Gridstatus#

Submodules#

Package Contents#

Classes Summary#

`CAISO`	California Independent System Operator (CAISO)
`Ercot`	Electric Reliability Council of Texas (ERCOT)
`ISONE`	ISO New England (ISONE)
`Markets`	Names of LMP Markets
`MISO`	Midcontinent Independent System Operator (MISO)
`NYISO`	New York Independent System Operator (NYISO)
`PJM`	PJM
`SPP`	Southwest Power Pool (SPP)

Exceptions Summary#

Functions#

`get_iso`	Get an ISO by its id
`list_isos`	List available ISOs
`load_folder`	Load a single DataFrame for same schema csv files in a folder

Contents#

class gridstatus.CAISO[source]#

Bases: gridstatus.base.ISOBase

California Independent System Operator (CAISO)

Attributes

default_timezone	US/Pacific
interconnection_homepage	https://rimspub.caiso.com/rimsui/logon.do
iso_id	caiso
markets	None
name	California ISO
status_homepage	https://www.caiso.com/TodaysOutlook/Pages/default.aspx
trading_hub_locations	[‘TH_NP15_GEN-APND’, ‘TH_SP15_GEN-APND’, ‘TH_ZP26_GEN-APND’]

Methods

`get_as_prices`	Return AS prices for a given date for each region
`get_as_procurement`	Get ancillary services procurement data from CAISO.
`get_curtailed_non_operational_generator_report`	Return curtailed non-operational generator report for a given date.
`get_curtailment`	Return curtailment data for a given date
`get_fuel_mix`	Get fuel mix in 5 minute intervals for a provided day
`get_gas_prices`	Return gas prices at a previous date
`get_ghg_allowance`	Return ghg allowance at a previous date
`get_interconnection_queue`
`get_lmp`	Get LMP pricing starting at supplied date for a list of locations.
`get_load`	Return load at a previous date in 5 minute intervals
`get_load_forecast`	Returns load forecast for a previous date in 1 hour intervals
`get_oasis_dataset`	Return data from OASIS for a given dataset
`get_pnodes`
`get_stats`
`get_status`	Get Current Status of the Grid. Only date="latest" is supported
`get_storage`	Return storage charging or discharging for today in 5 minute intervals
`list_oasis_datasets`

get_as_prices(date, end=None, market='DAM', sleep=4, verbose=False)#

Return AS prices for a given date for each region

Parameters

date (datetime.date, str) – date to return data
end (datetime.date, str) – last date of range to return data. If None, returns only date. Defaults to None.
market (str) – DAM or HASP. Defaults to DAM.
verbose (bool, optional) – print out url being fetched. Defaults to False.

Returns

A DataFrame of AS prices

Return type

pandas.DataFrame

get_as_procurement(date, end=None, market='DAM', sleep=4, verbose=False)#

Get ancillary services procurement data from CAISO.

Parameters

date (datetime.date, str) – date to return data
end (datetime.date, str) – last date of range to return data. If None, returns only date. Defaults to None.
market – DAM or RTM. Defaults to DAM.

Returns

A DataFrame of ancillary services data

Return type

pandas.DataFrame

get_curtailed_non_operational_generator_report(date, end=None, verbose=False)#

Return curtailed non-operational generator report for a given date.: Earliest available date is June 17, 2021.

Parameters

date (datetime.date, str) – date to return data
end (datetime.date, str) – last date of range to return data. If None, returns only date. Defaults to None.
verbose (bool, optional) – print out url being fetched. Defaults to False.

Returns

A DataFrame of curtailed non-operational generator report

column glossary: http://www.caiso.com/market/Pages/OutageManagement/Curtailed-OperationalGeneratorReportGlossary.aspx

if requesting multiple days, may want to run following to remove outages that get reported across multiple days: ```df.drop_duplicates(

subset=[“OUTAGE MRID”, “CURTAILMENT START DATE TIME”], keep=”last”)```

Return type

pandas.DataFrame

get_curtailment(date, verbose=False)#

Return curtailment data for a given date

Notes

requires java to be installed in order to run
Data available from June 30, 2016 to present

Parameters

date (datetime.date, str) – date to return data
end (datetime.date, str) – last date of range to return data. If None, returns only date. Defaults to None.
verbose – print out url being fetched. Defaults to False.

Returns

A DataFrame of curtailment data

Return type

pandas.DataFrame

get_fuel_mix(date, start=None, end=None, verbose=False)#

Get fuel mix in 5 minute intervals for a provided day

Parameters

date (datetime.date, str) – “latest”, “today”, or an object that can be parsed as a datetime for the day to return data.
start (datetime.date, str) – start of date range to return. alias for date parameter. Only specify one of date or start.
end (datetime.date, str) – “today” or an object that can be parsed as a datetime for the day to return data. Only used if requesting a range of dates.
verbose (bool, optional) – print verbose output. Defaults to False.

Returns

A DataFrame with columns - ‘Time’ and columns for each fuel type.

Return type

pandas.DataFrame

get_gas_prices(date, end=None, fuel_region_id='ALL', sleep=4, verbose=False)#

Return gas prices at a previous date

Parameters

date (datetime.date, str) – date to return data
end (datetime.date, str) – last date of range to return data. If None, returns only date. Defaults to None.
fuel_region_id (str, or list) – single fuel region id or list of fuel region ids to return data for. Defaults to ALL, which returns all fuel regions.

Returns

A DataFrame of gas prices

Return type

pandas.DataFrame

get_ghg_allowance(date, end=None, sleep=4, verbose=False)#

Return ghg allowance at a previous date

Parameters

date (datetime.date, str) – date to return data
end (datetime.date, str) – last date of range to return data. If None, returns only date. Defaults to None.

get_interconnection_queue(verbose=False)#

get_lmp(date, market: str, locations: list = None, sleep: int = 5, end=None, verbose=False)#

Get LMP pricing starting at supplied date for a list of locations.

Parameters

date (datetime.date, str) – date to return data
market – market to return from. supports:
locations (list) – list of locations to get data from. If no locations are provided, defaults to NP15, SP15, and ZP26, which are the trading hub locations. USE “ALL_AP_NODES” for all Aggregate Pricing Node. Use “ALL” to get all nodes. For a list of locations, call CAISO.get_pnodes()
sleep (int) – number of seconds to sleep before returning to avoid hitting rate limit in regular usage. Defaults to 5 seconds.

Returns

A DataFrame of pricing data

Return type

pandas.DataFrame

get_load(date, end=None, verbose=False)#: Return load at a previous date in 5 minute intervals

get_load_forecast(date, end=None, sleep=4, verbose=False)#

Returns load forecast for a previous date in 1 hour intervals

Parameters

date (datetime.date, pd.Timestamp, str) – day to return. If string, format should be YYYYMMDD e.g 20200623
sleep (int) – number of seconds to sleep before returning to avoid hitting rate limit in regular usage. Defaults to 5 seconds.

get_oasis_dataset(dataset, date, end=None, params=None, raw_data=True, sleep=5, verbose=False)#

Return data from OASIS for a given dataset

Parameters

dataset (str) – dataset to return data for. See CAISO.list_oasis_datasets for supported datasets
date (datetime.date, str) – date to return data
end (datetime.date, str) – last date of range to return data. If None, returns only date. Defaults to None.
params (dict) – dictionary of parameters to pass to dataset. See CAISO.list_oasis_datasets for supported parameters
raw_data (bool, optional) – return raw data from OASIS. Defaults to True.
sleep (int, optional) – number of seconds to sleep between requests. Defaults to 5.
verbose (bool, optional) – print out url being fetched. Defaults to False.

Returns

A DataFrame of OASIS data

Return type

pandas.DataFrame

get_pnodes(verbose=False)#

get_stats(verbose=False)#

get_status(date='latest', verbose=False) → str#

Get Current Status of the Grid. Only date=”latest” is supported

Known possible values: Normal, Restricted Maintenance Operations, Flex Alert

get_storage(date, verbose=False)#

Return storage charging or discharging for today in 5 minute intervals

Negative means charging, positive means discharging

Parameters: date (datetime.date, str) – date to return data

list_oasis_datasets(dataset=None)#

class gridstatus.Ercot[source]#

Bases: gridstatus.base.ISOBase

Electric Reliability Council of Texas (ERCOT)

class Document#

Attributes

constructed_name	None
friendly_name	None
publish_date	None
url	None

Attributes

ACTUAL_LOADS_URL_FORMAT	https://www.ercot.com/content/cdr/html/{timestamp}_actual_loads_of_forecast_zones.html
AS_PRICES_HISTORICAL_MAX_DAYS	30
BASE	https://www.ercot.com/api/1/services/read/dashboards
default_timezone	US/Central
interconnection_homepage	http://mis.ercot.com/misapp/GetReports.do?reportTypeId=15933
iso_id	ercot
LOAD_HISTORICAL_MAX_DAYS	14
location_types	None
markets	None
name	Electric Reliability Council of Texas
status_homepage	https://www.ercot.com/gridmktinfo/dashboards/gridconditions

Methods

`get_as_prices`	Get ancillary service clearing prices in hourly intervals in Day Ahead Market
`get_dam_spp`	Get Historical DAM Settlement Point Prices(SPPs)
`get_fuel_mix`	Get fuel mix 5 minute intervals
`get_interconnection_queue`	Get interconnection queue for ERCOT
`get_load`	Get load for a date
`get_load_forecast`	Returns load forecast
`get_rtm_spp`	Get Historical RTM Settlement Point Prices(SPPs)
`get_spp`	Get SPP data for ERCOT
`get_status`	Returns status of grid
`parse_doc`
`read_doc`

get_as_prices(date, end=None, verbose=False)#

Get ancillary service clearing prices in hourly intervals in Day Ahead Market

Parameters

date (datetime.date, str) – date of delivery for AS services
end (datetime.date, str, optional) – if declared, function will return data as a range, from “date” to “end”
verbose (bool, optional) – print verbose output. Defaults to False.

Returns

A DataFrame with prices for “Non-Spinning Reserves”, “Regulation Up”, “Regulation Down”, “Responsive Reserves”.

Return type

pandas.DataFrame

Source:: https://www.ercot.com/mp/data-products/data-product-details?id=NP4-181-ER

get_dam_spp(year, verbose=False)#

Get Historical DAM Settlement Point Prices(SPPs) for each of the Hubs and Load Zones

Parameters: year (int) – year to get data for. Starting 2011, returns data for the entire year

Source:: https://www.ercot.com/mp/data-products/data-product-details?id=NP4-180-ER

get_fuel_mix(date, verbose=False)#

Get fuel mix 5 minute intervals

Parameters

date (datetime.date, str) – “latest”, “today”, and yesterday’s date are supported.
verbose (bool) – print verbose output. Defaults to False.

Returns

A DataFrame with columns; Time and columns for each fuel type

Return type

pandas.DataFrame

get_interconnection_queue(verbose=False)#

Get interconnection queue for ERCOT

Monthly historical data available here:: http://mis.ercot.com/misapp/GetReports.do?reportTypeId=15933&reportTitle=GIS%20Report&showHTMLView=&mimicKey

get_load(date, end=None, verbose=False)#: Get load for a date

get_load_forecast(date, verbose=False)#

Returns load forecast

Currently only supports today’s forecast

get_rtm_spp(year, verbose=False)#

Get Historical RTM Settlement Point Prices(SPPs): for each of the Hubs and Load Zones

Parameters: year (int) – year to get data for Starting 2011, returns data for the entire year

Source:: https://www.ercot.com/mp/data-products/data-product-details?id=NP6-785-ER

get_spp(date, end=None, market: str = None, locations: list = 'ALL', location_type: str = 'ALL', verbose=False)#

Get SPP data for ERCOT

Supported Markets:

REAL_TIME_15_MIN
DAY_AHEAD_HOURLY

Supported Location Types:

zone
hub
node

get_status(date, verbose=False)#: Returns status of grid

parse_doc(doc, verbose=False)#

read_doc(doc, verbose=False)#

gridstatus.get_iso(iso_id)[source]#: Get an ISO by its id

class gridstatus.ISONE[source]#

Bases: gridstatus.base.ISOBase

ISO New England (ISONE)

Attributes

default_timezone	US/Eastern
hubs	None
interconnection_homepage	https://irtt.iso-ne.com/reports/external
interfaces	None
iso_id	isone
markets	None
name	ISO New England
status_homepage	https://www.iso-ne.com/markets-operations/system-forecast-status/current-system-status
zones	None

Methods

`get_btm_solar`	Return BTM solar at a previous date in 5 minute intervals
`get_fuel_mix`	Return fuel mix at a previous date
`get_interconnection_queue`	Get the interconnection queue. Contains active and withdrawm applications.
`get_lmp`	Find Node ID mapping:
`get_load`	Return load at a previous date in 5 minute intervals
`get_load_forecast`	Return forecast at a previous date
`get_status`	Get latest status for ISO NE

get_btm_solar(date, end=None, verbose=False)#: Return BTM solar at a previous date in 5 minute intervals

get_fuel_mix(date, end=None, verbose=False)#

Return fuel mix at a previous date

Provided at frequent, but irregular intervals by ISONE

get_interconnection_queue(verbose=False)#

Get the interconnection queue. Contains active and withdrawm applications.

More information: https://www.iso-ne.com/system-planning/interconnection-service/interconnection-request-queue/

Returns: interconnection queue
Return type: pandas.DataFrame

get_lmp(date, end=None, market: str = None, locations: list = None, include_id=False, verbose=False)#

Find Node ID mapping:: https://www.iso-ne.com/markets-operations/settlements/pricing-node-tables/

get_load(date, end=None, verbose=False)#: Return load at a previous date in 5 minute intervals

get_load_forecast(date, end=None, verbose=False)#: Return forecast at a previous date

get_status(date, verbose=False)#: Get latest status for ISO NE

gridstatus.list_isos()[source]#: List available ISOs

gridstatus.load_folder(path, time_zone=None, verbose=True)[source]#

Load a single DataFrame for same schema csv files in a folder

Parameters

path (str) – path to folder
time_zone (str) – time zone to localize to timestamps. By default returns as UTC
verbose (bool, optional) – print verbose output. Defaults to True.

Returns

A DataFrame of all files

Return type

pandas.DataFrame

class gridstatus.Markets[source]#

Bases: enum.Enum

Names of LMP Markets

Attributes

DAY_AHEAD_HOURLY	DAY_AHEAD_HOURLY
REAL_TIME_15_MIN	REAL_TIME_15_MIN
REAL_TIME_5_MIN	REAL_TIME_5_MIN
REAL_TIME_HOURLY	REAL_TIME_HOURLY

Methods

__contains__

__contains__(item)#

class gridstatus.MISO[source]#

Bases: gridstatus.base.ISOBase

Midcontinent Independent System Operator (MISO)

Attributes

BASE	https://api.misoenergy.org/MISORTWDDataBroker/DataBrokerServices.asmx
default_timezone	US/Eastern
hubs	[‘ILLINOIS.HUB’, ‘INDIANA.HUB’, ‘LOUISIANA.HUB’, ‘MICHIGAN.HUB’, ‘MINN.HUB’, ‘MS.HUB’, ‘TEXAS.HUB’, ‘ARKANSAS.HUB’]
interconnection_homepage	https://www.misoenergy.org/planning/generator-interconnection/GI_Queue/
iso_id	miso
markets	None
name	Midcontinent ISO

Methods

`get_fuel_mix`	Get the fuel mix for a given day for a provided MISO.
`get_interconnection_queue`	Get the interconnection queue
`get_lmp`	Supported Markets:
`get_load`
`get_load_forecast`

get_fuel_mix(date, verbose=False)#

Get the fuel mix for a given day for a provided MISO.

Parameters

date (datetime.date, str) – “latest”, “today”, or an object that can be parsed as a datetime for the day to return data.
verbose (bool, optional) – print verbose output. Defaults to False.

Returns

DataFrame with columns “Time”, “Load”, “Fuel Mix”

Return type

pandas.DataFrame

get_interconnection_queue(verbose=False)#

Get the interconnection queue

Returns: Interconnection queue
Return type: pandas.DataFrame

get_lmp(date, market: str, locations: list = None, verbose=False)#

Supported Markets:

REAL_TIME_5_MIN - (FiveMinLMP)
DAY_AHEAD_HOURLY - (DayAheadExPostLMP)

get_load(date, verbose=False)#

get_load_forecast(date, verbose=False)#

exception gridstatus.NotSupported[source]#

Bases: Exception

Common base class for all non-exit exceptions.

Initialize self. See help(type(self)) for accurate signature.

class gridstatus.NYISO[source]#

Bases: gridstatus.base.ISOBase

New York Independent System Operator (NYISO)

Attributes

default_timezone	US/Eastern
interconnection_homepage	https://www.nyiso.com/interconnections
iso_id	nyiso
markets	None
name	New York ISO
status_homepage	https://www.nyiso.com/system-conditions

Methods

`get_capacity_prices`	Pull the most recent capacity market report's market clearing prices
`get_fuel_mix`
`get_generators`	Get a list of generators in NYISO
`get_interconnection_queue`	Return NYISO interconnection queue
`get_lmp`	Supported Markets:
`get_load`	Returns load at a previous date in 5 minute intervals for
`get_load_forecast`	Get load forecast for a date in 1 hour intervals
`get_loads`	Get a list of loads in NYISO
`get_status`

get_capacity_prices(date=None, verbose=False)#

Pull the most recent capacity market report’s market clearing prices

Parameters

date (pandas.Timestamp) – date that will be used to pull latest capacity report (will refer to month and year)
verbose (bool, optional) – print out requested url. Defaults to False.

Returns

a DataFrame of monthly capacity prices (all three auctions) for each of the four capacity localities within NYISO

get_fuel_mix(date, end=None, verbose=False)#

get_generators(verbose=False)#

Get a list of generators in NYISO

When possible return capacity and fuel type information

Parameters

verbose (bool, optional) – print out requested url. Defaults to False.

Returns

a DataFrame of generators and locations

Possible Columns

Generator Name
PTID
Subzone
Zone
Latitude
Longitude
Owner, Operator, and / or Billing Organization
Station Unit
Town
County
State
In-Service Date
Name Plate Rating (V) MW
2022 CRIS MW Summer
2022 CRIS MW Winter
2022 Capability MW Summer
2022 Capability MW Winter
Is Dual Fuel
Unit Type
Fuel Type 1
Fuel Type 2
2021 Net Energy GWh
Notes
Generator Type

Return type

pandas.DataFrame

get_interconnection_queue(verbose=False)#

Return NYISO interconnection queue

Additional Non-NYISO queue info: https://www3.dps.ny.gov/W/PSCWeb.nsf/All/286D2C179E9A5A8385257FBF003F1F7E?OpenDocument

Returns: Interconnection queue containing, active, withdrawn, and completed project
Return type: pandas.DataFrame

get_lmp(date, end=None, market: str = None, locations: list = None, location_type: str = None, verbose=False)#

Supported Markets:

REAL_TIME_5_MIN
DAY_AHEAD_HOURLY

Supported Location Types:

zone
generator

get_load(date, end=None, verbose=False)#

Returns load at a previous date in 5 minute intervals for: each zone and total load

Parameters

date (str) – Date to get load for. Can be “latest”, “today”, or a date in the format YYYY-MM-DD
end (str) – End date for date range. Optional.
verbose (bool) – Whether to print verbose output. Optional.

Returns

Load data for NYISO and each zone

Return type

pandas.DataFrame

get_load_forecast(date, end=None, verbose=False)#: Get load forecast for a date in 1 hour intervals

get_loads(verbose=False)#

Get a list of loads in NYISO

Parameters: verbose (bool, optional) – print out requested url. Defaults to False.
Returns: a DataFrame of loads and locations
Return type: pandas.DataFrame

get_status(date, end=None, verbose=False)#

class gridstatus.PJM[source]#

Bases: gridstatus.base.ISOBase

PJM

Attributes

default_timezone	US/Eastern
hub_node_ids	[‘51217’, ‘116013751’, ‘35010337’, ‘34497151’, ‘34497127’, ‘34497125’, ‘33092315’, ‘33092313’, ‘33092311’, ‘4669664’, ‘51288’, ‘51287’]
interconnection_homepage	https://www.pjm.com/planning/services-requests/interconnection-queues.aspx
iso_id	pjm
location_types	[‘ZONE’, ‘LOAD’, ‘GEN’, ‘AGGREGATE’, ‘INTERFACE’, ‘EXT’, ‘HUB’, ‘EHV’, ‘TIE’, ‘RESIDUAL_METERED_EDC’]
markets	None
name	PJM
zone_node_ids	[‘1’, ‘3’, ‘51291’, ‘51292’, ‘51293’, ‘51295’, ‘51296’, ‘51297’, ‘51298’, ‘51299’, ‘51300’, ‘51301’, ‘7633629’, ‘8394954’, ‘8445784’, ‘33092371’, ‘34508503’, ‘34964545’, ‘37737283’, ‘116013753’, ‘124076095’, ‘970242670’, ‘1709725933’]

Methods

`get_fuel_mix`	Get fuel mix for a date or date range in hourly intervals
`get_interconnection_queue`
`get_lmp`	Returns LMP at a previous date
`get_load`	Returns load at a previous date at 5 minute intervals
`get_load_forecast`	Get forecast for today in hourly intervals.
`get_pnode_ids`

get_fuel_mix(date, end=None, verbose=False)#: Get fuel mix for a date or date range in hourly intervals

get_interconnection_queue(verbose=False)#

get_lmp(date, market: str, end=None, locations='hubs', location_type=None, verbose=False)#

Returns LMP at a previous date

Notes

If start date is prior to the PJM archive date, all data

must be downloaded before location filtering can be performed due to limitations of PJM API. The archive date is 186 days (~6 months) before today for the 5 minute real time market and 731 days (~2 years) before today for the Hourly Real Time and Day Ahead Hourly markets. Node type filter can be performed for Real Time Hourly and Day Ahead Hourly markets.

If location_type is provided, it is filtered after data

is retrieved for Real Time 5 Minute market regardless of the date. This is due to PJM api limitations

Parameters

date (datetime.date, str) – date to get LMPs for
end (datetime.date, str) – end date to get LMPs for
market (str) – Supported Markets: REAL_TIME_5_MIN, REAL_TIME_HOURLY, DAY_AHEAD_HOURLY
locations (list, optional) – list of pnodeid to get LMPs for. Defaults to “hubs”. Use get_pnode_ids() to get a list of possible pnode ids. If “all”, will return data from all p nodes (warning there are over 10,000 unique pnodes, so expect millions or billions of rows!)
location_type (str, optional) – If specified, will only return data for nodes of this type. Defaults to None. Possible location types are: ‘ZONE’, ‘LOAD’, ‘GEN’, ‘AGGREGATE’, ‘INTERFACE’, ‘EXT’, ‘HUB’, ‘EHV’, ‘TIE’, ‘RESIDUAL_METERED_EDC’.

get_load(date, end=None, verbose=False)#

Returns load at a previous date at 5 minute intervals

Parameters

date (datetime.date, str) – date to get load for. must be in last 30 days

Returns

Load data time series. Columns: Time, Load, and all areas

Load columns represent PJM-wide load
Returns data for the following areas: AE, AEP, APS, ATSI,

BC, COMED, DAYTON, DEOK, DOM, DPL, DUQ, EKPC, JC, ME, PE, PEP, PJM MID ATLANTIC REGION, PJM RTO, PJM SOUTHERN REGION, PJM WESTERN REGION, PL, PN, PS, RECO

Return type

pd.DataFrame

get_load_forecast(date, verbose=False)#

Get forecast for today in hourly intervals.

Updates every Every half hour on the quarter E.g. 1:15 and 1:45

get_pnode_ids()#

class gridstatus.SPP[source]#

Bases: gridstatus.base.ISOBase

Southwest Power Pool (SPP)

Attributes

default_timezone	US/Central
interconnection_homepage	https://www.spp.org/engineering/generator-interconnection/
iso_id	spp
location_types	None
markets	None
name	Southwest Power Pool
status_homepage	https://www.spp.org/markets-operations/current-grid-conditions/

Methods

`get_fuel_mix`	Get fuel mix
`get_interconnection_queue`	Get interconnection queue
`get_lmp`	Get LMP data
`get_load`	Returns load for last 24hrs in 5 minute intervals
`get_load_forecast`	Returns load forecast for next 7 days in hourly intervals
`get_status`
`get_ver_curtailments`	Get VER Curtailments
`get_ver_curtailments_annual`	Get VER Curtailments for a year. Starting 2014.

get_fuel_mix(date, detailed=False, verbose=False)#

Get fuel mix

Parameters

date – supports today and latest
detailed – if True, breaks out self scheduled and market scheduled

Note

if today, returns last 2 hours of data. maybe include previous day

Returns: fuel mix
Return type: pd.DataFrame

get_interconnection_queue(verbose=False)#

Get interconnection queue

Returns: Interconnection queue
Return type: pandas.DataFrame

get_lmp(date, end=None, market: str = None, locations: list = 'ALL', location_type: str = LOCATION_TYPE_HUB, verbose=False)#

Get LMP data

Supported Markets:

REAL_TIME_5_MIN
DAY_AHEAD_HOURLY

Supported Location Types:

hub
interface
settlement_location

get_load(date, verbose=False)#: Returns load for last 24hrs in 5 minute intervals

get_load_forecast(date, forecast_type='MID_TERM', verbose=False)#

Returns load forecast for next 7 days in hourly intervals

Parameters: forecast_type (str) – MID_TERM is hourly for next 7 days or SHORT_TERM is every five minutes for a few hours
Returns: forecast for current day
Return type: pd.DataFrame

get_status(date=None, verbose=False)#

get_ver_curtailments(date, end=None, verbose=False)#

Get VER Curtailments

Supports recent data. For historical annual data use get_ver_curtailments_annual

Parameters

date – start date
end – end date

get_ver_curtailments_annual(year, verbose=True)#

Get VER Curtailments for a year. Starting 2014. Recent data use get_ver_curtailments

Parameters

year – year to get data for
verbose – print url

Returns

VER Curtailments

Return type

pd.DataFrame

Gridstatus

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