isodata 0.4.0

API to access energy data

Install — Getting Started — Method Availability — Pricing Data — 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

>>> iso.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

>>> iso.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,

>>> iso.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	✅	✅	❌	✅	❌	❌	✅

Pricing Data

We are investigating adding pricing data to isodata. Currently, day ahead prices are supported for CAISO. If this would be useful, please let us know by filing an issue and describing your use case.

>>> import isodata
>>> iso = isodata.CAISO()
>>> iso.get_day_ahead_prices(start_date="may 2, 2022",
                         num_days=1,
                         nodes=["TH_NP15_GEN-APND"])

LMP_TYPE	pnode	lmp	congestion	energy	losses	MGHG
interval start
2022-05-02 00:00:00-07:00	TH_NP15_GEN-APND	70.47015	0.00000	71.55783	-1.08768	0.0
2022-05-02 01:00:00-07:00	TH_NP15_GEN-APND	68.73617	0.00000	69.86093	-1.12476	0.0
2022-05-02 02:00:00-07:00	TH_NP15_GEN-APND	67.58898	0.00000	68.82788	-1.23890	0.0
2022-05-02 03:00:00-07:00	TH_NP15_GEN-APND	68.51088	0.00000	69.64611	-1.13523	0.0
2022-05-02 04:00:00-07:00	TH_NP15_GEN-APND	74.25415	0.00000	75.56136	-1.30721	0.0
2022-05-02 05:00:00-07:00	TH_NP15_GEN-APND	77.86464	0.00000	79.62434	-1.75970	0.0
2022-05-02 06:00:00-07:00	TH_NP15_GEN-APND	80.71256	0.00000	82.11675	-1.40420	0.0
2022-05-02 07:00:00-07:00	TH_NP15_GEN-APND	66.68011	0.00000	67.15016	-0.47005	0.0
2022-05-02 08:00:00-07:00	TH_NP15_GEN-APND	56.40186	7.88764	48.52878	-0.01456	0.0
2022-05-02 09:00:00-07:00	TH_NP15_GEN-APND	48.69254	9.08351	39.49055	0.11847	0.0
2022-05-02 10:00:00-07:00	TH_NP15_GEN-APND	41.55114	8.09662	33.41776	0.03676	0.0
2022-05-02 11:00:00-07:00	TH_NP15_GEN-APND	38.59000	10.35001	28.20333	0.03666	0.0
2022-05-02 12:00:00-07:00	TH_NP15_GEN-APND	36.89000	8.04264	28.82718	0.02018	0.0
2022-05-02 13:00:00-07:00	TH_NP15_GEN-APND	38.34660	8.08619	30.11885	0.14156	0.0
2022-05-02 14:00:00-07:00	TH_NP15_GEN-APND	40.00000	7.97681	31.85753	0.16566	0.0
2022-05-02 15:00:00-07:00	TH_NP15_GEN-APND	40.00000	6.59597	33.42743	-0.02340	0.0
2022-05-02 16:00:00-07:00	TH_NP15_GEN-APND	45.31324	8.08926	36.76443	0.45956	0.0
2022-05-02 17:00:00-07:00	TH_NP15_GEN-APND	59.39957	2.43405	56.88020	0.08532	0.0
2022-05-02 18:00:00-07:00	TH_NP15_GEN-APND	81.43412	0.00000	83.73688	-2.30276	0.0
2022-05-02 19:00:00-07:00	TH_NP15_GEN-APND	100.77406	0.00000	104.60251	-3.82845	0.0
2022-05-02 20:00:00-07:00	TH_NP15_GEN-APND	102.88135	0.00000	105.97585	-3.09449	0.0
2022-05-02 21:00:00-07:00	TH_NP15_GEN-APND	91.42214	0.00000	94.18167	-2.75952	0.0
2022-05-02 22:00:00-07:00	TH_NP15_GEN-APND	81.84891	0.00000	83.61315	-1.76424	0.0
2022-05-02 23:00:00-07:00	TH_NP15_GEN-APND	72.61741	0.00000	73.53662	-0.91921	0.0

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 [e-mail].

Related projects

• pyiso