Wind and Solar Curtailment

Published wind and solar curtailment from CAISO's Daily Renewable Report HTML, by report hour, fuel, economic/self-schedule/operator-instruction category, and local/system reason.

Generation data CAISO market

Query with the agent

Native record

report hour x fuel x curtailment category x local/system reason

daily report (hourly observations) publication cadence

Evidence

Observed market data

Published observations from the named source

Time basis

Date-labelled records

UTC · event_time

Overview

curtailment_mwh is hourly curtailed energy; curtailment_mw is the hourly maximum curtailed power, not average MW. event_time preserves the report's UTC chart labels for its reporting date; use the report-day basis for daily totals, not an assumed UTC dispatch clock for price joins. The former Production and Curtailments workbook was retired on 2025-06-01. This renewable-curtailment report is distinct from the generator outage/availability report.

Query contract

Read FINAL to retain one current revision per report hour, fuel, category and reason. The source HTML encodes report-hour labels with Date.UTC; event_time retains those labels, not an independently verified UTC dispatch instant.

Analysis rules

Sum curtailment_mwh across the 24 report-hour labels and the disjoint fuel/type/reason rows for a daily energy total; report coverage and non-null observations.
curtailment_mw is the hourly maximum curtailed power. Take max for a peak; never sum hourly maxima into MWh or substitute them for hourly average MW.

Interpretation

Missing reports or null measurements are unknown coverage, not zero curtailment. Explicit published zeroes are observations.
Renewable curtailment is separate from the planned/forced non-operational generator report.

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.

CAISO MCP API reference

HTTP endpoint

POST /api/v1/datasets/caiso_curtailment/query

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

Schema7

Column

Type

event_timeDateTime64(6, 'UTC')

curtailment_typeLowCardinality(String)

curtailment_reasonLowCardinality(String)

fuel_typeLowCardinality(String)

curtailment_mwhNullable(Float64)

curtailment_mwNullable(Float64)

ingested_atDateTime64(6, 'UTC')

Sample data

event_time	curtailment_type	curtailment_reason	fuel_type	ingested_at
2026-10-17 23:00:00.000000	self-schedule	system	wind	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	self-schedule	system	solar	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	self-schedule	local	wind	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	self-schedule	local	solar	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	operator-instruction	system	wind	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	operator-instruction	system	solar	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	operator-instruction	local	wind	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	operator-instruction	local	solar	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	economic	system	wind	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	economic	system	solar	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	economic	local	wind	2026-10-18 18:58:28.743808
2026-10-17 23:00:00.000000	economic	local	solar	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	self-schedule	system	wind	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	self-schedule	system	solar	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	self-schedule	local	wind	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	self-schedule	local	solar	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	operator-instruction	system	wind	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	operator-instruction	system	solar	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	operator-instruction	local	wind	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	operator-instruction	local	solar	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	economic	system	wind	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	economic	system	solar	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	economic	local	wind	2026-10-18 18:58:28.743808
2026-10-17 22:00:00.000000	economic	local	solar	2026-10-18 18:58:28.743808
2026-10-17 21:00:00.000000	self-schedule	system	wind	2026-10-18 18:58:28.743808

Coverage

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

Related generation data

Related generation data
Dataset	Description
Battery Storage Net OutputCAISO · 5-minute	Observed five-minute net output from standalone and hybrid battery storage across the CAISO footprint. The total supply_mw field is positive when batteries are discharging into the grid and negative when they are charging from the grid; standalone_batteries_mw and hybrid_batteries_mw are components of that total, not additional generation to add on top. This is the live operating series published in CAISO Today's Outlook, not nameplate capacity or state of charge.
Daily HTML report and corrected publicationCAISO · day publication	CAISO's Daily HTML report and corrected publication. 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.
EDAM Wind and Solar Forecast by Balancing AreaCAISO · hourly delivery; half-hourly collection	CAISO OASIS EDAM wind and solar generation forecasts by balancing-authority group, with the delivery hour and publication vintage retained separately. Forecasts for participating areas are not CAISO system generation.
Renewable Generation ForecastCAISO · 5-minute RTD and hourly DAM	CAISO wind and solar forecasts by trading hub and market run. event_time is delivery time and source_time is publication time. Historical forecast-error analysis must use the last source_time at or before delivery; using a later revision introduces hindsight.