CONTRACTUNITLOADING

CONTRACTUNITLOADING became unused when Ancillary Services Review was implemented in 2001. For more details, see Change Notice 126. CONTRACTUNITLOADING shows Unit Loading contract details used in the settlement and dispatch of this service.

Deprecation Warning

This table is in the HISTORICAL TABLES package, so is likely deprecated.

CONTRACTUNITLOADING is confidential to participants.

Source

CONTRACTUNITLOADING is not in Use - discontinued 30/09/2001; was updated only where there was a contract variation.

Column Schema

CONTRACTID

Contract Identifier

SQL Type: VARCHAR2(10) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

VERSIONNO

Contract Version No.

SQL Type: NUMBER(3,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

ACR

Available Control Range

SQL Type: NUMBER(10,2) Polars Type: pl.Float64

This column is not mandatory.

AUTHORISEDBY

User Name

SQL Type: VARCHAR2(15) Polars Type: str

This column is not mandatory.

AUTHORISEDDATE

Date Contract was authorised

Warning

Despite what the name suggests, this is a datetime, not a date.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2026/01/20 00:05:00

BS

Block Size of Unit

SQL Type: NUMBER(10,2) Polars Type: pl.Float64

This column is not mandatory.

CCPRICE

Compensation Cap

SQL Type: NUMBER(10,2) Polars Type: pl.Float64

This column is not mandatory.

DUID

Dispatchable Unit ID

Warning

This column may contain funny characters such as / (slash) or # (hash). This may break hive-style partitioning.

For more information, see the dedicated documentation page.

SQL Type: VARCHAR2(10) Polars Type: pl.Categorical

This column is not mandatory.

Example: W/HOE#2

ENDDATE

Termination Date of Contract

Warning

Despite what the name suggests, this is a datetime, not a date.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2026/01/20 00:05:00

EU

Estimated Power consumption of unit when enabled for RGUL

SQL Type: NUMBER(10,2) Polars Type: pl.Float64

This column is not mandatory.

LASTCHANGED

Last date and time record changed

For more information, see the dedicated documentation page.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2026/01/20 00:05:00

PARTICIPANTID

Unique participant identifier

For more information, see the dedicated documentation page.

SQL Type: VARCHAR2(10) Polars Type: pl.Categorical

This column is not mandatory.

PP

Estimated Price for supply

SQL Type: NUMBER(10,2) Polars Type: pl.Float64

This column is not mandatory.

RPRICE

Enabling Price

SQL Type: NUMBER(10,2) Polars Type: pl.Float64

This column is not mandatory.

STARTDATE

Starting Date of Contract

Warning

Despite what the name suggests, this is a datetime, not a date.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2026/01/20 00:05:00

SUPRICE

Usage Price

SQL Type: NUMBER(10,2) Polars Type: pl.Float64

This column is not mandatory.

Code Examples

Polars

Casting is enums, categoricals etc is not essential, but may speed up parsing. Swapping int for pl.UInt16, pl.Int32 would also speed up parsing. However some of the datatypes are inferred, so they may be wrong.

This code deduplicates for you. Deduplication is normally only required across multiple months.

This code assumes that all columns are present, which may not be true for older files.

import polars as pl
import polars.selectors as cs

# e.g. "2029/03/15 00:05:00"
dt_s_fmt = "%Y/%m/%d %H:%M:%S"

csv_paths = ["SOMEFILE.CSV", "OTHERFILE.CSV"]

lf = (
    pl.concat(
        [
            pl.scan_csv(
                csv_path,  # must be unzipped beforehand
                skip_rows=1,  # skip the header
                infer_schema=False,  # much faster
            )
            .filter(cs.by_index(0) == "D")  # drop the footer
            .select(~cs.by_index(range(4)))  # drop metadata columns
            for csv_path in csv_paths
        ],
        how="diagonal_relaxed",
    )
    .with_columns(
        pl.col("AUTHORISEDDATE", "ENDDATE", "LASTCHANGED", "STARTDATE").str.strptime(
            pl.Datetime, dt_s_fmt
        ),
    )
    .cast(
        {
            "CONTRACTID": pl.Categorical,
            "VERSIONNO": int,  # or pl.UInt16
            "ACR": pl.Float64,
            "AUTHORISEDBY": str,
            "BS": pl.Float64,
            "CCPRICE": pl.Float64,
            "DUID": pl.Categorical,
            "EU": pl.Float64,
            "PARTICIPANTID": pl.Categorical,
            "PP": pl.Float64,
            "RPRICE": pl.Float64,
            "SUPRICE": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['CONTRACTID', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["CONTRACTID", "VERSIONNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Availability

Visibility: Private

This table is not available in the public monthly MMSDM archive. Is is only available to registered market participants over FTP inside a VPN.

Deduplication and PDR Loader Configuration

The primary keys are:

CONTRACTID
VERSIONNO

PDR Loader configuration does not mention this table, so it is unclear how to choose which row to keep when there are multiple rows for a given set of primary keys.

You should probably take the row with the maximum LASTCHANGED.