding to one period of the nominal frequency of the network at 50 Hz.
To obtain DATA_u and DATA_i, each voltage signal is temporelly segmented into 128 samples. A transient selection criterion is applied to each segment. The signal is kept if:
- the standard deviation of the signal is greater than 100 times the quantization step (to remove windows where the signal amplitude changes little)
- if the mean absolute value of the signal is greater than 2000 V
If the voltage signal are retained, the current signal are also retained. DATA_u[k] and DATA_i[k] are therefore derived from the observation of the same conductor.
Download the npz files DATA_S, DATA_u and DATA_i.
Space required to download the databases :
DATA_S.npz : 2 GB
DATA_u.npz : 10 MB
DATA_i.npz : 5 MB
then with python run
import numpy as np
import matplotlib.pyplot as plt
DATA_S_load = np.load('DATA_S.npz')['DATA_S'] # Load DATA_S from the npz file
DATA_u_load = np.load('DATA_u.npz')['DATA_u'] # Load DATA_u from the npz file
DATA_i_load = np.load('DATA_i.npz')['DATA_i'] # Load DATA_i from the npz file
## test
print("DATA_S_load",np.shape(DATA_S_load))
print("DATA_u_load",np.shape(DATA_u_load))
print("DATA_i_load",np.shape(DATA_i_load))
t=np.linspace(0,(21000-1)/6400,21000)
for k in range(10):
fig=plt.figure(figsize=(15,5),dpi=100)
for i in range(3):
plt.plot(t,DATA_S_load[k][i]*18.310,lw=2,label='v{}'.format(i+1))
plt.xlabel('t (s)')
plt.ylabel('Voltage (V)')
plt.grid( which='major', color='#666666', linestyle='-')
plt.legend()
plt.minorticks_on()
fig=plt.figure(figsize=(15,5),dpi=100)
for i in range(3):
plt.plot(t,DATA_S_load[k][i+3]*4.314,lw=2,label='i{}'.format(i+1))
plt.xlabel('t (s)')
plt.ylabel('Courrent (A)')
plt.grid( which='major', color='#666666', linestyle='-')
plt.legend()
plt.minorticks_on()
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numpy
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matplotlib.pyplot