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NEM Schema

P5MIN_PRICESENSITIVITIES

P5MIN_PRICESENSITIVITIES

Price Sensitivies for 5MinPD solution. New solution every 5 minutes. Current Scenarios defined in P5MIN_SCENARIODEMANDTRK/P5MIN_SCENARIODEMAND

Column Schema

INTERVAL_DATETIME

The unique identifier for the interval within this study

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

This column is mandatory, and a primary key.

Example: 2026/09/01 00:05:00

REGIONID

Region

For more information, see the dedicated documentation page.

The SQL type is VARCHAR2(20). This is actually a factor/enum, with values:

QLD1
VIC1
TAS1
NSW1
SA1
SNOWY1

This column is mandatory, and a primary key.

RUN_DATETIME

Definitive Run from which this solution derives

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

This column is mandatory, and a primary key.

Example: 2026/09/01 00:05:00

INTERVENTION

Whether an Intervention constraint was defined in this run

Warning

Unlike most tables with an INTERVENTION column, INTERVENTION is not a primary key of P5MIN_PRICESENSITIVITIES.

For more information, see the dedicated documentation page.

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is mandatory (but not a primary key).

Example: 0

INTERVENTION_ACTIVE

Flag to indicate if the sensitivity run contains an active intervention constraint: 0 = No, 1 = Yes

For more information, see the dedicated documentation page.

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 0

LASTCHANGED

Timestamp when this record was last modified

For more information, see the dedicated documentation page.

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

This column is not mandatory.

Example: 2026/09/01 00:01:29

RRP1

Regional Reference price for scenario 1

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04343, 0.00003, 90, 88.75296

RRP2

Regional Reference price for scenario 2

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04343, 0.00003, 43, 67.49593

RRP3

Regional Reference price for scenario 3

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04343, 0.00003, 90, 97.73002

RRP4

Regional Reference price for scenario 4

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.00003, 83.99

RRP5

Regional Reference price for scenario 5

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04343, 0.00003, 0, 79.05483

RRP6

Regional Reference price for scenario 6

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.00003, 52, 84.72588

RRP7

Regional Reference price for scenario 7

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.00003, 83.99

RRP8

Regional Reference price for scenario 8

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04255, 0.00003, -0.05261, 79.05483

RRP9

Regional Reference price for scenario 9

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.00003, 83.99

RRP10

Regional Reference price for scenario 10

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04343, 0.00003, 83.9901

RRP11

Regional Reference price for scenario 11

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04343, 0.00003, 43, 77.07695

RRP12

Regional Reference price for scenario 12

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04343, 0.00003, 90, 89.41077

RRP13

Regional Reference price for scenario 13

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.00003, 83.99

RRP14

Regional Reference price for scenario 14

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.04335, 0.00003, -0.05278, 83.99

RRP15

Regional Reference price for scenario 15

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.00003, 83.99

RRP16

Regional Reference price for scenario 16

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP17

Regional Reference price for scenario 17

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP18

Regional Reference price for scenario 18

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP19

Regional Reference price for scenario 19

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP20

Regional Reference price for scenario 20

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP21

Regional Reference price for scenario 21

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP22

Regional Reference price for scenario 22

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP23

Regional Reference price for scenario 23

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP24

Regional Reference price for scenario 24

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP25

Regional Reference price for scenario 25

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP26

Regional Reference price for scenario 26

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP27

Regional Reference price for scenario 27

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP28

Regional Reference price for scenario 28

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP29

Regional Reference price for scenario 29

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP30

Regional Reference price for scenario 30

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP31

Regional Reference price for scenario 31

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP32

Regional Reference price for scenario 32

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP33

Regional Reference price for scenario 33

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP34

Regional Reference price for scenario 34

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP35

Regional Reference price for scenario 35

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP36

Regional Reference price for scenario 36

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP37

Regional Reference price for scenario 37

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP38

Regional Reference price for scenario 38

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP39

Regional Reference price for scenario 39

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP40

Regional Reference price for scenario 40

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP41

Regional Reference price for scenario 41

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP42

Regional Reference price for scenario 42

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

RRP43

Regional Reference price for scenario 43

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: 0

New Data Timing

Every 5 minutes

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("INTERVAL_DATETIME", "RUN_DATETIME", "LASTCHANGED").str.strptime(
            pl.Datetime, dt_s_fmt
        ),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"INTERVENTION": pl.UInt8, "INTERVENTION_ACTIVE": pl.UInt8})
    .cast(
        {
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "INTERVENTION": pl.Boolean,
            "INTERVENTION_ACTIVE": pl.Boolean,
            "RRP1": pl.Float64,
            "RRP2": pl.Float64,
            "RRP3": pl.Float64,
            "RRP4": pl.Float64,
            "RRP5": pl.Float64,
            "RRP6": pl.Float64,
            "RRP7": pl.Float64,
            "RRP8": pl.Float64,
            "RRP9": pl.Float64,
            "RRP10": pl.Float64,
            "RRP11": pl.Float64,
            "RRP12": pl.Float64,
            "RRP13": pl.Float64,
            "RRP14": pl.Float64,
            "RRP15": pl.Float64,
            "RRP16": pl.Float64,
            "RRP17": pl.Float64,
            "RRP18": pl.Float64,
            "RRP19": pl.Float64,
            "RRP20": pl.Float64,
            "RRP21": pl.Float64,
            "RRP22": pl.Float64,
            "RRP23": pl.Float64,
            "RRP24": pl.Float64,
            "RRP25": pl.Float64,
            "RRP26": pl.Float64,
            "RRP27": pl.Float64,
            "RRP28": pl.Float64,
            "RRP29": pl.Float64,
            "RRP30": pl.Float64,
            "RRP31": pl.Float64,
            "RRP32": pl.Float64,
            "RRP33": pl.Float64,
            "RRP34": pl.Float64,
            "RRP35": pl.Float64,
            "RRP36": pl.Float64,
            "RRP37": pl.Float64,
            "RRP38": pl.Float64,
            "RRP39": pl.Float64,
            "RRP40": pl.Float64,
            "RRP41": pl.Float64,
            "RRP42": pl.Float64,
            "RRP43": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['INTERVAL_DATETIME', 'REGIONID', 'RUN_DATETIME']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(subset=["INTERVAL_DATETIME", "REGIONID", "RUN_DATETIME"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_P5MIN_PRICESENSITIVITIES_FILE01_202609010000.zip

Table without MetadataTable with MetadataRaw Text without Metadata

RUN_DATETIME	REGIONID	INTERVAL_DATETIME	INTERVENTION	INTERVENTION_ACTIVE	RRP1	RRP2	RRP3	RRP4	RRP5	RRP6	RRP7	RRP8	RRP9	RRP10	RRP11	RRP12	RRP13	RRP14	RRP15	RRP16	RRP17	RRP18	RRP19	RRP20	RRP21	RRP22	RRP23	RRP24	RRP25	RRP26	RRP27	RRP28	RRP29	RRP30	RRP31	RRP32	RRP33	RRP34	RRP35	RRP36	RRP37	RRP38	RRP39	RRP40	RRP41	RRP42	RRP43	LASTCHANGED
2026/09/01 00:05:00	NSW1	2026/09/01 00:05:00	0	0	75.9601	63.05888	94.70142	65.51	65.02988	65.51	65.51	64.95006	65.51	72.2763	64.95	83.34	65.51	64.95006	65.51	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:10:00	0	0	83.99	65.51	90	68.12955	67.2473	75.9601	68.12955	67.67467	75.9601	77.07697	67.67467	83.99	67.69935	67.69935	68.12955	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:15:00	0	0	79.05486	65.51	83.99	67.69935	66.82258	68.58988	67.69935	67.27182	67.69935	76.59015	67.2473	83.99	67.27182	67.27182	67.52055	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:20:00	0	0	78.55573	65.51	83.99	67.69935	66.84695	68.80637	67.52055	67.27182	67.69935	75.9601	67.2473	83.30506	67.27182	67.27182	67.27182	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:25:00	0	0	78.5557	65.51	83.99	67.2473	66.40049	67.69935	66.82258	66.82258	67.2473	66.42471	66.82258	75.9601	66.82258	66.82258	66.82258	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:30:00	0	0	68.56246	65.51	83.99	66.82258	65.981	67.2473	66.40049	66.40049	66.82258	66.42471	66.40049	75.62555	66.40049	66.40049	66.40049	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:35:00	0	0	79.05483	65.51	83.99	75.9601	66.84695	75.9601	75.9601	67.27182	76.92557	75.9601	67.24735	78.48428	75.9601	75.9601	75.9601	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:40:00	0	0	79.05483	65.51	83.99	67.69935	66.84695	68.12955	67.69935	67.27182	68.12955	75.9601	67.2473	75.9601	67.52055	67.27182	67.69935	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:45:00	0	0	68.9981	65.51	83.99	67.27182	66.40049	67.67467	67.27182	66.82258	67.69935	66.84695	66.82258	75.62555	67.27182	66.82258	67.27182	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:50:00	0	0	75.9601	65.51	83.99	66.84695	66.40049	67.27182	66.84695	66.42471	67.27182	66.42471	66.40049	75.9601	66.49326	66.42471	66.84695	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
2026/09/01 00:05:00	NSW1	2026/09/01 00:55:00	0	0	68.10472	64.95	80.06256	66.40044	65.51	66.82253	65.90679	65.51	66.82253	65.98095	65.51	66.00506	65.51	65.51	65.51	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
...

C	SETP.WORLD	DVD_P5MIN_PRICESENSITIVITIES	AEMO	PUBLIC	2026/10/09	16:19:39	001791526779735	MONTHLY_ARCHIVE	001791526779735
I	P5MIN	PRICESENSITIVITIES	1	RUN_DATETIME	REGIONID	INTERVAL_DATETIME	INTERVENTION	INTERVENTION_ACTIVE	RRP1	RRP2	RRP3	RRP4	RRP5	RRP6	RRP7	RRP8	RRP9	RRP10	RRP11	RRP12	RRP13	RRP14	RRP15	RRP16	RRP17	RRP18	RRP19	RRP20	RRP21	RRP22	RRP23	RRP24	RRP25	RRP26	RRP27	RRP28	RRP29	RRP30	RRP31	RRP32	RRP33	RRP34	RRP35	RRP36	RRP37	RRP38	RRP39	RRP40	RRP41	RRP42	RRP43	LASTCHANGED
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:05:00	0	0	75.9601	63.05888	94.70142	65.51	65.02988	65.51	65.51	64.95006	65.51	72.2763	64.95	83.34	65.51	64.95006	65.51	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:10:00	0	0	83.99	65.51	90	68.12955	67.2473	75.9601	68.12955	67.67467	75.9601	77.07697	67.67467	83.99	67.69935	67.69935	68.12955	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:15:00	0	0	79.05486	65.51	83.99	67.69935	66.82258	68.58988	67.69935	67.27182	67.69935	76.59015	67.2473	83.99	67.27182	67.27182	67.52055	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:20:00	0	0	78.55573	65.51	83.99	67.69935	66.84695	68.80637	67.52055	67.27182	67.69935	75.9601	67.2473	83.30506	67.27182	67.27182	67.27182	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:25:00	0	0	78.5557	65.51	83.99	67.2473	66.40049	67.69935	66.82258	66.82258	67.2473	66.42471	66.82258	75.9601	66.82258	66.82258	66.82258	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:30:00	0	0	68.56246	65.51	83.99	66.82258	65.981	67.2473	66.40049	66.40049	66.82258	66.42471	66.40049	75.62555	66.40049	66.40049	66.40049	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:35:00	0	0	79.05483	65.51	83.99	75.9601	66.84695	75.9601	75.9601	67.27182	76.92557	75.9601	67.24735	78.48428	75.9601	75.9601	75.9601	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:40:00	0	0	79.05483	65.51	83.99	67.69935	66.84695	68.12955	67.69935	67.27182	68.12955	75.9601	67.2473	75.9601	67.52055	67.27182	67.69935	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:45:00	0	0	68.9981	65.51	83.99	67.27182	66.40049	67.67467	67.27182	66.82258	67.69935	66.84695	66.82258	75.62555	67.27182	66.82258	67.27182	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:50:00	0	0	75.9601	65.51	83.99	66.84695	66.40049	67.27182	66.84695	66.42471	67.27182	66.42471	66.40049	75.9601	66.49326	66.42471	66.84695	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
D	P5MIN	PRICESENSITIVITIES	1	2026/09/01 00:05:00	NSW1	2026/09/01 00:55:00	0	0	68.10472	64.95	80.06256	66.40044	65.51	66.82253	65.90679	65.51	66.82253	65.98095	65.51	66.00506	65.51	65.51	65.51	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2026/09/01 00:01:29
...
C	END OF REPORT	1003

RUN_DATETIME,REGIONID,INTERVAL_DATETIME,INTERVENTION,INTERVENTION_ACTIVE,RRP1,RRP2,RRP3,RRP4,RRP5,RRP6,RRP7,RRP8,RRP9,RRP10,RRP11,RRP12,RRP13,RRP14,RRP15,RRP16,RRP17,RRP18,RRP19,RRP20,RRP21,RRP22,RRP23,RRP24,RRP25,RRP26,RRP27,RRP28,RRP29,RRP30,RRP31,RRP32,RRP33,RRP34,RRP35,RRP36,RRP37,RRP38,RRP39,RRP40,RRP41,RRP42,RRP43,LASTCHANGED
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:05:00",0,0,75.9601,63.05888,94.70142,65.51,65.02988,65.51,65.51,64.95006,65.51,72.2763,64.95,83.34,65.51,64.95006,65.51,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:10:00",0,0,83.99,65.51,90,68.12955,67.2473,75.9601,68.12955,67.67467,75.9601,77.07697,67.67467,83.99,67.69935,67.69935,68.12955,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:15:00",0,0,79.05486,65.51,83.99,67.69935,66.82258,68.58988,67.69935,67.27182,67.69935,76.59015,67.2473,83.99,67.27182,67.27182,67.52055,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:20:00",0,0,78.55573,65.51,83.99,67.69935,66.84695,68.80637,67.52055,67.27182,67.69935,75.9601,67.2473,83.30506,67.27182,67.27182,67.27182,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:25:00",0,0,78.5557,65.51,83.99,67.2473,66.40049,67.69935,66.82258,66.82258,67.2473,66.42471,66.82258,75.9601,66.82258,66.82258,66.82258,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:30:00",0,0,68.56246,65.51,83.99,66.82258,65.981,67.2473,66.40049,66.40049,66.82258,66.42471,66.40049,75.62555,66.40049,66.40049,66.40049,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:35:00",0,0,79.05483,65.51,83.99,75.9601,66.84695,75.9601,75.9601,67.27182,76.92557,75.9601,67.24735,78.48428,75.9601,75.9601,75.9601,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:40:00",0,0,79.05483,65.51,83.99,67.69935,66.84695,68.12955,67.69935,67.27182,68.12955,75.9601,67.2473,75.9601,67.52055,67.27182,67.69935,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:45:00",0,0,68.9981,65.51,83.99,67.27182,66.40049,67.67467,67.27182,66.82258,67.69935,66.84695,66.82258,75.62555,67.27182,66.82258,67.27182,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:50:00",0,0,75.9601,65.51,83.99,66.84695,66.40049,67.27182,66.84695,66.42471,67.27182,66.42471,66.40049,75.9601,66.49326,66.42471,66.84695,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
"2026/09/01 00:05:00",NSW1,"2026/09/01 00:55:00",0,0,68.10472,64.95,80.06256,66.40044,65.51,66.82253,65.90679,65.51,66.82253,65.98095,65.51,66.00506,65.51,65.51,65.51,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
...

Raw Text with Metadata

C,SETP.WORLD,DVD_P5MIN_PRICESENSITIVITIES,AEMO,PUBLIC,2026/10/09,16:19:39,001791526779735,MONTHLY_ARCHIVE,001791526779735
I,P5MIN,PRICESENSITIVITIES,1,RUN_DATETIME,REGIONID,INTERVAL_DATETIME,INTERVENTION,INTERVENTION_ACTIVE,RRP1,RRP2,RRP3,RRP4,RRP5,RRP6,RRP7,RRP8,RRP9,RRP10,RRP11,RRP12,RRP13,RRP14,RRP15,RRP16,RRP17,RRP18,RRP19,RRP20,RRP21,RRP22,RRP23,RRP24,RRP25,RRP26,RRP27,RRP28,RRP29,RRP30,RRP31,RRP32,RRP33,RRP34,RRP35,RRP36,RRP37,RRP38,RRP39,RRP40,RRP41,RRP42,RRP43,LASTCHANGED
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:05:00",0,0,75.9601,63.05888,94.70142,65.51,65.02988,65.51,65.51,64.95006,65.51,72.2763,64.95,83.34,65.51,64.95006,65.51,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:10:00",0,0,83.99,65.51,90,68.12955,67.2473,75.9601,68.12955,67.67467,75.9601,77.07697,67.67467,83.99,67.69935,67.69935,68.12955,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:15:00",0,0,79.05486,65.51,83.99,67.69935,66.82258,68.58988,67.69935,67.27182,67.69935,76.59015,67.2473,83.99,67.27182,67.27182,67.52055,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:20:00",0,0,78.55573,65.51,83.99,67.69935,66.84695,68.80637,67.52055,67.27182,67.69935,75.9601,67.2473,83.30506,67.27182,67.27182,67.27182,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:25:00",0,0,78.5557,65.51,83.99,67.2473,66.40049,67.69935,66.82258,66.82258,67.2473,66.42471,66.82258,75.9601,66.82258,66.82258,66.82258,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:30:00",0,0,68.56246,65.51,83.99,66.82258,65.981,67.2473,66.40049,66.40049,66.82258,66.42471,66.40049,75.62555,66.40049,66.40049,66.40049,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:35:00",0,0,79.05483,65.51,83.99,75.9601,66.84695,75.9601,75.9601,67.27182,76.92557,75.9601,67.24735,78.48428,75.9601,75.9601,75.9601,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:40:00",0,0,79.05483,65.51,83.99,67.69935,66.84695,68.12955,67.69935,67.27182,68.12955,75.9601,67.2473,75.9601,67.52055,67.27182,67.69935,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:45:00",0,0,68.9981,65.51,83.99,67.27182,66.40049,67.67467,67.27182,66.82258,67.69935,66.84695,66.82258,75.62555,67.27182,66.82258,67.27182,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:50:00",0,0,75.9601,65.51,83.99,66.84695,66.40049,67.27182,66.84695,66.42471,67.27182,66.42471,66.40049,75.9601,66.49326,66.42471,66.84695,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
D,P5MIN,PRICESENSITIVITIES,1,"2026/09/01 00:05:00",NSW1,"2026/09/01 00:55:00",0,0,68.10472,64.95,80.06256,66.40044,65.51,66.82253,65.90679,65.51,66.82253,65.98095,65.51,66.00506,65.51,65.51,65.51,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,"2026/09/01 00:01:29"
...
C,"END OF REPORT",1003

Availability

Visibility: Public

This table is in the public monthly MMSDM archive.

I have collated the list of all those files into one place, in this CSV metadata file. (Columns year, month, url, compressed_size in bytes).

The earliest available data is month 8 of 2024. The most recent available data is month 9 of 2026.

Every month in between has a file. (No gaps.)

Data Size

Each year of data is approximately 219 MB when zipped, 2 GB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

INTERVAL_DATETIME
REGIONID
RUN_DATETIME

The transaction type is "insert", which means that you will usually not see duplicate data. If you do, you can deduplicate based on the primary keys, without sorting first. Rows from different files with the same primary keys should have the same values.

PDR Loader configuration is:

Report Name	Report Subtype	Version
P5MIN	PRICESENSITIVITIES	1

This means that the CSV files start with metadata columns:

I,P5MIN,PRICESENSITIVITIES,1,...
D,P5MIN,PRICESENSITIVITIES,1,...

Links

This page as JSON (schema documented here, but may change)

Download a JSON Schema specification for this table.

Official AEMO schema documentation

Other Information

Package: P5MIN