ERCOT Day-Ahead Binding Constraints

Which transmission facilities bound in ERCOT's day-ahead market and what each one cost, one row per interval and constraint.

Congestion & Constraints data ERCOT market

Query with the agent

Native record

constraint x delivery hour

hourly (DAM) publication cadence

Evidence

Cleared day-ahead market

A market outcome, not a physical observation

Time basis

Interval-start records

UTC · event_time

Overview

2.94M rows, 2017-01 to the next delivery day. Columns: event_time, constraint_name, shadow_price_usd_mwh, plus contingency, from_station and to_station, limit_mw and flow_mw. The shadow price is the marginal cost of the binding limit — what the market would have saved from one more megawatt of capability on that element. This is the table that answers WHY congestion appeared; a price spread between two locations shows that they separated but not which facility separated them.

Query contract

A row means this constraint was binding in this interval. Absence of a row means it was not binding, not that it does not exist.

Analysis rules

Rank constraints by summed or averaged shadow price over a window, and say which — a constraint that binds rarely but hard ranks differently from one that binds constantly and cheaply.
Count binding INTERVALS, not rows, when describing how often a constraint bound.

Related analysis

explaining why a location's congestion component moved in an interval · align on event_time; the constraint explains the market-wide congestion pattern, not one location's share of it

Interpretation

A shadow price is the marginal value of relaxing the limit. It is not the amount of power that flowed, not a measure of how loaded the line was, and not a dollar cost anyone paid.
This table names the binding element. Attributing a specific location's congestion to a specific constraint additionally needs a shift factor, which is not published here.

Access

Query from your own tools

Use the guarded HTTP endpoint directly, or connect an MCP client and load the dataset contract with describe_data before calling query_data.

ERCOT MCP API reference

HTTP endpoint

POST /api/v1/datasets/ercot_constraints_da/query

Need the full history of this dataset in Snowflake, Databricks or your own storage? Data services delivers it on a schedule.

Schema8

Column

Type

event_timeDateTime64(6, 'UTC')

constraint_nameLowCardinality(String)

contingencyLowCardinality(String)

from_stationLowCardinality(Nullable(String))

to_stationLowCardinality(Nullable(String))

shadow_price_usd_mwhNullable(Float64)

limit_mwNullable(Float64)

flow_mwNullable(Float64)

Sample data

event_time	constraint_name	contingency	from_station	to_station	shadow_price_usd_mwh	limit_mw	flow_mw
2026-10-13 05:00:00.000000	TREADW_YELWJC1_1	DBIGKEN5	TREADWEL	YELWJCKT	11.98	204	204
2026-10-13 05:00:00.000000	THW_AT2T	BASE CASE	THW	THW	0.004	25	25
2026-10-13 05:00:00.000000	RG_SC_1	BASE CASE	REDGATE	REDGATE	0.105	325	325
2026-10-13 05:00:00.000000	RAYBURN_69_2	SFURMOU8	RAYBURN	RAYBURN	1.178	84	84
2026-10-13 05:00:00.000000	RANDAD_ZAPATA1_1	BASE CASE	RANDADO	ZAPATA	0.003	77	77
2026-10-13 05:00:00.000000	ODEHV_MR1H	MODERTR5	ODEHV	ODEHV	1.792	550	550
2026-10-13 05:00:00.000000	NLARSW_PILONC1_1	DFOAVLO5	NLARSW	PILONCIL	0.04	139	139
2026-10-13 05:00:00.000000	MENPHT_YELWJC1_1	MMSWMSN9	YELWJCKT	MENPHTAP	17.012	60	60
2026-10-13 05:00:00.000000	LPLMK_LPLCO_1	XLP259	LPLCO	LPLMK	1.371	131	131
2026-10-13 05:00:00.000000	KLNSW_MR1H	DSALKLN5	KLNSW	KLNSW	73.442	750	750
2026-10-13 05:00:00.000000	HARGRO_TWINBU1_1	DBAKCED5	TWINBU	HARGROVE	1.846	151	151
2026-10-13 05:00:00.000000	G138_4B_1	SGRNCAD8	CADDOTN	APACHE	0.285	379	379
2026-10-13 05:00:00.000000	FTST_SOLSTI1_1	DBAKSOL5	FTST	SOLSTICE	0.029	222	222
2026-10-13 05:00:00.000000	DIESEL_FMR1	BASE CASE	DIESEL	DIESEL	0.009	25	25
2026-10-13 05:00:00.000000	CG_CG_06_1	BASE CASE	CG	CG	0.264	180	180
2026-10-13 05:00:00.000000	CELANE_KLEBER1_1	SN_SAJO5	KLEBERG	CELANEBI	0.088	243	243
2026-10-13 05:00:00.000000	BRUNI_69_1	SLAQLOB8	BRUNI	BRUNI	5.74	37	37
2026-10-13 05:00:00.000000	BRUNI_69_1	DFOAVLO5	BRUNI	BRUNI	21.407	37	37
2026-10-13 05:00:00.000000	BLESSI_PAVLOV1_1	SCBEDYN8	BLESSING	PAVLOV	0.747	157	157
2026-10-13 05:00:00.000000	BLESSING_1382	DELMSTP5	BLESSING	BLESSING	8.007	428	428
2026-10-13 05:00:00.000000	BERGHE_AT1H	DZORHAY5	BERGHE	BERGHE	1.035	370	370
2026-10-13 05:00:00.000000	BENTS_FRTER_1B_1	SBENS_M8	FRONTERA	S_MISSIN	4.601	213	213
2026-10-13 05:00:00.000000	BCVPSA03_A	SSCJFS8	PSA	BCV	8.475	478	478
2026-10-13 05:00:00.000000	BAKRFLD_CEDCAN_1	SBAKCED5	CEDACA	BAKESW	1.47	1793	1793
2026-10-13 05:00:00.000000	6830__B	DGRMGRS8	CRDSW	OLNEY	0.991	48	48

Coverage

100.0% complete0 gap days3,572 days with data

Show coverage history

Coverage: 100.0%Days with data: 3,572Gaps: 0

2026

2025

2024

2023

2022

2021

2020

2019

2018

2017

gaplessmore

Related congestion & constraints data

Related congestion & constraints data
Dataset	Description
Constraint Shift Factor RunsERCOT · nightly (one row per completed run)	One row per COMPLETED nightly estimation of ERCOT constraint shift factors, and the only record that a run finished. Resolve the latest usable run here — computed_at = (SELECT max(computed_at) FROM atg.ercot_constraint_sensitivity_runs) — and never off max(computed_at) of the sensitivities themselves, because a run writes its rows in blocks that all carry the new timestamp and an unfinished or abandoned run would otherwise look like the newest one. Each row also carries how much evidence that run had: interval_coverage is the fraction of published dispatch intervals that survived admission, intervals_refused_unexplained counts intervals showing congestion with no constraint recorded as binding (an unobserved binding set), constraint_feed_lag_minutes is how far the constraint feed trailed the price feed, and constraints_seen / constraints_in_fit / constraints_reported show how many constraints bound, how many were good enough to control for, and how many earned a published estimate.
Constraint Shift Factors (Estimated)ERCOT · nightly (60-day rolling estimation window)	Estimated sensitivity of every ERCOT pricing location's price to every binding transmission constraint: one row per constraint, contingency, and location, recomputed nightly over a rolling 60-day window. This is what answers 'which nodes drive this constraint' and 'which constraints is this node exposed to'. Covers ERCOT's transmission constraints with their contingency and both named terminals, over 1,123 settlement points. shift_factor is in the ISO's orientation — POSITIVE means an incremental MW injected at that node increases loading on the constraint and the node is paid below system lambda while it binds; NEGATIVE means generation there relieves the constraint and earns a premium. These are ESTIMATES recovered from the price identity LMP = energy - sum(shift_factor x shadow_price), not a published PTDF matrix. They are measured RELATIVE TO THE MARKET'S REFERENCE — the identity yields SF(node) - SF(reference), so a single absolute value should be quoted as 'relative to the system reference' rather than as the node's PTDF, while DIFFERENCES between nodes are exact because the reference term cancels. Three further differences from a published matrix: they describe a NODE (a generator at that node inherits its location's value, and two units at one node are indistinguishable), they reflect the topology actually in effect across the window including outages rather than a stated base case, and every one carries a std_error from a 200-draw block bootstrap that resamples whole days. Read std_error before quoting shift_factor: an estimate whose absolute value is not at least twice its standard error is not distinguishable from zero. estimation_status says why a row has no number — 'thin_support' (in the fit, so it is controlled for, but under 12 binding intervals or under 3 distinct binding days), 'no_support' (under 3 binding intervals; not a regressor), or 'collinear' (it bound in lockstep with another constraint, so the two cannot be separated). Where from_station and to_station are populated they identify the monitored element and are NOT the constrained direction — the sign of shift_factor is what says which way. Every read must pin computed_at to one run, and must resolve that run through the companion atg.<iso>_constraint_sensitivity_runs ledger rather than off max(computed_at) here — rows are written in blocks that all carry the new timestamp, so an unfinished or abandoned run would otherwise look like the newest. Mixing runs averages a node across different network topologies.
CRR Monthly Auction ResultsERCOT · monthly auction posting	Cleared ERCOT monthly Congestion Revenue Right auction awards, one row per source-to-sink CRR and time-of-use block, including awarded MW and the auction shadow price per MWh. This is public auction evidence for who acquired a path and at what clearing price. It does not contain realized day-ahead congestion settlements, fees, later trades, the holder's full portfolio, or net profit, so auction cost must not be described as payout or profitability. The official source is ERCOT report NP7-803-M.
Day-Ahead Shadow Prices & Binding ConstraintsERCOT · hourly (DAM)	Binding transmission constraint and contingency pairs from ERCOT's Day-Ahead Market solution, one row per constraint, contingency, and delivery hour, including the limiting facility, its from and to stations, the constraint limit, flow, and violation in MW, and the shadow price. A row establishes that the named constraint bound in the cleared day-ahead solution for that hour and its marginal system cost. It does not, by itself, identify which settlement point or hub the constraint affected, or establish that the constraint bound in real time; the first requires shift-factor or direct attribution evidence, and real-time binding is recorded in the SCED shadow prices. The official source is ERCOT report NP4-191-CD.