CONNECTIONPOINTDETAILS

CONNECTIONPOINTDETAILS is obsolete, since it was never populated by Participants accessing AEMO's Oracle Interface. CONNECTIONPOINTDETAILS was designed to show relevant details for each connection point including the responsible party, loss factor and relevant MDAs.

Deprecation Warning

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

CONNECTIONPOINTDETAILS data is confidential to each participant included in details.

Source

CONNECTIONPOINTDETAILS updates periodically, such as for Transmission Loss Factor (TLF) changes

Column Schema

CONNECTIONPOINTID

Connection point identifier

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

This column is mandatory, and a primary key.

EFFECTIVEDATE

Effective date of record

Warning

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

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

This column is mandatory, and a primary key.

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

VERSIONNO

Version no of record for given effective date

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

This column is mandatory, and a primary key.

AGGREGATEDDATA

Aggregate flag.

SQL Type: VARCHAR2(1) Polars Type: pl.Boolean

This column is not mandatory.

AUTHORISEDBY

User authorising record

SQL Type: VARCHAR2(15) Polars Type: str

This column is not mandatory.

AUTHORISEDDATE

Date record 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

DISTRIBUTIONLOSSFACTOR

The distribution level loss factor for a distribution connection point

SQL Type: NUMBER(7,5) Polars Type: pl.Float64

This column is not mandatory.

FINRESPORGAN

Financially responsible organisation

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

INUSE

Status flag.

SQL Type: VARCHAR2(1) Polars Type: pl.Boolean

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

LNSP

Local Electricity Network Service Provider

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

LR

Local Retailer

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

MDA

Metering Data Agent for connection point.

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

METERDATAPROVIDER

The MDA providing meter data for this connection point

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

NATIONALMETERINSTALLID

National Meter Id

SQL Type: NUMBER(7,5) Polars Type: pl.Float64

This column is not mandatory.

NETWORKSERVICEPROVIDER

The Network Service Provider

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

REGIONID

Region Identifier

For more information, see the dedicated documentation page.

The SQL type is VARCHAR2(10). This is actually a factor/enum, with values:

QLD1
VIC1
TAS1
NSW1
SA1
SNOWY1

This column is not mandatory.

ROLR

Retailer of last resort.

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

RP

Responsible party.

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

TRANSMISSIONCPTID

Associated transmission connection point id for a distribution connection point

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

TRANSMISSIONLOSSFACTOR

The transmission level loss factor for this connection point

SQL Type: NUMBER(7,5) Polars Type: pl.Float64

This column is not mandatory.

VALID_TODATE

Date of validity.

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

New Data Timing

Periodically with changes to connection point details

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(
            "EFFECTIVEDATE", "AUTHORISEDDATE", "LASTCHANGED", "VALID_TODATE"
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"AGGREGATEDDATA": pl.UInt8, "INUSE": pl.UInt8})
    .cast(
        {
            "CONNECTIONPOINTID": pl.Categorical,
            "VERSIONNO": int,  # or pl.UInt16
            "AGGREGATEDDATA": pl.Boolean,
            "AUTHORISEDBY": str,
            "DISTRIBUTIONLOSSFACTOR": pl.Float64,
            "FINRESPORGAN": str,
            "INUSE": pl.Boolean,
            "LNSP": str,
            "LR": str,
            "MDA": str,
            "METERDATAPROVIDER": str,
            "NATIONALMETERINSTALLID": pl.Float64,
            "NETWORKSERVICEPROVIDER": str,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "ROLR": str,
            "RP": str,
            "TRANSMISSIONCPTID": str,
            "TRANSMISSIONLOSSFACTOR": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['CONNECTIONPOINTID', 'EFFECTIVEDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['METERDATAPROVIDER', 'NETWORKSERVICEPROVIDER', 'FINRESPORGAN']
    .sort(
        ["METERDATAPROVIDER", "NETWORKSERVICEPROVIDER", "FINRESPORGAN"],
        descending=False,
    )
    .unique(subset=["CONNECTIONPOINTID", "EFFECTIVEDATE", "VERSIONNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Availability

AEMO's documentation states that this table's visibility is "Public". However, it is not available in the public monthly MMSDM archive. AEMO probably call this public because it is available to all market participants over private FTP.

There is a chance that is is still public to non-participants. It may only be available for some months; or (rarely) it may be available in a non-standard location.

Deduplication and PDR Loader Configuration

The primary keys are:

CONNECTIONPOINTID
EFFECTIVEDATE
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.