API to access energy data
Project description
Install — Getting Started — Method Availability — LMP Data — Supported LMP Markets — Feedback
isodata provides standardized API to access energy data from the major Independent System Operators (ISOs) in the United States.
Install
isodata supports python 3.7+. Install with pip
python -m pip install isodata
Getting Started
First, we can see all of the ISOs that are supported
>>> import isodata
>>> isodata.list_isos()
Name Id
0 California ISO caiso
1 Electric Reliability Council of Texas ercot
2 New York ISO nyiso
3 Southwest Power Pool spp
4 PJM pjm
5 Midcontinent ISO miso
6 ISO New England isone
Next, we can select an ISO we want to use
>>> iso = isodata.get_iso('caiso')
>>> caiso = iso()
All ISOs have the same API. Here is how we can get the fuel mix
>>> caiso.get_latest_fuel_mix()
ISO: California ISO
Total Production: 43104 MW
Time: 2022-08-03 18:25:00-07:00
+-------------+-------+-----------+
| Fuel | MW | Percent |
|-------------+-------+-----------|
| Natural Gas | 19868 | 46.1 |
| Solar | 5388 | 12.5 |
| Imports | 4997 | 11.6 |
| Wind | 3887 | 9 |
| Large Hydro | 3312 | 7.7 |
| Nuclear | 2255 | 5.2 |
| Batteries | 1709 | 4 |
| Geothermal | 886 | 2.1 |
| Biomass | 344 | 0.8 |
| Small hydro | 234 | 0.5 |
| Biogas | 208 | 0.5 |
| Coal | 16 | 0 |
| Other | 0 | 0 |
+-------------+-------+-----------+
or the energy demand throughout the current day as a Pandas DataFrame
>>> caiso.get_demand_today()
Time Demand
0 2022-08-03 00:00:00-07:00 30076.0
1 2022-08-03 00:05:00-07:00 29966.0
2 2022-08-03 00:10:00-07:00 29893.0
3 2022-08-03 00:15:00-07:00 29730.0
4 2022-08-03 00:20:00-07:00 29600.0
.. ... ...
219 2022-08-03 18:15:00-07:00 41733.0
220 2022-08-03 18:20:00-07:00 41690.0
221 2022-08-03 18:25:00-07:00 41718.0
222 2022-08-03 18:30:00-07:00 41657.0
223 2022-08-03 18:35:00-07:00 41605.0
[224 rows x 2 columns]
we can get today's supply in the same way
>>> caiso.get_supply_today()
Time Supply
0 2022-08-03 00:00:00-07:00 31454
1 2022-08-03 00:05:00-07:00 31366
2 2022-08-03 00:10:00-07:00 30985
3 2022-08-03 00:15:00-07:00 30821
4 2022-08-03 00:20:00-07:00 30667
.. ... ...
220 2022-08-03 18:20:00-07:00 43096
221 2022-08-03 18:25:00-07:00 43104
222 2022-08-03 18:30:00-07:00 43013
223 2022-08-03 18:35:00-07:00 42885
224 2022-08-03 18:40:00-07:00 42875
[225 rows x 2 columns]
to get data for a specific day, use the historical method calls. For example,
>>> caiso.get_historical_demand("Jan 1, 2020")
Time Demand
0 2020-01-01 00:00:00-08:00 21533
1 2020-01-01 00:05:00-08:00 21429
2 2020-01-01 00:10:00-08:00 21320
3 2020-01-01 00:15:00-08:00 21272
4 2020-01-01 00:20:00-08:00 21193
.. ... ...
284 2020-01-01 23:40:00-08:00 20383
285 2020-01-01 23:45:00-08:00 20297
286 2020-01-01 23:50:00-08:00 20242
287 2020-01-01 23:55:00-08:00 20128
288 2020-01-01 00:00:00-08:00 20025
[289 rows x 2 columns]
The best part is these APIs work across all the supported ISOs
Method Availability
Here is the current status of availability of each method for each ISO
| New York ISO | California ISO | Electric Reliability Council of Texas | ISO New England | Midcontinent ISO | Southwest Power Pool | PJM | |
|---|---|---|---|---|---|---|---|
get_latest_status |
✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
get_latest_fuel_mix |
✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
get_fuel_mix_today |
✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ |
get_fuel_mix_yesterday |
✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ |
get_historical_fuel_mix |
✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ |
get_latest_demand |
✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
get_demand_today |
✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
get_demand_yesterday |
✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ |
get_historical_demand |
✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ |
get_latest_supply |
✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
get_supply_today |
✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ✅ |
get_supply_yesterday |
✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ |
get_historical_supply |
✅ | ✅ | ❌ | ✅ | ❌ | ❌ | ✅ |
LMP Pricing Data
We are currently adding Locational Marginal Price (LMP). Even though each BA offers different markets, but you can query them with a standardized API
>>> import isodata
>>> nyiso = isodata.NYISO()
>>> nyiso.get_lmp_today("REAL_TIME_5_MIN", locations="ALL")
Time Market Location Location Type LMP Energy Congestion Loss
0 2022-08-16 00:05:00-04:00 REAL_TIME_5_MIN CAPITL Zone 70.88 66.65 1.10 5.33
1 2022-08-16 00:05:00-04:00 REAL_TIME_5_MIN CENTRL Zone 68.91 66.64 0.00 2.27
2 2022-08-16 00:05:00-04:00 REAL_TIME_5_MIN DUNWOD Zone 75.44 66.65 -1.26 7.53
3 2022-08-16 00:05:00-04:00 REAL_TIME_5_MIN GENESE Zone 68.64 66.64 0.00 2.00
4 2022-08-16 00:05:00-04:00 REAL_TIME_5_MIN H Q Zone 64.58 66.65 0.00 -2.07
... ... ... ... ... ... ... ... ...
3370 2022-08-16 20:15:00-04:00 REAL_TIME_5_MIN NORTH Zone 85.57 87.85 0.00 -2.28
3371 2022-08-16 20:15:00-04:00 REAL_TIME_5_MIN NPX Zone 78.73 87.85 15.36 6.24
3372 2022-08-16 20:15:00-04:00 REAL_TIME_5_MIN O H Zone 85.48 87.85 0.00 -2.37
3373 2022-08-16 20:15:00-04:00 REAL_TIME_5_MIN PJM Zone 94.45 87.85 -1.86 4.74
3374 2022-08-16 20:15:00-04:00 REAL_TIME_5_MIN WEST Zone 87.85 87.85 0.00 0.00
[3375 rows x 8 columns]
And here is querying CAISO
>>> import isodata
>>> caiso = isodata.CAISO()
>>> caiso.get_lmp_today('DAY_AHEAD_HOURLY', locations=["TH_NP15_GEN-APND", "TH_SP15_GEN-APND", "TH_ZP26_GEN-APND"])
LMP_TYPE Time Market Location Location Type LMP Energy Congestion Loss
0 2022-08-16 00:00:00-07:00 DAY_AHEAD_HOURLY TH_NP15_GEN-APND None 89.48766 95.51493 -0.1531 -5.87417
1 2022-08-16 00:00:00-07:00 DAY_AHEAD_HOURLY TH_SP15_GEN-APND None 94.02489 95.51493 0.0000 -1.49003
2 2022-08-16 00:00:00-07:00 DAY_AHEAD_HOURLY TH_ZP26_GEN-APND None 90.57680 95.51493 0.0000 -4.93812
3 2022-08-16 01:00:00-07:00 DAY_AHEAD_HOURLY TH_NP15_GEN-APND None 86.38892 92.12283 -0.0223 -5.71162
4 2022-08-16 01:00:00-07:00 DAY_AHEAD_HOURLY TH_SP15_GEN-APND None 90.94366 92.12283 0.0000 -1.17917
.. ... ... ... ... ... ... ... ...
67 2022-08-16 22:00:00-07:00 DAY_AHEAD_HOURLY TH_SP15_GEN-APND None 131.45525 135.43710 0.0000 -3.98185
68 2022-08-16 22:00:00-07:00 DAY_AHEAD_HOURLY TH_ZP26_GEN-APND None 127.04000 135.43710 0.0000 -8.39710
69 2022-08-16 23:00:00-07:00 DAY_AHEAD_HOURLY TH_NP15_GEN-APND None 107.36120 113.91108 0.0000 -6.54989
70 2022-08-16 23:00:00-07:00 DAY_AHEAD_HOURLY TH_SP15_GEN-APND None 111.22278 113.91108 0.0000 -2.68830
71 2022-08-16 23:00:00-07:00 DAY_AHEAD_HOURLY TH_ZP26_GEN-APND None 108.01049 113.91108 0.0000 -5.90059
[72 rows x 8 columns]
You can see what markets are available by accessing the markets property of an iso. For, example
>>> caiso.markets
[<Markets.REAL_TIME_15_MIN: 'REAL_TIME_15_MIN'>, <Markets.REAL_TIME_HOURLY: 'REAL_TIME_HOURLY'>, <Markets.DAY_AHEAD_HOURLY: 'DAY_AHEAD_HOURLY'>]
The possible lmp query methods are ISO.get_latest_lmp, ISO.get_lmp_today, ISO.get_lmp_yesterday, and ISO.get_historical_lmp.
Supported LMP Markets
| Markets | |
|---|---|
| Midcontinent ISO | REAL_TIME_5_MIN, DAY_AHEAD_HOURLY |
| California ISO | REAL_TIME_15_MIN, REAL_TIME_HOURLY, DAY_AHEAD_HOURLY |
| PJM | |
| Electric Reliability Council of Texas | |
| Southwest Power Pool | |
| New York ISO | REAL_TIME_5_MIN, DAY_AHEAD_5_MIN |
| ISO New England | REAL_TIME_5_MIN, REAL_TIME_HOURLY, DAY_AHEAD_HOURLY |
Feedback Welcome
isodata is under active development. If there is any particular data you would like access to, let us know by posting an issue or emailing kmax12@gmail.com.
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