Energy Consumption Time Series
This dataset provides detailed, hourly electricity consumption records for both commercial and residential consumers, enriched with contextual information such as region, temperature, and holiday indicators. It is ideal for utility companies and researchers seeking to perform load forecasting, demand analysis, and anomaly detection at a granular level.
Sample rows
preview · 8 of 200 rows · all 10 columns| record_idstring | consumer_typestring | energy_consumed_kwhfloat | is_holidayboolean | consumer_idstring | regionstring | timestampdatetime | peak_demand_kwfloat | temperature_celsiusfloat | anomaly_flagboolean |
|---|---|---|---|---|---|---|---|---|---|
| REC00001 | residential | 2.6 | false | R1001 | NY-10001 | 2024-01-05T06:00:00 | 2.2 | -3 | false |
| REC00002 | residential | 1.8 | false | R1002 | IL-60616 | 2024-01-15T19:00:00 | 1.3 | -9.5 | false |
| REC00003 | commercial | 49.2 | true | C2001 | CA-94107 | 2024-02-19T13:00:00 | 20.1 | 13.8 | false |
| REC00004 | residential | 0 | false | R1003 | MN-55105 | 2024-01-18T23:00:00 | 0 | -22 | true |
| REC00005 | commercial | 75.5 | false | C2002 | TX-75201 | 2024-03-10T10:00:00 | 35.6 | 17.1 | false |
| REC00006 | residential | 3.5 | false | R1004 | FL-33101 | 2024-06-15T15:00:00 | 3.1 | 32 | false |
| REC00007 | commercial | 0 | true | C2003 | WA-98101 | 2024-05-27T08:00:00 | 0 | 12 | true |
| REC00008 | commercial | 120.3 | false | C2004 | GA-30301 | 2024-04-14T16:00:00 | 41.5 | 24.7 | false |
| REC00009 | residential | 7.2 | true | R1005 | AZ-85001 | 2024-07-04T17:00:00 | 5.5 | 39.8 | false |
| REC00010 | residential | 0.1 | false | R1006 | OR-97201 | 2024-03-31T04:00:00 | blank | 7.9 | true |
| REC00011 | residential | 4.7 | false | R1007 | CA-90001 | 2024-08-14T21:00:00 | 3.8 | 28.9 | false |
| REC00012 | commercial | 2400 | true | C2005 | IL-60616 | 2023-12-25T12:00:00 | 600 | -10.2 | true |
| REC00013 | residential | 1.5 | false | R1008 | CO-80202 | 2024-02-14T18:00:00 | 0.9 | -2.5 | false |
| REC00014 | commercial | 62.9 | false | C2006 | NV-89101 | 2024-04-24T02:00:00 | 19.4 | 20 | false |
| REC00015 | residential | 3.2 | true | R1009 | WA-98101 | 2024-09-02T09:00:00 | 2.7 | 18.5 | false |
| REC00016 | commercial | 0 | true | C2007 | MI-48201 | 2024-06-19T20:00:00 | 0 | 21.2 | true |
| REC00017 | commercial | 83.7 | false | C2008 | NC-28202 | 2024-03-27T14:00:00 | 33.6 | 15.3 | false |
| REC00018 | residential | 1.1 | true | R1010 | MA-02118 | 2024-12-25T05:00:00 | 0.8 | -4.7 | false |
| REC00019 | commercial | 120 | true | C2009 | OH-44101 | 2024-11-28T08:00:00 | 43 | 2.3 | false |
| REC00020 | residential | 2.4 | false | R1011 | PA-19103 | 2024-04-08T12:00:00 | 1.7 | 13.1 | false |
What the 200 rows show
from the 200-row sample- 55%is_
holiday = true - 4.1median energy_
consumed_ kwh - 3.8median peak_
demand_ kw - 17.0median temperature_
celsius
Median 4.1, from 0.0 to 5,200.
- string 4
- float 3
- datetime 1
- boolean 2
Columns
10 columns in four groups| column | type | description | example |
|---|---|---|---|
| Text 4 columns | |||
record_id | string | Unique identifier for each hourly energy consumption recordunique | REC00001 |
consumer_id | string | Unique identifier for the consumer (either residential or commercial) | R1001 |
consumer_type | string | Type of consumer: residential or commercialresidential · commercial | residential |
region | string | Geographic region or zone of the consumer (e.g., city, utility zone, or postal code) | NY-10001 |
| Numbers 3 columns | |||
energy_consumed_kwh | float | Amount of electricity consumed during the hour, measured in kilowatt-hours (kWh)0 or more | 2.6 |
peak_demand_kw | float | Maximum power demand during the hour, measured in kilowatts (kW)0 or more · optional | 2.2 |
temperature_celsius | float | Ambient temperature at the time of recording, in degrees Celsiusoptional | -3 |
| Dates and times 1 column | |||
timestamp | datetime | Date and time (hourly granularity) when the electricity demand was recorded | 2024-01-05T06:00:00 |
| True or false 2 columns | |||
is_holiday | boolean | Indicates whether the timestamp falls on a public holiday (true/false)optional | false |
anomaly_flag | boolean | Indicates if the record has been flagged as an anomaly (true/false)optional | false |
Use it for
An energy dashboard
The is_
holiday rate and energy_ consumed_ kwh by consumer_ type. Excel, Power BI or Tableau. Why do 110 of 200 rows have is_
holiday = true? A class exercise
Hand out the rows and one question. Everyone works from the same 200 rows.
- Records200REC000012.6resident…REC0000349.2commerci…REC000070commerci…
A software demo
Believable records with consumer_
id, consumer_ type and region to fill a screen in front of a buyer.
blueprint · energy-consumption-time-series
Behind this dataset
Same schema. As many rows as you need.
These 200 rows came out of a blueprint — 10 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
- Weekends have lower commercial usage
- Weather affects daily demand patterns
- Holiday spikes represented in residential data
- Missing values simulated during outages
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- energy-consumption-time-series