Energy
16 columns
120 rows
8 formats

Warehouse Energy Consumption Logs

This dataset provides granular, hourly records of energy consumption, cost, emissions, and operational context for e-commerce warehouses. It enables detailed analysis of usage patterns, anomaly detection, and measurement of efficiency upgrades, supporting sustainability and cost-saving initiatives for warehouse operations.

last updated 10 Jan 2026
by GoMask

The brief that made it

Monitor and optimize warehouse energy usage to reduce operational costs

Sample rows

preview · 8 of 120 rows · all 16 columns

log_idstring	energy_sourcestring	energy_consumed_kwhfloat	efficiency_upgrade_flagboolean	warehouse_postal_codestring	warehouse_idstring	warehouse_namestring	warehouse_street_addressstring	warehouse_citystring	warehouse_statestring	warehouse_countrystring	timestampdatetime	energy_cost_usdfloat	co2_emissions_kgfloat	is_anomalyboolean	notesstring
LOG00001	grid	142.7	false	43215	WH001	Central Fulfillment	101 Main St	Columbus	OH	USA	2024-04-30T08:00:00Z	19.85	65.2	false	blank
LOG00002	grid	182.3	false	60607	WH002	Urban Express Hub	202 5th Ave	Chicago	IL	USA	2024-04-30T09:00:00Z	23.6	81.1	false	blank
LOG00003	grid	229.9	true	30303	WH003	Southern Storage	303 Market Rd	Atlanta	GA	USA	2024-04-29T13:00:00Z	31.2	97.6	false	LED lighting upgrade implemented April 28
LOG00004	solar	34.3	true	80202	WH004	Mountain Logistics	404 Hillside Dr	Denver	CO	USA	2024-04-29T14:00:00Z	4.74	0.09	false	Solar panel installation completed April 25
LOG00005	wind	28.9	true	53703	WH005	Rural Hub Depot	505 County Hwy	Madison	WI	USA	2024-04-29T15:00:00Z	3.86	0.03	false	Wind turbine maintenance completed April 28
LOG00006	grid	94.8	false	92101	WH006	Pacific Distribution Center	606 Ocean View	San Diego	CA	USA	2024-04-28T08:00:00Z	12.2	42.6	false	blank
LOG00007	solar	61.2	true	02110	WH007	Eastside Depot	707 Elm St	Boston	MA	USA	2024-04-28T09:00:00Z	8.1	0.05	false	Efficiency upgrade: Solar array expansion completed April 27
LOG00008	grid	0	false	55401	WH008	Northern Distribution	808 Lake Ave	Minneapolis	MN	USA	2024-04-28T10:00:00Z	0	0	true	Power outage due to severe weather
LOG00009	wind	27.5	true	80010	WH009	Aurora Storage	909 Sunrise Blvd	Aurora	CO	USA	2024-04-28T11:00:00Z	3.67	0.02	false	Wind turbine upgrade implemented April 26
LOG00010	grid	138.9	false	85001	WH010	Desert Outpost	1010 Sand Rd	Phoenix	AZ	USA	2024-04-27T08:00:00Z	18.5	63.8	false	blank
LOG00011	grid	820.3	false	W1A 1AA	WH011	Diamond Storage	1111 Crystal Ln	London	England	UK	2024-03-15T10:00:00Z	148.2	391.5	true	Unexpected spike in demand; equipment malfunction
LOG00012	grid	105.6	false	20095	WH012	Baltic Storage	1212 Hafenstr	Hamburg	Hamburg	Germany	2024-03-15T11:00:00Z	18.45	52.1	false	blank
LOG00013	grid	228.7	false	75010	WH013	Metro Storage Hub	1313 Rue Lafayette	Paris	Île-de-France	France	2024-03-15T12:00:00Z	42.8	98.9	false	blank
LOG00014	grid	133.2	false	2000	WH014	Mega Distribution	1414 Industrial Ave	Sydney	NSW	Australia	2024-03-15T13:00:00Z	24.7	56.7	false	blank
LOG00015	generator	0	false	W1A 1AA	WH015	Diamond Storage	1515 Crystal Ln	London	England	UK	2024-03-16T10:00:00Z	0	0	true	Generator system failed; emergency maintenance
LOG00016	grid	8500	false	75010	WH016	Metro Storage Hub	1616 Rue Lafayette	Paris	Île-de-France	France	2024-03-16T11:00:00Z	1539.75	4227.4	true	Extreme peak demand; equipment malfunction
LOG00017	grid	153.8	false	W1A 1AA	WH017	Diamond Storage	1717 Crystal Ln	London	England	UK	2024-03-16T12:00:00Z	28.5	67.2	false	blank
LOG00018	generator	82.2	false	2000	WH018	Mega Distribution	1818 Industrial Ave	Sydney	NSW	Australia	2024-03-16T13:00:00Z	14.8	40.1	false	Generator run due to grid maintenance
LOG00019	grid	176.2	false	20095	WH019	Baltic Storage	1919 Hafenstr	Hamburg	Hamburg	Germany	2024-03-16T14:00:00Z	32.8	76.3	false	blank
LOG00020	grid	112.5	false	92101	WH020	Pacific Distribution Center	2020 Ocean View	San Diego	CA	USA	2024-03-17T08:00:00Z	14.9	49.3	false	blank

What the 120 rows show

from the 120-row sample

Solar (energy source) stands out: 12 of its 15 rows have efficiency_upgrade_flag = true, against 12 of 105 for the rest.

20%efficiency_upgrade_flag = true
123.1median energy_consumed_kwh
8warehouse countries
24warehouse names
24warehouse states
29warehouse cities

Efficiency upgrade flag rate by energy_sourceefficiency_upgrade_flag = true

energy_consumed_kwh120 rows, in bands of 1,000

Median 123.1, from 0.0 to 8,500.

warehouse_postal_code120 rows · top 10 of 38 values

20009
432158
303037
200957
850016
W1A 1AA6
921015
606074
802024
750104

16 columns by typefrom the column list below

string 10
float 3
datetime 1
boolean 2

Columns

16 columns in four groups

blueprint · 16 columns
column	type	description	example
Text 10 columns
`log_id`	string	Unique identifier for each energy consumption log entryunique	LOG00001
`warehouse_id`	string	Unique identifier for the warehouse where energy consumption is recorded	WH001
`warehouse_name`	string	Name of the warehouseoptional	Central Fulfillment
`warehouse_street_address`	string	Street address of the warehouseoptional	101 Main St
`warehouse_city`	string	City where the warehouse is locatedoptional	Columbus
`warehouse_state`	string	State or province where the warehouse is locatedoptional	OH
`warehouse_postal_code`	string	Postal or ZIP code of the warehouse locationoptional	43215
`warehouse_country`	string	Country where the warehouse is located8 countries · optional	USA
`energy_source`	string	Primary source of energy used (e.g., grid, solar, wind, generator)grid · solar · wind · generator · other · optional	grid
`notes`	string	Additional notes or comments about this log entry (e.g., maintenance, outages, unusual events)optional	Peak usage period.
Numbers 3 columns
`energy_consumed_kwh`	float	Total energy consumed during the hour, measured in kilowatt-hours (kWh)0 or more	142.7
`energy_cost_usd`	float	Cost of energy consumed during the hour, in US dollars0 or more · optional	19.85
`co2_emissions_kg`	float	Estimated CO2 emissions produced during the hour, in kilograms0 or more · optional	65.2
Dates and times 1 column
`timestamp`	datetime	Date and time (hourly) when the energy consumption was recorded	2024-04-30T08:00:00Z
True or false 2 columns
`is_anomaly`	boolean	Indicates whether this log entry has been flagged as an anomalyoptional	false
`efficiency_upgrade_flag`	boolean	Indicates if an efficiency upgrade was implemented prior to or during this periodoptional	false

Use it for

An energy dashboard
The efficiency_upgrade_flag rate, energy_consumed_kwh by energy_source and a breakdown of warehouse_postal_code. Excel, Power BI or Tableau.
Why do 24 of 120 rows have efficiency_upgrade_flag = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Logs120
LOG00001142.7grid
LOG00003229.9grid
LOG0000434.3solar
A software demo
Believable logs with warehouse_id, warehouse_name and warehouse_street_address to fill a screen in front of a buyer.

This dataset120 rows16 columns

Yours1,000 rows16 columnswarehouse_street_address: UK only

blueprint · warehouse-energy-consumption-logs

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 16 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.

Rules it was built with

Each row represents one warehouse’s energy usage per hour.
Include warehouse ID, location type (urban/suburban/rural), and energy source (grid/renewable/mixed).
Flag hours with consumption above baseline threshold for anomaly detection.
List associated operational activity type (receiving, packing, idle, maintenance).
Calculate cumulative daily consumption per warehouse.
Indicate whether any efficiency measures are active (LED, smart HVAC, solar panels).

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: warehouse-energy-consumption-logs

What should your data show?

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Sample rows

What the 120 rows show

Columns

Use it for

An energy dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Energy

What should your data show?