Energy
16 columns
202 rows
8 formats

Energy Market Price Forecasting

This dataset provides granular hourly and daily records of wholesale energy market prices, demand and supply signals, and contextual factors such as weather and holidays across multiple market regions. It is designed for advanced price forecasting, market analysis, and the development of predictive models for energy trading and grid management.

last updated 29 Jul 2025
by GoMask

The brief that made it

Developing machine learning models for energy price forecasting

Sample rows

preview · 8 of 202 rows · all 16 columns

market_idstring	weather_conditionstring	weather_temperature_cfloat	is_holidayboolean	currencystring	market_namestring	datetimedatetime	frequencystring	pricefloat	total_demand_mwfloat	total_supply_mwfloat	renewable_supply_mwfloat	nonrenewable_supply_mwfloat	forecasted_pricefloat	forecasted_demand_mwfloat	forecasted_supply_mwfloat
PJM	clear	33.7	false	USD	PJM Interconnection	2023-07-15T16:00:00Z	hourly	172.34	66850	67920	15430	52490	169.6	67550	67700
CAISO	clear	42.1	false	USD	California ISO	2023-08-10T20:00:00Z	hourly	2541.1	52800	54600	23600	31000	2503.2	53000	54510
NEM-QLD	clear	45.3	true	AUD	NEM Queensland	2023-01-26T00:00:00Z	daily	9999.99	18300	18670	10260	8410	9955.5	18070	18540
EPEX	cloudy	11.8	false	EUR	EPEX Spot France	2023-10-12T00:00:00Z	daily	94.14	68400	68710	39400	29310	95.2	68050	68600
SWIS	clear	35.1	false	AUD	South West Interconnected System	2023-02-11T13:00:00Z	hourly	118.43	5420	5560	3360	2200	116.81	5409	5545
PJM	snowy	-2.8	true	USD	PJM Interconnection	2023-12-25T00:00:00Z	daily	89.12	59000	59530	18800	40730	91.1	59150	59500
UKPX	cloudy	1.3	false	GBP	UK Power Exchange	2023-11-03T02:00:00Z	hourly	0	0	0	0	0	0	0	0
ISO-NE	clear	31.5	true	USD	ISO New England	2023-07-04T14:00:00Z	hourly	149.88	22500	23600	5500	18100	147.45	22700	23520
AESO	snowy	-21.5	false	CAD	Alberta Electric System Operator	2023-01-16T00:00:00Z	daily	78.92	10200	10400	3900	6500	79.2	10290	10420
NO-1	windy	6.5	false	NOK	Nord Pool Norway NO-1	2023-03-18T00:00:00Z	daily	44.13	16900	17010	14300	2710	43.85	17000	17000
ERCOT	clear	44.2	false	USD	ERCOT Texas	2023-08-20T18:00:00Z	hourly	1201.99	77900	79300	25100	54200	1218.3	78000	79000
AEMO	other	36.4	false	AUD	Australian Energy Market Operator	2023-02-01T00:00:00Z	daily	59.94	20900	21080	11200	9880	60.32	21010	21020
SPP	windy	34.7	false	USD	Southwest Power Pool	2023-09-03T17:00:00Z	hourly	97.1	43800	44400	11500	32900	98.25	43890	44405
SING	rainy	30	false	SGD	Singapore Wholesale Electricity Market	2023-06-17T00:00:00Z	daily	66.24	6700	6770	300	6470	66.8	6725	6780
FRANCE	cloudy	16.5	false	EUR	French Power Market	2023-04-14T00:00:00Z	daily	52.71	72000	72390	36800	35590	53.1	72230	72380
NYISO	snowy	-6.2	true	USD	New York ISO	2023-01-01T00:00:00Z	daily	125.77	19500	19740	6200	13540	124.2	19400	19700
PJM	clear	37.8	false	USD	PJM Interconnection	2023-09-09T19:00:00Z	hourly	156.32	73100	73390	20900	52490	158.2	73300	73420
EPEX	cloudy	9.4	false	EUR	EPEX Spot Germany	2023-03-15T00:00:00Z	daily	53.72	81000	81100	38600	42500	54.9	81005	81090
NEM-NSW	clear	35.8	true	AUD	NEM New South Wales	2023-01-01T00:00:00Z	daily	92.84	12700	12890	7010	5880	91.8	12760	12870
ERCOT	clear	39.9	false	USD	ERCOT Texas	2023-09-02T21:00:00Z	hourly	201.62	69800	70700	22500	48200	199.18	69900	70710

What the 202 rows show

from the 202-row sample

Snowy (weather condition) stands out: mean weather_temperature_c is -7.1, against 25.4 for the rest.

34%is_holiday = true
27.1median weather_temperature_c
2frequencies
50markets
84.5median price
19,500median total_demand_mw

weather_temperature_c202 rows, in bands of 10

Median 27.1, from -21.5 to 46.7.

currency202 rows · top 10 of 11 values

USD70
EUR33
AUD31
GBP16
NOK16
SGD12
CAD11
INR4
BRL4
JPY3

16 columns by typefrom the column list below

string 5
float 9
datetime 1
boolean 1

Columns

16 columns in four groups

blueprint · 16 columns
column	type	description	example
Text 5 columns
`market_id`	string	Unique identifier for the wholesale energy market (e.g., ISO code or market region).	PJM
`market_name`	string	Descriptive name of the energy market or region.	PJM Interconnection
`frequency`	string	Granularity of the record, either 'hourly' or 'daily'.hourly · daily	hourly
`currency`	string	Currency code for the price (e.g., USD, EUR).11 currencies	USD
`weather_condition`	string	General weather condition (e.g., clear, cloudy, rainy, snowy) for the market region and time period.6 values · optional	clear
Numbers 9 columns
`price`	float	Wholesale market clearing price for the given time period (e.g., $/MWh).0 or more	172.34
`total_demand_mw`	float	Total electricity demand in megawatts (MW) for the market and time period.0 or more · optional	66850
`total_supply_mw`	float	Total electricity supply in megawatts (MW) for the market and time period.0 or more · optional	67920
`renewable_supply_mw`	float	Amount of supply from renewable sources in megawatts (MW) for the market and time period.0 or more · optional	15430
`nonrenewable_supply_mw`	float	Amount of supply from non-renewable sources in megawatts (MW) for the market and time period.0 or more · optional	52490
`forecasted_price`	float	Forecasted market price for the given time period, if available.0 or more · optional	169.6
`forecasted_demand_mw`	float	Forecasted electricity demand in megawatts (MW) for the market and time period, if available.0 or more · optional	67550
`forecasted_supply_mw`	float	Forecasted electricity supply in megawatts (MW) for the market and time period, if available.0 or more · optional	67700
`weather_temperature_c`	float	Average temperature in Celsius for the market region and time period, if available.optional	33.7
Dates and times 1 column
`datetime`	datetime	Timestamp indicating the date and time of the record (hourly or daily granularity).	2023-07-15T16:00:00Z
True or false 1 column
`is_holiday`	boolean	Indicates if the date is a public holiday in the market region.optional	false

Use it for

An energy dashboard
The is_holiday rate, weather_temperature_c by weather_condition and a breakdown of currency. Excel, Power BI or Tableau.
Why do the 28 snowy rows have a mean weather_temperature_c of -7.1?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Markets202
PJM33.7clear
NEM-QLD45.3clear
PJM-2.8snowy
A software demo
Believable markets with market_name, datetime and frequency to fill a screen in front of a buyer.

This dataset202 rows16 columns

Yours1,000 rows16 columns

blueprint · energy-market-price-forecasting

Behind this dataset

Same schema. As many rows as you need.

These 202 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

Price series segmented by region
Demand and supply inputs provided
Price spikes during peak seasons
Regulatory cap/floor events simulated

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

Open the blueprint in Data Factory

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-market-price-forecasting

What should your data show?

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Sample rows

What the 202 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?