ERCOT Hourly Load by Weather Zone

Hourly weather-zone actual-load history for ERCOT, including the eight weather zones and a system total.

ercot.system_loadLoad data

One row per: event_time; Hourly cadence
Evidence: Observed market data; Published observations from the named source
Time basis: Interval-end records; UTC · event_time

Overview

Use it for zonal and historical hourly analysis; for current system-wide demand and intraday forecast error, prefer Current Supply, Demand & Intraday Forecast (ercot_supply_demand). Analysts use this archive to study load shape and peaks, normalize demand against temperature, and contextualize price moves and reserve conditions. It comes from ERCOT report NP6-345-CD.

Query contract: Preserve one canonical row per (event_time) before aggregating.
Analysis rules: Group only after preserving the declared grain: event_time.
Interpretation: For current system-wide demand, use series='realized' from ercot.supply_demand. This hourly table remains useful for weather-zone and historical-hour analysis.
Related analysis: current system-wide demand and intraday forecast error · aggregate compatible intervals to the same hour

Access

Plans: See available download and API access options. View pricing
Full history: Delivered to Snowflake, Databricks or your own storage on a schedule by Data services.
More coverage

Schema

14 columns

Column	Type
`event_time`	`DateTime64(6, 'UTC')`
`coast_mw`	`Nullable(Float64)`
`east_mw`	`Nullable(Float64)`
`far_west_mw`	`Nullable(Float64)`
`north_mw`	`Nullable(Float64)`
`north_central_mw`	`Nullable(Float64)`
`south_central_mw`	`Nullable(Float64)`
`southern_mw`	`Nullable(Float64)`
`west_mw`	`Nullable(Float64)`
`system_total_mw`	`Nullable(Float64)`
`dst_flag`	`Nullable(Bool)`
`emil_id`	`Nullable(String)`
`doc_id`	`Nullable(Int64)`
`ingested_at`	`DateTime64(6, 'UTC')`

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Sample data

event_timeDateTime64(6, 'UTC')

coast_mwNullable(Float64)

east_mwNullable(Float64)

far_west_mwNullable(Float64)

north_mwNullable(Float64)

north_central_mwNullable(Float64)

south_central_mwNullable(Float64)

southern_mwNullable(Float64)

west_mwNullable(Float64)

system_total_mwNullable(Float64)

dst_flagNullable(Bool)

emil_idNullable(String)

doc_idNullable(Int64)

ingested_atDateTime64(6, 'UTC')

2026-11-09 12:00:00.000000

11254.98

1379.78

7163.34

1261.7

11610.37

6837.29

3764.29

1765.54

45037.3

false

NULL

2026-11-09 12:22:28.768717

2026-11-09 11:00:00.000000

10771

1345.11

7160.12

1174.95

10922.67

6526.53

3692.84

1726.5

43319.72

false

NULL

2026-11-09 12:22:28.768717

2026-11-09 11:00:00.000000

10771

1345.11

7160.12

1174.95

10922.67

6526.53

3692.84

1726.5

43319.72

false

NULL

2026-11-09 11:22:28.234899

2026-11-09 10:00:00.000000

10556.28

1300.44

7186.61

1162.5

10706.93

6421.51

3615.91

1725.06

42675.22

false

NULL

2026-11-09 12:22:28.768717

2026-11-09 10:00:00.000000

10556.28

1300.44

7186.61

1162.5

10706.93

6421.51

3615.91

1725.06

42675.22

false

NULL

2026-11-09 11:22:28.234899

2026-11-09 09:00:00.000000

10545.32

1304.79

7182.7

1175.79

10741.55

6453.54

3558.69

1823.35

42785.74

false

NULL

2026-11-09 12:22:28.768717

2026-11-09 09:00:00.000000

10545.32

1304.79

7182.7

1175.79

10741.55

6453.54

3558.69

1823.35

42785.74

false

NULL

2026-11-09 11:22:28.234899

2026-11-09 08:00:00.000000

10678.82

1327.24

7122.62

1223.13

10875.31

6555.26

3614.1

1927.59

43324.07

false

NULL

2026-11-09 12:22:28.768717

2026-11-09 08:00:00.000000

10678.82

1327.24

7122.62

1223.13

10875.31

6555.26

3614.1

1927.59

43324.07

false

NULL

2026-11-09 11:22:28.234899

2026-11-09 07:00:00.000000

10933.07

1324.25

7099.62

1269.73

11338.44

6785.97

3873.32

1964.58

44588.96

false

NULL

2026-11-09 12:22:28.768717

2026-11-09 07:00:00.000000

10933.07

1324.25

7099.62

1269.73

11338.44

6785.97

3873.32

1964.58

44588.96

false

NULL

2026-11-09 11:22:28.234899

2026-11-09 06:00:00.000000

11274.68

1382.76

7168.29

1255.41

11910.2

7117.81

4070.65

2014.09

46193.89

false

NP6-345-CD

NULL

2026-11-09 12:32:51.788411

2026-11-09 05:00:00.000000

11750.69

1405.19

7144.16

1419.68

12322.85

7528.08

4227.56

2057.03

47855.23

false

NP6-345-CD

NULL

2026-11-09 12:32:51.788411

2026-11-09 05:00:00.000000

11750.69

1405.19

7144.16

1419.68

12322.85

7528.08

4227.56

2057.03

47855.23

false

NULL

2026-11-09 05:22:28.103862

2026-11-09 04:00:00.000000

12225.14

1426.99

7053.59

1207.81

12875.37

7910.49

4330.39

2094.3

49124.09

false

NP6-345-CD

NULL

2026-11-09 12:32:51.788411

2026-11-09 04:00:00.000000

12225.14

1426.99

7053.59

1207.81

12875.37

7910.49

4330.39

2094.3

49124.09

false

NULL

2026-11-09 05:22:28.103862

2026-11-09 03:00:00.000000

12464.22

1413.8

7049.94

1270.31

13318.6

8182.19

4448.53

2111.88

50259.46

false

NP6-345-CD

NULL

2026-11-09 12:32:51.788411

2026-11-09 03:00:00.000000

12464.22

1413.8

7049.94

1270.31

13318.6

8182.19

4448.53

2111.88

50259.46

false

NULL

2026-11-09 05:22:28.103862

2026-11-09 02:00:00.000000

12606.45

1442.13

7039.24

1350.13

13712.41

8342.6

4496

2146.96

51135.92

false

NP6-345-CD

NULL

2026-11-09 12:32:51.788411

2026-11-09 02:00:00.000000

12606.45

1442.13

7039.24

1350.13

13712.41

8342.6

4496

2146.96

51135.92

false

NULL

2026-11-09 05:22:28.103862

2026-11-09 01:00:00.000000

12685.78

1481.47

7038.08

1366.76

14009.7

8432.33

4529.33

2150.1

51693.56

false

NP6-345-CD

NULL

2026-11-09 12:32:51.788411

2026-11-09 01:00:00.000000

12685.78

1481.47

7038.08

1366.76

14009.7

8432.33

4529.33

2150.1

51693.56

false

NULL

2026-11-09 05:22:28.103862

2026-11-09 00:00:00.000000

12486.06

1495.8

6994.29

1402.17

13990.26

8249.39

4411.16

2139.87

51168.99

false

NP6-345-CD

NULL

2026-11-09 12:32:51.788411

2026-11-09 00:00:00.000000

12486.06

1495.8

6994.29

1402.17

13990.26

8249.39

4411.16

2139.87

51168.99

false

NULL

2026-11-09 05:22:28.103862

2026-11-08 23:00:00.000000

12236.39

1479.26

7150.67

1396.48

13716.95

8023.25

4412.06

2119.63

50534.7

false

NP6-345-CD

NULL

2026-11-09 12:32:51.788411

25 rows

25 sample rows of 288.9KBrowse every row in Data

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Coverage

Complete: 100.0%
Gap days: 0
Days with data: 5,061

Show coverage history

Coverage: 100.0%Days with data: 5,061Gaps: 0

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Related data

Related load data
Dataset	Description
ERCOT 2-Day Aggregate Generation, Load and OutputERCOT · day publication	The two-day disclosure of aggregated generation, load and resource output (report NP3-910-ER), every member. 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.
ERCOT Current Supply, Demand and Intraday ForecastERCOT · 5-minute	ERCOT's public real-time supply and demand dashboard at five-minute resolution. This is the preferred dataset for a current actual-versus-forecast demand comparison: series='realized' reports observed demand_mw and committed capacity_mw; series='intraday_forecast' reports demand_mw, capacity_mw, and available_mw for the same target event_time at successive source_time vintages, where the on-the-hour values are hourly-average forecasts and the points between them are interpolated; and series='forward_forecast' reports forecasted_demand_mw and avail_cap_gen_mw farther ahead. Operators, traders, and researchers use it to measure current forecast error, headroom, and how forecasts converge toward realized demand.
ERCOT Hourly Actual LoadERCOT · hourly	Actual hourly electricity demand in ERCOT, one row per hour with a system total and one column per weather zone. 119,475 hours, 2013-01 to now. Columns: system_mw plus coast_mw, east_mw, far_west_mw, north_mw, north_central_mw, south_central_mw, southern_mw, west_mw. system_mw is ERCOT's own published total, and the eight zones sum to it to within 0.03 MW — so a zone share is simply zone_mw / system_mw. Wide rather than long, so "load right now" and "the 8 weather zone shares of it" are one row, not 9. Every market's load table in this catalog shares the system_mw column and the same hourly grain, so a cross-market demand comparison needs no reshaping.
ERCOT Mid-Term Load Forecast (MTLF)ERCOT · hourly (7-day forecast)	ERCOT's mid-term load forecast (MTLF) for the Texas grid, giving the expected electricity demand for each of the next seven days at hourly resolution. The forecast is broken out by ERCOT's eight weather zones plus a system-wide total, and a new vintage is issued every hour, so you can also see how the outlook for a given day shifts as it approaches. Operators use this to plan generation and reserves, while traders and researchers use it to anticipate price and tightness conditions and to study how forecasts evolve and where they miss. The official source is ERCOT report NP3-565-CD, Seven-Day Load Forecast by Weather Zone.