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ISO-NE Day-Ahead Binding Constraints

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

Native record
constraint x delivery hour
hourly publication cadence
Evidence
Cleared day-ahead market
A market outcome, not a physical observation
Time basis
Interval-start records
UTC · event_time

Overview

24,146 rows, 2022-01 to now. Columns: event_time, constraint_name, shadow_price_usd_mwh, plus contingency. 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. ISO-NE's negative source marginal values are sign-normalized here so larger positive values have the same meaning as the other markets. 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 event_time to iso_ne.lmp rows filtered to market_run='da_hourly_final' and scope='all'; the constraint explains the market-wide congestion pattern, not one location's share of it

Interpretation

  • shadow_price_usd_mwh is sign-normalized: ISO-NE's source marginal_value is negated because the source publishes a binding marginal value as negative in more than 99.9% of rows. In this canonical table, a larger positive value consistently means a more expensive binding constraint.
  • The handful of positive source marginal values become negative canonical shadow prices and remain present. They are preserved anomalies, not clipped or silently discarded.

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.

HTTP endpoint
POST /api/v1/datasets/isone_canonical_constraints_da/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)
contingencyLowCardinality(String)
shadow_price_usd_mwhNullable(Float64)

Sample data

event_timeconstraint_namecontingencyshadow_price_usd_mwh
2026-10-17 02:00:00.000000Node_Shoreham_ExportGeneric Constraint0.53
2026-10-17 02:00:00.000000S_NAUGTK1580ALNSTEV12322.02
2026-10-17 02:00:00.000000RUM-EXInterface7.01
2026-10-17 02:00:00.000000VNRDWInterface42.23
2026-10-17 01:00:00.000000Node_Shoreham_ExportGeneric Constraint5.16
2026-10-17 01:00:00.000000RUMFIPInterface4.4
2026-10-17 01:00:00.000000VNRDWInterface39.18
2026-10-17 00:00:00.000000RUMFIPInterface10.78
2026-10-17 00:00:00.000000VNRDWInterface43.78
2026-10-16 23:00:00.000000RUMFIPInterface20.97
2026-10-16 23:00:00.000000JOHNST_TT172S-3ALNS17116.29
2026-10-16 23:00:00.000000VNRDWInterface54.49
2026-10-16 22:00:00.000000JOHNST_TT172S-3ALNS17125.23
2026-10-16 22:00:00.000000RUMFIPInterface29.27
2026-10-16 22:00:00.000000S_NAUGTK1580ALNSTEV1232143.1
2026-10-16 22:00:00.000000BAKER_ST110-511-4ALNActual0.02
2026-10-16 22:00:00.000000VNRDWInterface63.51
2026-10-16 22:00:00.000000BAKER_ST110C110CXFActual0.02
2026-10-16 21:00:00.000000WYM-EX STABGeneric Constraint43.76
2026-10-16 21:00:00.000000RUMFIPInterface21.96
2026-10-16 21:00:00.000000BAKER_ST110-510-4ALNActual0.01
2026-10-16 21:00:00.000000JOHNST_TT172S-3ALNS17119.85
2026-10-16 21:00:00.000000BAKER_ST110D110DXFActual0.01
2026-10-16 21:00:00.000000S_NAUGTK1580ALNSTEV1232101.75
2026-10-16 21:00:00.000000VNRDWInterface58.06

Coverage

94.9% complete89 gap days1,662 days with data
Show coverage history
Coverage: 94.9%Days with data: 1,662Gaps: 89
2026
2025
2024
2023
2022
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