MISO Real-Time Binding Constraints

Which transmission facilities bound in MISO's real-time market and what each one cost, one row per interval and constraint.

Congestion & Constraints data MISO market

Query with the agent

Native record

constraint x dispatch interval

5-minute publication cadence

Evidence

Observed market data

Published observations from the named source

Time basis

Interval-start records

UTC · event_time

Overview

80k rows, 2026-08-12 to now. Columns: event_time, constraint_name, shadow_price_usd_mwh, plus constraint_type (real_time for transmission constraints, sub_regional for power-balance constraints, reserve for reserve constraints). The contingency is inside constraint_name after a _flo_ or _FLO_ marker; there is no contingency column. 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

Interpretation

shadow_price_usd_mwh is negated from MISO's published negative values so that, as in every other market here, a larger positive number is a more expensive binding constraint.
constraint_type is a population selector: filter it before counting or ranking, because reserve and sub-regional rows are not transmission constraints.

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.

MISO MCP API reference

HTTP endpoint

POST /api/v1/datasets/miso_constraints_rt/query

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

Schema4

Column

Type

event_timeDateTime64(6, 'UTC')

constraint_nameLowCardinality(String)

constraint_typeLowCardinality(String)

shadow_price_usd_mwhNullable(Float64)

Sample data

event_time	constraint_name	constraint_type	shadow_price_usd_mwh
2026-10-17 04:55:00.000000	IPL13095_HANNAIPL_132-30_1	real_time	35.38
2026-10-17 04:55:00.000000	RDT_SO_MW (South_North) - STR+Lost_Gen Zone_1	reserve	15.37
2026-10-17 04:55:00.000000	NDEX	real_time	39.96
2026-10-17 04:50:00.000000	IPL13095_HANNAIPL_132-30_1	real_time	56.69
2026-10-17 04:50:00.000000	EA16106_WYNN_S_WYNN_S_HAMRIK5_1	real_time	98.52
2026-10-17 04:50:00.000000	RDT_SO_MW (South_North) - STR+Lost_Gen Zone_1	reserve	24.84
2026-10-17 04:50:00.000000	NDEX	real_time	49.98
2026-10-17 04:45:00.000000	RDT_SO_MW (South_North)	sub_regional	11.35
2026-10-17 04:45:00.000000	EA16106_WYNN_S_WYNN_S_HAMRIK5_1	real_time	98.15
2026-10-17 04:45:00.000000	RDT_SO_MW (South_North)	real_time	11.35
2026-10-17 04:45:00.000000	NDEX	real_time	36.32
2026-10-17 04:45:00.000000	RDT_SO_MW (South_North) - STR+Lost_Gen Zone_1	reserve	0.16
2026-10-17 04:45:00.000000	IPL13095_HANNAIPL_132-30_1	real_time	27.57
2026-10-17 04:40:00.000000	NDEX	real_time	55.59
2026-10-17 04:40:00.000000	IPL13095_HANNAIPL_132-30_1	real_time	65.37
2026-10-17 04:40:00.000000	RDT_SO_MW (South_North) - STR+Lost_Gen Zone_1	reserve	30.84
2026-10-17 04:35:00.000000	EA16106_WYNN_S_WYNN_S_HAMRIK5_1	real_time	73.19
2026-10-17 04:35:00.000000	IPL13095_HANNAIPL_132-30_1	real_time	61.16
2026-10-17 04:35:00.000000	NDEX	real_time	52.83
2026-10-17 04:35:00.000000	RDT_SO_MW (South_North) - STR+Lost_Gen Zone_1	reserve	25.75
2026-10-17 04:30:00.000000	IPL13095_HANNAIPL_132-30_1	real_time	17.03
2026-10-17 04:30:00.000000	NDEX	real_time	32.29
2026-10-17 04:25:00.000000	IPL13095_HANNAIPL_132-30_1	real_time	17.73
2026-10-17 04:25:00.000000	NDEX	real_time	39.22
2026-10-17 04:25:00.000000	RDT_SO_MW (South_North) - STR+Lost_Gen Zone_1	reserve	3.3

Coverage

No time-indexed data — coverage isn’t applicable to this dataset.

Related congestion & constraints data

Related congestion & constraints data
Dataset	Description
Annual real-time constraint historyMISO · year publication	MISO's Annual real-time constraint history. Each row preserves a publisher record, workbook row, or report document with its source member and row index. Source timestamps, units, geographic scope, and revision qualifiers are retained in record_json; event_time is collection time; completed_at is when the entire document became available.
Constraint Shift Factor RunsMISO · nightly (one row per completed run)	One row per COMPLETED nightly estimation of MISO 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.miso_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)MISO · nightly (60-day rolling estimation window)	Estimated sensitivity of every MISO 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 MISO's binding real-time constraints over its hub and zone roll-up of roughly 325 pricing locations, so the answers are coarser than a full nodal set. MISO publishes no contingency or terminal names, so contingency_name, from_station and to_station are always empty. 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.
Daily day-ahead binding constraintsMISO · day publication	MISO's Daily day-ahead binding constraints. Each row preserves a publisher record, workbook row, or report document with its source member and row index. Source timestamps, units, geographic scope, and revision qualifiers are retained in record_json; event_time is collection time; completed_at is when the entire document became available.