nem-writer
Write meter readings to AEMO NEM12 (interval metering data) and NEM13 (accumulated metering data) data files
Accumulated Data (NEM13)
from datetime import datetime
from nemwriter import NEM13
m = NEM13(to_participant='123')
ch = m.add_reading(nmi='123',
nmi_configuration='E1B1B2',
register_id='1',
nmi_suffix='E1',
previous_read=412,
previous_read_date=datetime(2017,1,1),
previous_quality_method='A',
current_read=512,
current_read_date=datetime(2017,2,1),
current_quality_method='A',
quantity=100,
uom='kWh'
)
output = m.output_csv(file_path='output.csv')Will output:
100,NEM13,201701010101,,123
250,123,E1B1B2,1,E1,,,E,412,201701010000,A,,,512,201702010000,A,,,100,kWh,,,
900
Interval Data (NEM12)
from datetime import datetime
from nemwriter import NEM12
m = NEM12(to_participant='123')
readings = [
# read end, read value, quality method, event code, event desc
[datetime(2004, 4, 18, 0, 30), 10.1, 'A', 79, 'Power Outage Alarm'],
[datetime(2004, 4, 18, 1, 0), 11.2, 'A'],
[datetime(2004, 4, 18, 1, 30), 12.3, 'A'],
[datetime(2004, 4, 18, 2, 0), 13.4, 'A'],
]
ch = m.add_readings(nmi='123',
nmi_configuration='E1B1B2',
nmi_suffix='E1', uom='kWh',
readings=readings)
output = m.output_csv(file_path='output.csv')Will output:
100,NEM12,201701010101,,123
200,123,E1B1B2,,E1,,,kWh,30,
300,20040418,10.1,11.2,12.3,13.4,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,V,,,,
400,1,1,A,79,Power Outage Alarm
400,2,48,A,,
900
Alternatively, save as a compressed csv in a zip file.
output = m.output_zip(file_path='output.zip')From Pandas DataFrame
If you create a pandas DataFrame, for example:
num_intervals = 288
index = [datetime(2004, 4, 1) + timedelta(minutes=5*x) for x in range(1,num_intervals+1)]
e1 = [randrange(1,10) for x in range(1,num_intervals+1)]
e2 = [randrange(1,5) for x in range(1,num_intervals+1)]
s1 = pd.Series(data=e1, index=index, name="E1")
s2 = pd.Series(data=e2, index=index, name="E2")
df=pd.concat([s1,s2],axis=1)
print(df) E1 E2
2004-04-01 00:05:00 2 3
2004-04-01 00:10:00 8 3
2004-04-01 00:15:00 7 2
2004-04-01 00:20:00 4 3
2004-04-01 00:25:00 3 4
... .. ..
2004-04-01 23:40:00 9 2
2004-04-01 23:45:00 1 1
2004-04-01 23:50:00 6 2
2004-04-01 23:55:00 7 1
2004-04-01 00:00:00 4 2
You can easily output the dataframe to a NEM12 file:
m = NEM12(to_participant='123')
m.add_dataframe(nmi='123', interval=5, df=df, uoms={'E1': 'kWh', 'E2': 'kWh'})
output = m.output_csv(file_path='output.csv')If your DataFrame has a Quality and EventDesc column, they will also be handled appropriately.
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