LMP Data Examples#
Walkthrough on how to query LMP data from SPP using gridstatus#
import gridstatus
import pandas as pd
iso = gridstatus.SPP()
Available Markets#
SPP has 2 LMP Markets you can query:
iso.markets
[<Markets.REAL_TIME_5_MIN: 'REAL_TIME_5_MIN'>,
<Markets.DAY_AHEAD_HOURLY: 'DAY_AHEAD_HOURLY'>]
Available Location Types#
The following locations types are available:
iso.location_types
['HUB', 'INTERFACE', 'SETTLEMENT_LOCATION']
HUB and INTERFACE will filter for those location types, but when choosing SETTLEMENT_LOCATION, all available locations and location types will be returned and labeled correctly.
Query Latest Real-Time LMPs by Hub#
By default, the LMP methods will get data for the Hub nodes in SPP:
df = iso.get_lmp(date="latest", market="REAL_TIME_5_MIN")
df
| Time | Market | Location | Location Type | LMP | Energy | Congestion | Loss | |
|---|---|---|---|---|---|---|---|---|
| 0 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | SPPNORTH_HUB | Hub | -32.8155 | 15.8662 | -47.8942 | -0.7875 |
| 1 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | SPPSOUTH_HUB | Hub | 16.9609 | 15.8661 | 1.4744 | -0.3796 |
Query Latest Real-Time LMPs by Settlement Location#
df = iso.get_lmp(
date="latest", market="REAL_TIME_5_MIN", location_type="SETTLEMENT_LOCATION"
)
df.head(5)
| Time | Market | Location | Location Type | LMP | Energy | Congestion | Loss | |
|---|---|---|---|---|---|---|---|---|
| 0 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | AEC | Settlement Location | 69.4670 | 15.8661 | 53.0336 | 0.5673 |
| 1 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | AECC_CSWS | Settlement Location | 82.9840 | 15.8662 | 66.2379 | 0.8799 |
| 2 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | AECC_ELKINS | Settlement Location | 109.7306 | 15.8661 | 92.9510 | 0.9135 |
| 3 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | AECC_FITZHUGH | Settlement Location | 78.6462 | 15.8661 | 61.5857 | 1.1944 |
| 4 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | AECC_FLTCREEK | Settlement Location | 124.9584 | 15.8662 | 108.5484 | 0.5438 |
When requesting Settlement Locations, locations which are Interfaces and Hubs are marked as such.
df["Location Type"].unique().tolist()
['Settlement Location', 'Interface', 'Hub']
Query Latest Real-Time LMPs by Interface#
df = iso.get_lmp(date="latest", market="REAL_TIME_5_MIN", location_type="Interface")
df.head(5)
| Time | Market | Location | Location Type | LMP | Energy | Congestion | Loss | |
|---|---|---|---|---|---|---|---|---|
| 0 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | AECI | Interface | 79.5027 | 15.8661 | 63.1488 | 0.4878 |
| 1 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | ALTW | Interface | 43.7429 | 15.8662 | 27.6867 | 0.1900 |
| 2 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | AMRN | Interface | 43.7429 | 15.8662 | 27.6867 | 0.1900 |
| 3 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | BLKW | Interface | -23.2882 | 15.8661 | -38.5089 | -0.6454 |
| 4 | 2022-12-27 22:20:00-06:00 | REAL_TIME_5_MIN | CLEC | Interface | 43.7429 | 15.8662 | 27.6867 | 0.1900 |
Query Today’s Real-Time LMPs by Interface#
df = iso.get_lmp(date="today", market="REAL_TIME_5_MIN", location_type="Interface")
df.head(5)
| Time | Market | Location | Location Type | LMP | Energy | Congestion | Loss | |
|---|---|---|---|---|---|---|---|---|
| 0 | 2022-12-27 00:00:00-06:00 | REAL_TIME_5_MIN | AECI | Interface | 62.3457 | 18.1608 | 43.5727 | 0.6122 |
| 1 | 2022-12-27 00:00:00-06:00 | REAL_TIME_5_MIN | ALTW | Interface | 50.6113 | 18.1609 | 32.4184 | 0.0320 |
| 2 | 2022-12-27 00:00:00-06:00 | REAL_TIME_5_MIN | AMRN | Interface | 50.6113 | 18.1609 | 32.4184 | 0.0320 |
| 3 | 2022-12-27 00:00:00-06:00 | REAL_TIME_5_MIN | BLKW | Interface | -25.3934 | 18.1608 | -42.6874 | -0.8668 |
| 4 | 2022-12-27 00:00:00-06:00 | REAL_TIME_5_MIN | CLEC | Interface | 50.6113 | 18.1609 | 32.4184 | 0.0320 |
Query Day-Ahead LMPs by Hub#
Return today’s day-ahead hourly data by hub:
df = iso.get_lmp(date="today", market="DAY_AHEAD_HOURLY", location_type="Hub")
df.head(5)
| Time | Market | Location | Location Type | LMP | Energy | Congestion | Loss | |
|---|---|---|---|---|---|---|---|---|
| 0 | 2022-12-28 00:55:00-06:00 | DAY_AHEAD_HOURLY | SPPNORTH_HUB | Hub | -2.0650 | 18.3069 | -19.4408 | -0.9311 |
| 1 | 2022-12-28 00:55:00-06:00 | DAY_AHEAD_HOURLY | SPPSOUTH_HUB | Hub | 29.2452 | 18.3069 | 11.1502 | -0.2119 |
| 2 | 2022-12-28 01:55:00-06:00 | DAY_AHEAD_HOURLY | SPPNORTH_HUB | Hub | -4.3129 | 17.8149 | -21.2129 | -0.9149 |
| 3 | 2022-12-28 01:55:00-06:00 | DAY_AHEAD_HOURLY | SPPSOUTH_HUB | Hub | 28.6881 | 17.8150 | 11.0831 | -0.2100 |
| 4 | 2022-12-28 02:55:00-06:00 | DAY_AHEAD_HOURLY | SPPNORTH_HUB | Hub | -4.6564 | 16.6584 | -20.4966 | -0.8182 |
Query Day-Ahead LMPs by Interface#
Return the latest day-ahead hourly data by interface:
df = iso.get_lmp(date="today", market="DAY_AHEAD_HOURLY", location_type="Interface")
df.head(5)
| Time | Market | Location | Location Type | LMP | Energy | Congestion | Loss | |
|---|---|---|---|---|---|---|---|---|
| 0 | 2022-12-28 00:55:00-06:00 | DAY_AHEAD_HOURLY | AECI | Interface | 68.3391 | 18.3069 | 49.3985 | 0.6337 |
| 1 | 2022-12-28 00:55:00-06:00 | DAY_AHEAD_HOURLY | ALTW | Interface | 56.8415 | 18.3070 | 38.0957 | 0.4388 |
| 2 | 2022-12-28 00:55:00-06:00 | DAY_AHEAD_HOURLY | AMRN | Interface | 56.8415 | 18.3070 | 38.0957 | 0.4388 |
| 3 | 2022-12-28 00:55:00-06:00 | DAY_AHEAD_HOURLY | BLKW | Interface | -12.2775 | 18.3069 | -29.8699 | -0.7145 |
| 4 | 2022-12-28 00:55:00-06:00 | DAY_AHEAD_HOURLY | CLEC | Interface | 56.8415 | 18.3070 | 38.0957 | 0.4388 |