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P5MIN_FCAS_REQ_CONSTRAINT

The constraint level FCAS cost / price details for constraint FCAS processor runs. This enhanced output table format is established for the constraint FCAS processor release required for the Frequency Performance Payments (FPP) release. This enhanced output is hierarchical in nature, with the parent *_FCAS_REQ_RUN table holding the details about the triggering case run and time, and the child *_FCAS_REQ_CONSTRAINT table holding the constraint level details of FCAS costs / prices.

Column Schema

BIDTYPE

DUID offered type

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

  • ENERGY

  • LOWERREG

  • LOWER60SEC

  • RAISE5MIN

  • LOWER5MIN

  • LOWER6SEC

  • RAISE60SEC

  • RAISE6SEC

  • RAISEREG

  • RAISE1SEC

  • LOWER1SEC

This column is mandatory, and a primary key.

CONSTRAINTID

ConstraintID join to table GenConData

SQL Type: VARCHAR2(20) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

Examples:

  • D_I+BIP_ML2_L1
  • D_I+NIL_MG2_R1
  • D_Q+BIP_ML_L1
  • D_Q+BIP_ML_L6
  • D_T+NIL_BB_TG_R1
  • D_T+NIL_MG_R1
  • D_T+NIL_ML_L1
  • D_T+NIL_ML_RECL_L1
  • D_T+NIL_TL_L1_DS
  • D_T+NIL_WF_TG_R1

INTERVAL_DATETIME

The 5 minute interval date and time of the 5 minute predispatch interval that was processed by the constraint FCAS processor

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

This column is mandatory, and a primary key.

Example: 2026/09/16 11:25:00

REGIONID

Region identifier

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

The run date and time of the 5 minute predispatch case that triggers the constraint FCAS processor run

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

This column is mandatory, and a primary key.

Example: 2026/09/16 11:20:00

RUNNO

The 5 minute predispatch case run number that has triggers the constraint FCAS processor run

SQL Type: NUMBER(5) Polars Type: pl.UInt32

This column is mandatory, and a primary key.

Example: 1

ADJUSTED_COST

The adjusted cost of the constraint for this service, after the regulation/contingency split

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.2375, 0, 36.40833333

BASE_COST

The base cost of the constraint, before the regulation/contingency split

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.2375, 0, 36.40833333

CONSTRAINT_ENABLEMENT

MW enabled for this bid type within the constraint

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

This column is not mandatory.

Examples: 31.28, 0, 12, 285

LHS

Constraints summed LHS - aggregate LHS Solution values from the physical run from the P5MIN_CONSTRAINTSOLUTION table

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

This column is not mandatory.

Examples: -11.02678, 0.685, 0, 220

MARGINALVALUE

Shadow price of constraint from the P5MIN_CONSTRAINTSOLUTION table from the physical run.

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

This column is not mandatory.

Examples: 0.01, 0, 3.79

P_REGULATION

The adjusted marginal value of the constraint for FPP recovery (blank for constraints without REG terms)

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.01, 0, 3.79

REGION_BASE_COST

The regional payment allocated to the constraint for the interval pro- rated based on marginal value ratios over the binding constraints for that service in that region (this is an intermediate calculation to get to the base cost)

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.01, 0, 15.79166667

REGIONAL_ENABLEMENT

The dispatched MW for the bid type inside the region from the physical run of the P5MIN_REGIONSOLUTION table

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

This column is not mandatory.

Examples: 29.67, 0, 3, 190

RHS

Constraints RHS value used in the solution - may be either dynamic (calculated) or static from the physical run from the P5MIN_CONSTRAINTSOLUTION table

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

This column is not mandatory.

Examples: -8.12571, 5.49538, 0, 1390

RRP

Bid type prices for the region coming from the pricing run of the P5MIN_REGIONSOLUTION table

For more information, see the dedicated documentation page.

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

This column is not mandatory.

Examples: 0.01, 0, 3.8

New Data Timing

Public at the completion of a constraint FCAS processor run for a 5 minute predispatch run

Code Examples

Polars

This table is so large that you should explicitly enumerate and cast every column, which will speed things up and prevents some errors. Although some of the datatypes are inferred, so they may be wrong. In particular, UInt16 vs UInt8 vs Int16 etc. If you get errors, you can swap these for just int.

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").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "BIDTYPE": pl.Enum(
                [
                    "ENERGY",
                    "LOWERREG",
                    "LOWER60SEC",
                    "RAISE5MIN",
                    "LOWER5MIN",
                    "LOWER6SEC",
                    "RAISE60SEC",
                    "RAISE6SEC",
                    "RAISEREG",
                    "RAISE1SEC",
                    "LOWER1SEC",
                ]
            ),
            "CONSTRAINTID": pl.Categorical,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "RUNNO": pl.UInt32,
            "ADJUSTED_COST": pl.Float64,
            "BASE_COST": pl.Float64,
            "CONSTRAINT_ENABLEMENT": pl.Float64,
            "LHS": pl.Float64,
            "MARGINALVALUE": pl.Float64,
            "P_REGULATION": pl.Float64,
            "REGION_BASE_COST": pl.Float64,
            "REGIONAL_ENABLEMENT": pl.Float64,
            "RHS": pl.Float64,
            "RRP": pl.Float64,
        }
    )
    # Deduplicate
    # These files are so large that this step may cause your laptop to run out of memory.
    # We want one row per ['BIDTYPE', 'CONSTRAINTID', 'INTERVAL_DATETIME', 'REGIONID', 'RUN_DATETIME', 'RUNNO']
    .unique(
        subset=[
            "BIDTYPE",
            "CONSTRAINTID",
            "INTERVAL_DATETIME",
            "REGIONID",
            "RUN_DATETIME",
            "RUNNO",
        ],
        keep="any",
    )
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_P5MIN_FCAS_REQ_CONSTRAINT_FILE02_202609010000.zip

RUN_DATETIMERUNNOINTERVAL_DATETIMECONSTRAINTIDREGIONIDBIDTYPELHSRHSMARGINALVALUERRPREGIONAL_ENABLEMENTCONSTRAINT_ENABLEMENTREGION_BASE_COSTBASE_COSTADJUSTED_COSTP_REGULATION
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5SA1LOWER5MIN323.42046-43.0795400.0175328.420000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5SA1LOWERREG323.42046-43.0795401.07502100000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5VIC1LOWERREG323.42046-43.0795401.07582100000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5TAS1LOWER5MIN323.42046-43.0795400.010328.420000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5TAS1LOWERREG323.42046-43.0795401.79502100000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5VIC1LOWER5MIN323.42046-43.0795400.0194.42328.420000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6NSW1LOWER6SEC79.30098-287.1990200.0144294.30000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6QLD1LOWER6SEC79.30098-287.1990200.0162.3294.30000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6SA1LOWER6SEC79.30098-287.1990200.0175294.30000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6TAS1LOWER6SEC79.30098-287.1990200.010294.30000
2026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6VIC1LOWER6SEC79.30098-287.1990200.01113294.30000
...

CSETP.WORLDDVD_P5MIN_FCAS_REQ_CONSTRAINTAEMOPUBLIC2026/10/0918:31:07001791534667112MONTHLY_ARCHIVE001791534667112
IP5MINFCAS_REQ_CONSTRAINT1RUN_DATETIMERUNNOINTERVAL_DATETIMECONSTRAINTIDREGIONIDBIDTYPELHSRHSMARGINALVALUERRPREGIONAL_ENABLEMENTCONSTRAINT_ENABLEMENTREGION_BASE_COSTBASE_COSTADJUSTED_COSTP_REGULATION
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5SA1LOWER5MIN323.42046-43.0795400.0175328.420000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5SA1LOWERREG323.42046-43.0795401.07502100000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5VIC1LOWERREG323.42046-43.0795401.07582100000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5TAS1LOWER5MIN323.42046-43.0795400.010328.420000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5TAS1LOWERREG323.42046-43.0795401.79502100000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L5VIC1LOWER5MIN323.42046-43.0795400.0194.42328.420000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6NSW1LOWER6SEC79.30098-287.1990200.0144294.30000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6QLD1LOWER6SEC79.30098-287.1990200.0162.3294.30000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6SA1LOWER6SEC79.30098-287.1990200.0175294.30000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6TAS1LOWER6SEC79.30098-287.1990200.010294.30000
DP5MINFCAS_REQ_CONSTRAINT12026/09/16 11:20:0012026/09/16 12:15:00F_I+NIL_MREH_TL_L6VIC1LOWER6SEC79.30098-287.1990200.01113294.30000
...
CEND OF REPORT1003

RUN_DATETIME,RUNNO,INTERVAL_DATETIME,CONSTRAINTID,REGIONID,BIDTYPE,LHS,RHS,MARGINALVALUE,RRP,REGIONAL_ENABLEMENT,CONSTRAINT_ENABLEMENT,REGION_BASE_COST,BASE_COST,ADJUSTED_COST,P_REGULATION
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,SA1,LOWER5MIN,323.42046,-43.07954,0,0.01,75,328.42,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,SA1,LOWERREG,323.42046,-43.07954,0,1.07,50,210,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,VIC1,LOWERREG,323.42046,-43.07954,0,1.07,58,210,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,TAS1,LOWER5MIN,323.42046,-43.07954,0,0.01,0,328.42,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,TAS1,LOWERREG,323.42046,-43.07954,0,1.79,50,210,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,VIC1,LOWER5MIN,323.42046,-43.07954,0,0.01,94.42,328.42,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,NSW1,LOWER6SEC,79.30098,-287.19902,0,0.01,44,294.3,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,QLD1,LOWER6SEC,79.30098,-287.19902,0,0.01,62.3,294.3,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,SA1,LOWER6SEC,79.30098,-287.19902,0,0.01,75,294.3,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,TAS1,LOWER6SEC,79.30098,-287.19902,0,0.01,0,294.3,0,0,0,0
"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,VIC1,LOWER6SEC,79.30098,-287.19902,0,0.01,113,294.3,0,0,0,0
...

C,SETP.WORLD,DVD_P5MIN_FCAS_REQ_CONSTRAINT,AEMO,PUBLIC,2026/10/09,18:31:07,001791534667112,MONTHLY_ARCHIVE,001791534667112
I,P5MIN,FCAS_REQ_CONSTRAINT,1,RUN_DATETIME,RUNNO,INTERVAL_DATETIME,CONSTRAINTID,REGIONID,BIDTYPE,LHS,RHS,MARGINALVALUE,RRP,REGIONAL_ENABLEMENT,CONSTRAINT_ENABLEMENT,REGION_BASE_COST,BASE_COST,ADJUSTED_COST,P_REGULATION
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,SA1,LOWER5MIN,323.42046,-43.07954,0,0.01,75,328.42,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,SA1,LOWERREG,323.42046,-43.07954,0,1.07,50,210,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,VIC1,LOWERREG,323.42046,-43.07954,0,1.07,58,210,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,TAS1,LOWER5MIN,323.42046,-43.07954,0,0.01,0,328.42,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,TAS1,LOWERREG,323.42046,-43.07954,0,1.79,50,210,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L5,VIC1,LOWER5MIN,323.42046,-43.07954,0,0.01,94.42,328.42,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,NSW1,LOWER6SEC,79.30098,-287.19902,0,0.01,44,294.3,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,QLD1,LOWER6SEC,79.30098,-287.19902,0,0.01,62.3,294.3,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,SA1,LOWER6SEC,79.30098,-287.19902,0,0.01,75,294.3,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,TAS1,LOWER6SEC,79.30098,-287.19902,0,0.01,0,294.3,0,0,0,0
D,P5MIN,FCAS_REQ_CONSTRAINT,1,"2026/09/16 11:20:00",1,"2026/09/16 12:15:00",F_I+NIL_MREH_TL_L6,VIC1,LOWER6SEC,79.30098,-287.19902,0,0.01,113,294.3,0,0,0,0
...
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).

Tip

There are multiple files per month, because this is such a large table.

The earliest available data is month 12 of 2024. The most recent available data is month 9 of 2026.

Every month in between has at least one file.

Data Size

Each year of data is approximately 9 GB when zipped, 90 GB as unzipped CSV.

Tip

This table is large. Simply calling pd.read_csv() might fill up all the memory on your laptop. (As a rule of thumb, you need double the amount of memory as the size of the CSV.) You will need to think hard about memory optimisation. e.g. consider using Polars instead of Pandas, and selecting only the columns you care about.

Deduplication and PDR Loader Configuration

The primary keys are:

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 FCAS_REQ_CONSTRAINT 1

This means that the CSV files start with metadata columns:

I,P5MIN,FCAS_REQ_CONSTRAINT,1,...
D,P5MIN,FCAS_REQ_CONSTRAINT,1,...

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