Electric loads data accessor and multi-sector load data tool
See https://www.eudoxys.com/loads
pip install git+https://github.com/eudoxys/loads
To update the documentation run the command
make docs
To rebuild the cache run the command
make cache
To save the cache run the command
cache backup -f filename.tar.gz
To restore the cache run the command
cache resetore -f filename.tar.gz
Get the Alameda county California residential load data
loads print -S=CA -C=Alameda
Outputs
elec_baseload_MW elec_cooling_MW elec_dg_MW elec_heating_MW elec_net_MW elec_total_MW nonelec_baseload_MW nonelec_cooling_MW nonelec_heating_MW nonelec_total_MW
timestamp
2018-01-01 00:00:00+00:00 281.892669 1.7496 -1.0535 2.0579 284.646669 285.700069 509.669469 0.0049 34.3793 544.053669
2018-01-01 01:00:00+00:00 289.359369 1.1131 0.0000 2.4693 292.941769 292.941769 513.807569 0.0034 40.0684 553.879369
2018-01-01 02:00:00+00:00 295.018669 0.6803 0.0000 3.7304 299.429369 299.429369 515.856769 0.0029 49.9559 565.815669
.
.
.
2018-12-31 21:00:00+00:00 277.309369 1.8679 -6.3966 3.3568 276.137269 282.533969 507.140169 0.0143 44.8301 551.984469
2018-12-31 22:00:00+00:00 275.588869 2.1452 -5.3423 2.8486 275.240469 280.582669 505.091169 0.0127 38.0819 543.185869
2018-12-31 23:00:00+00:00 275.565069 2.5066 -3.7245 1.8676 276.214569 279.939069 505.597969 0.0099 30.8302 536.437969
Get the COMstock data frame for medium office buildings in Alameda County CA.
from loads import COMstock
print(COMstock(state="CA",county="Alameda",building_type="CMO"))
Outputs
district_cooling district_heating district_hotwater elec_cooling ... other_watersystems other_total total floor_area
2018-01-01 00:00:00+00:00 0.0 0.0 0.0 0.248472 ... 0.001661 0.001661 2.031439 1.035391e+08
2018-01-01 01:00:00+00:00 0.0 0.0 0.0 0.148115 ... 0.000957 0.000957 1.857834 1.035391e+08
2018-01-01 02:00:00+00:00 0.0 0.0 0.0 0.112703 ... 0.001011 0.001011 1.742692 1.035391e+08
2018-01-01 03:00:00+00:00 0.0 0.0 0.0 0.091315 ... 0.000938 0.000938 1.659679 1.035391e+08
2018-01-01 04:00:00+00:00 0.0 0.0 0.0 0.079424 ... 0.000930 0.000930 1.580334 1.035391e+08
... ... ... ... ... ... ... ... ... ...
2018-12-31 19:00:00+00:00 0.0 0.0 0.0 0.332330 ... 0.003769 0.003769 2.693050 1.035391e+08
2018-12-31 20:00:00+00:00 0.0 0.0 0.0 0.356295 ... 0.004248 0.004248 2.704405 1.035391e+08
2018-12-31 21:00:00+00:00 0.0 0.0 0.0 0.390223 ... 0.004254 0.004254 2.719034 1.035391e+08
2018-12-31 22:00:00+00:00 0.0 0.0 0.0 0.396624 ... 0.004203 0.004203 2.627227 1.035391e+08
2018-12-31 23:00:00+00:00 0.0 0.0 0.0 0.367452 ... 0.004202 0.004202 2.395476 1.035391e+08
[8760 rows x 26 columns]
Get the residential building loads data frame for Alameda County CA.
from loads import Residential
print(Residential(state="CA",county="Alameda"))
Outputs
elec_baseload_MW elec_cooling_MW elec_dg_MW ... nonelec_cooling_MW nonelec_heating_MW nonelec_total_MW
timestamp ...
2018-01-01 00:00:00+00:00 45.0850 1.1091 -1.0535 ... 0.0 34.3669 46.4693
2018-01-01 01:00:00+00:00 52.1497 0.8527 0.0000 ... 0.0 40.0531 55.4907
2018-01-01 02:00:00+00:00 58.1370 0.5313 0.0000 ... 0.0 49.9345 66.6151
2018-01-01 03:00:00+00:00 55.9089 0.4585 0.0000 ... 0.0 64.5472 76.4473
2018-01-01 04:00:00+00:00 52.8237 0.3425 0.0000 ... 0.0 78.3935 88.7045
... ... ... ... ... ... ... ...
2018-12-31 19:00:00+00:00 41.0822 0.4936 -6.4541 ... 0.0 67.5158 78.7194
2018-12-31 20:00:00+00:00 41.3200 0.7251 -6.7804 ... 0.0 53.9646 65.7889
2018-12-31 21:00:00+00:00 39.1495 0.8430 -6.3966 ... 0.0 44.8131 54.6172
2018-12-31 22:00:00+00:00 37.7114 1.0330 -5.3423 ... 0.0 38.0684 45.9721
2018-12-31 23:00:00+00:00 38.2257 1.3822 -3.7245 ... 0.0 30.8190 39.2178
[8760 rows x 10 columns]
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Although a data cache is used extensively to avoid multiple/slow queries, the processing of this large amount of data can be very time-consuming.
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Some COMstock and RESstock building types have no data in some counties. In such cases, zero loads are provided. If logging is set to
DEBUGa message is output.