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CO2 Emission Prognosis Data

Total number of rows: 570,216


2017-02-04 02:20Z 2017-02-04 03:20 DK2 294
2017-02-04 02:20Z 2017-02-04 03:20 DK1 294
2017-02-04 02:15Z 2017-02-04 03:15 DK2 294
2017-02-04 02:15Z 2017-02-04 03:15 DK1 294
2017-02-04 02:10Z 2017-02-04 03:10 DK2 286
2017-02-04 02:10Z 2017-02-04 03:10 DK1 286
2017-02-04 02:05Z 2017-02-04 03:05 DK2 289
2017-02-04 02:05Z 2017-02-04 03:05 DK1 289
2017-02-04 02:00Z 2017-02-04 03:00 DK2 288
2017-02-04 02:00Z 2017-02-04 03:00 DK1 288
2017-02-04 01:55Z 2017-02-04 02:55 DK2 287
2017-02-04 01:55Z 2017-02-04 02:55 DK1 287
2017-02-04 01:50Z 2017-02-04 02:50 DK2 290
2017-02-04 01:50Z 2017-02-04 02:50 DK1 290
2017-02-04 01:45Z 2017-02-04 02:45 DK2 290
2017-02-04 01:45Z 2017-02-04 02:45 DK1 290
2017-02-04 01:40Z 2017-02-04 02:40 DK2 290
2017-02-04 01:40Z 2017-02-04 02:40 DK1 290
2017-02-04 01:35Z 2017-02-04 02:35 DK2 287
2017-02-04 01:35Z 2017-02-04 02:35 DK1 287
2017-02-04 01:30Z 2017-02-04 02:30 DK2 286
2017-02-04 01:30Z 2017-02-04 02:30 DK1 286
2017-02-04 01:25Z 2017-02-04 02:25 DK2 286
2017-02-04 01:25Z 2017-02-04 02:25 DK1 286
2017-02-04 01:20Z 2017-02-04 02:20 DK2 289
2017-02-04 01:20Z 2017-02-04 02:20 DK1 289
2017-02-04 01:15Z 2017-02-04 02:15 DK2 289
2017-02-04 01:15Z 2017-02-04 02:15 DK1 289
2017-02-04 01:10Z 2017-02-04 02:10 DK2 294
2017-02-04 01:10Z 2017-02-04 02:10 DK1 294
2017-02-04 01:05Z 2017-02-04 02:05 DK2 293
2017-02-04 01:05Z 2017-02-04 02:05 DK1 293
2017-02-04 01:00Z 2017-02-04 02:00 DK2 288
2017-02-04 01:00Z 2017-02-04 02:00 DK1 288
2017-02-04 00:55Z 2017-02-04 01:55 DK2 288
2017-02-04 00:55Z 2017-02-04 01:55 DK1 288
2017-02-04 00:50Z 2017-02-04 01:50 DK2 295
2017-02-04 00:50Z 2017-02-04 01:50 DK1 295
2017-02-04 00:45Z 2017-02-04 01:45 DK2 295
2017-02-04 00:45Z 2017-02-04 01:45 DK1 295
2017-02-04 00:40Z 2017-02-04 01:40 DK2 295
2017-02-04 00:40Z 2017-02-04 01:40 DK1 295
2017-02-04 00:35Z 2017-02-04 01:35 DK2 295
2017-02-04 00:35Z 2017-02-04 01:35 DK1 295
2017-02-04 00:30Z 2017-02-04 01:30 DK2 301
2017-02-04 00:30Z 2017-02-04 01:30 DK1 301
2017-02-04 00:25Z 2017-02-04 01:25 DK2 301
2017-02-04 00:25Z 2017-02-04 01:25 DK1 301
2017-02-04 00:20Z 2017-02-04 01:20 DK2 301
2017-02-04 00:20Z 2017-02-04 01:20 DK1 301

Data Dictionary

Column Type Label Description
Minutes5UTC timestamptz
Minutes5DK timestamp
PriceArea text
CO2Emission int4

5 minutes UTC

Name 5 minutes UTC
Description

A date and time (interval), shown in UTC time zone, where the values are valid. 00:00:00 o’clock is the first 5 minutes of a given day, interval 00:00:00 - 00:04:59, and 00:05:00 covers the second 5 minutes period (interval) of the day and so forth.

Please note: The naming is based on the length of the interval of the finest grain of the resolution

Comment

Please note that the format shown in the example applies to data download as JSON, XML or fetched through the API and is in accordance with the ISO 8601 standard. The format is slightly different when it is shown on screen or downloaded manually as CSV or XLSX. This is mainly due to readability and consideration for Excel users.

In preview (in the GUI) all timestamps are shown as (display convention) YYYY-MM-DD hh:mmZ e.g. 2017-07-14 08:05Z. The Z will remind viewers that this is UTC.

In download (CSV and XLSX) the date time are exported as YYYY-MM-DD hh:mm e.g. 2017-07-14 08:05. That is without the “T” and the “Z” and the seconds. Excel will recognize it as date-time. The user must remember the convention about time zones.

In download (JSON and XML) the full format is used YYYY-MM-DDThh:mmZ e.g. 2017-07-14T08:05Z.

Example 2017-07-14T08:05:00Z
Unit
Field Minutes5UTC
Property Contstraint
Type timestamptz
Size 20
Format Regex
Validation Rules

5 minutes DK

Name 5 minutes DK
Description

A date and time (interval), shown in Danish time zone, where the values are valid. 00:00:00 o’clock is the first 5 minutes of a given day, interval 00:00:00 - 00:04:59, and 00:05:00 covers the second 5 minutes period (interval) of the day and so forth.

Comment

On one normal day there will be 24 * 12 = 288 intervals.

When daylight saving times shifts there will be either 276 or 300 intervals.

Please note that the format shown in the example applies to data download as JSON, XML or fetched through the API and is in accordance with the ISO 8601 standard. The format is slightly different when it is shown on screen or downloaded manually as CSV or XLSX. This is mainly due to readability and consideration for Excel users.

In preview (in the GUI) all timestamps are shown as (display convention) YYYY-MM-DD hh:mm e.g. 2017-07-14 08:00. Please note that is no time zone indicator, showning that this is local (Danish) time.

In download (CSV and XLSX) the date time are exported as YYYY-MM-DD hh:mm:ss e.g. 2017-07-14 08:00:00. That is without the “T” and the seconds. Excel will recognize it as date-time. The user must remember that this is local (Danish) time.

In download (JSON and XML) the format used is YYYY-MM-DDThh:mm:ss e.g. 2017-07-14T08:00:00.

Example 2012-10-01T02:15:00
Unit
Field Minutes5DK
Property Contstraint
Type timestamp
Size 19
Format Regex
Validation Rules

Price area

Name Price area
Description

DK1 is Jutland and Fyen and DK2 is Zealand and islands

Comment

DK1 and DK2 are the standard abbreviation for the two Danish price areas

Example DK1
Unit
Field PriceArea
Property Contstraint
Type text
Size 3
Format Regex DK1 | DK2
Validation Rules DK1 or DK2

CO2 Emission

Name CO2 Emission
Description

The estimated value for the emission in g/kWh for the relevant 5 minutes period.

Comment
Example 301
Unit g/kWh
Field CO2Emission
Property Contstraint
Type int
Size 4
Format Regex \d{4}
Validation Rules