aemo: Australian Energy Market Operator Data

Description

Tidy R access to AEMO's public data: wholesale electricity prices, demand, dispatch, interconnector flows, rooftop PV, bids, predispatch and PASA forecasts, FCAS markets, and gas markets across the NEM.

Main function families

• aemo_price(), aemo_demand(): workhorse price and demand.

• aemo_dispatch_units(), aemo_interconnector(), aemo_rooftop_pv(): dispatch and flow.

• aemo_bids(), aemo_predispatch(), aemo_pasa(): bids and forecasts.

• aemo_fcas(), aemo_gas(): ancillary services and gas.

• aemo_units(), aemo_regions(), aemo_interconnectors(): reference data.

• aemo_nemweb_ls(), aemo_nemweb_download(): low-level escape hatches for arbitrary NEMweb paths.

• aemo_cache_info(), aemo_clear_cache(), aemo_throttle(): configuration.

Data source

Data is published by AEMO at http://nemweb.com.au under the AEMO Copyright Permissions Notice https://www.aemo.com.au/privacy-and-legal-notices/copyright-permissions.

Author(s)

Maintainer: Charles Coverdale charlesfcoverdale@gmail.com

See Also

Useful links:

• https://github.com/charlescoverdale/aemo

• Report bugs at https://github.com/charlescoverdale/aemo/issues

Generator bid stack

Description

Returns BIDDAYOFFER_D (daily bid summary: 10 price bands, MaxAvail, fixed load, locked at 12:30 D-1), BIDPEROFFER_D (per-interval availability and rebids), or the two joined on ⁠(duid, settlementdate, bidtype)⁠.

Usage

aemo_bids(
  duid,
  start,
  end,
  resolution = c("day", "period", "joined"),
  allow_large = FALSE
)

Arguments

Details

Parent / child structure. BIDDAYOFFER_D carries the price bands (priceband1..priceband10), which are locked at 12:30 on the day ahead and cannot be rebid. BIDPEROFFER_D carries the per-interval availability bands (bandavail1..bandavail10), which can be rebid intraday. Serious bidding analysis (Goncalves & Menezes 2022 Energy Economics 113 106398; Nelson et al. 2024 AJARE 68(4)) needs both joined.

Size warning. BIDPEROFFER_D monthly archives are multi-gigabyte. By default aemo_bids() refuses spans longer than 30 days; pass allow_large = TRUE to override.

Upstream gap. AEMO has a documented gap in BIDPEROFFER_D between March 2021 and July 2024. Rows in that range may be missing.

Value

An aemo_tbl.

See Also

Other dispatch: aemo_constraints(), aemo_dispatch_units(), aemo_fcas_enablement(), aemo_gencon(), aemo_interconnector(), aemo_market_notices(), aemo_outages(), aemo_rooftop_pv(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  # Daily bid summary (price bands)
  b <- aemo_bids(duid = "BW01",
                  start = now - 86400, end = now)

  # Joined: price bands + per-interval volumes
  bj <- aemo_bids(duid = "BW01", start = now - 86400, end = now,
                   resolution = "joined")
})
options(op)

Inspect the local aemo cache

Description

Inspect the local aemo cache

Usage

aemo_cache_info()

Value

A list with dir, n_files, size_bytes, size_human, files.

See Also

Other configuration: aemo_clear_cache(), aemo_throttle()

Examples

op <- options(aemo.cache_dir = tempdir())
aemo_cache_info()
options(op)

Clear the aemo cache

Description

Clear the aemo cache

Usage

aemo_clear_cache()

Value

Invisibly returns NULL.

See Also

Other configuration: aemo_cache_info(), aemo_throttle()

Examples

op <- options(aemo.cache_dir = tempdir())
aemo_clear_cache()
options(op)

Binding transmission and system constraints

Description

Returns the DISPATCHCONSTRAINT table from NEMweb: one row per binding (or near-binding) constraint per 5-minute dispatch interval. Each row records the constraint ID, the left-hand side (LHS) and right-hand side (RHS) values, the marginal value (shadow price on the constraint in AUD/MWh), and the violation degree if any.

Usage

aemo_constraints(
  start,
  end,
  constraint_id = NULL,
  intervention = FALSE,
  min_marginal_value = 0.01
)

Arguments

Details

This is the table that answers the question "why was the RRP so high at 17:35?": the sum of marginal values across binding constraints at the Regional Reference Node equals the regional price component attributable to network limits.

Constraint equations and RHS terms (GENCONDATA, GENCONSETINVOKE) are published through MMSDM on a separate cadence and are not exposed directly by this function; use aemo_nemweb_download() on an MMSDM URL for those.

Value

An aemo_tbl with columns settlementdate, constraintid, rhs, marginalvalue, violationdegree, lhs, plus the intervention flag.

Source

AEMO NEMweb DISPATCHIS_Reports, DISPATCHCONSTRAINT table.

See Also

Other dispatch: aemo_bids(), aemo_dispatch_units(), aemo_fcas_enablement(), aemo_gencon(), aemo_interconnector(), aemo_market_notices(), aemo_outages(), aemo_rooftop_pv(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  c <- aemo_constraints(start = now - 3600, end = now)
  head(c)
})
options(op)

Regional electricity demand

Description

Returns 5-minute regional demand from DISPATCHREGIONSUM. Three demand measures are supported, aligned with AEMO's Demand Terms taxonomy:

Usage

aemo_demand(
  region,
  start,
  end,
  measure = c("operational", "operational_less_snsg", "native"),
  intervention = FALSE
)

Arguments

Details

• "operational" (default): TOTALDEMAND, the grid-measured demand met by scheduled and semi-scheduled generation plus net interchange. This is the quantity AEMO dispatches.

• "operational_less_snsg": TOTALDEMAND minus small non-scheduled generation (SS_SOLAR_UIGF + SS_WIND_UIGF where present).

• "native": TOTALDEMAND plus estimated rooftop PV generation. Closest to end-use consumption. If the rooftop PV component is not available in DISPATCHREGIONSUM the function warns and returns TOTALDEMAND; users should join with aemo_rooftop_pv() for a full native-demand estimate.

Timestamps are AEST (UTC+10, no DST).

Value

An aemo_tbl with columns settlementdate, regionid, demand_mw (the requested measure), plus the underlying DISPATCHREGIONSUM columns used in the derivation.

Source

AEMO NEMweb, AEMO Copyright Permissions Notice.

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  d <- aemo_demand("VIC1", now - 3600, now)
  head(d)
})
options(op)

Per-DUID dispatch output

Description

Returns 5-minute generator output for one or more DUIDs. Three measures are available:

Usage

aemo_dispatch_units(
  duid = NULL,
  start,
  end,
  measure = c("scada_mw", "target_mw", "both")
)

Arguments

Details

• "scada_mw" (default): actual metered output from DISPATCH_UNIT_SCADA (SCADAVALUE).

• "target_mw": dispatch target from DISPATCHLOAD (TOTALCLEARED). This is the MW AEMO asked the unit to produce at the end of the interval.

• "both": returns SCADAVALUE, INITIALMW (SCADA at the start of the interval) and TOTALCLEARED (target at the end) in a single row per DUID per interval. Use this for ramp-trajectory research: the ramp applied during the interval is the straight line from INITIALMW to TOTALCLEARED.

Timestamps are AEST (UTC+10, no DST).

Value

An aemo_tbl with columns settlementdate, duid, and the requested measure(s).

See Also

Other dispatch: aemo_bids(), aemo_constraints(), aemo_fcas_enablement(), aemo_gencon(), aemo_interconnector(), aemo_market_notices(), aemo_outages(), aemo_rooftop_pv(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  # SCADA actual
  d <- aemo_dispatch_units(duid = "BW01", start = now - 3600,
                            end = now)

  # Paired: INITIALMW, TOTALCLEARED, SCADAVALUE (ramp research)
  d_both <- aemo_dispatch_units(duid = "BW01",
                                 start = now - 3600, end = now,
                                 measure = "both")
})
options(op)

Distribution Loss Factors (DLF) by connection point

Description

Returns the Distribution Loss Factor for NEM connection points from the MMSDM LOSSFACTORMODEL table. DLFs measure the average energy loss on the distribution network between a connection point and the transmission network boundary; a DLF of 1.02 means the generator must produce 2% more energy than it delivers to the transmission system.

Usage

aemo_dlf(year = NULL, connection_point_id = NULL)

Arguments

Details

DLFs are published annually by AEMO (NER 3.6.3) and combined with MLFs in settlement to give the total loss factor (TLF = MLF x DLF) used in energy payments.

Value

An aemo_tbl with at minimum financial_year, connectionpointid, and dlf.

Source

AEMO MMSDM archive, LOSSFACTORMODEL table. AEMO Copyright Permissions Notice.

See Also

Other reference: aemo_interconnectors(), aemo_mlf(), aemo_participants(), aemo_price_caps(), aemo_regions(), aemo_settlement(), aemo_snapshot(), aemo_units()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  dlf <- aemo_dlf(year = "2024-25")
  head(dlf)
})
options(op)

Frequency control ancillary services (FCAS) prices

Description

Returns regional FCAS market prices across the eight contingency services plus the two regulation services. Ten services are live in the NEM since R1/L1 Very Fast commenced on 9 October 2023.

Usage

aemo_fcas(region, start, end, service = NULL, intervention = FALSE)

Arguments

Details

Thin wrapper over aemo_price(..., market = "fcas").

Value

An aemo_tbl with one row per interval and columns for each requested FCAS RRP (AUD/MW).

See Also

Other price: aemo_price()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  f <- aemo_fcas("NSW1", now - 3600, now)
  head(f)
})
options(op)

FCAS enablement volumes by generator unit

Description

Returns the MW enabled for each of the ten Frequency Control Ancillary Services (FCAS) per DUID per 5-minute dispatch interval from DISPATCHLOAD. This is the quantity side of the FCAS market: how much each unit was enabled (dispatched) to provide each service, as distinct from the price returned by aemo_fcas().

Usage

aemo_fcas_enablement(
  duid = NULL,
  start,
  end,
  service = NULL,
  intervention = FALSE
)

Arguments

Details

Ten services are active since 9 October 2023 when Very Fast (RAISE1SEC / LOWER1SEC) commenced. Before that date only eight services are present; the raise1secmw / lower1secmw columns will be NA for intervals before that date.

Value

An aemo_tbl with columns settlementdate, duid, and one column per FCAS service (raise1secmw, lower1secmw, raise6secmw, lower6secmw, raise60secmw, lower60secmw, raise5minmw, lower5minmw, raiseregmw, lowerregmw). Values are MW; zero means the unit was not enabled for that service.

Source

AEMO NEMweb DISPATCHIS_Reports, DISPATCHLOAD table.

See Also

Other dispatch: aemo_bids(), aemo_constraints(), aemo_dispatch_units(), aemo_gencon(), aemo_interconnector(), aemo_market_notices(), aemo_outages(), aemo_rooftop_pv(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  e <- aemo_fcas_enablement(start = now - 3600, end = now)
  head(e)
})
options(op)

Gas market data (STTM, DWGM)

Description

Returns Short Term Trading Market (STTM, Adelaide, Brisbane, Sydney hubs) or Declared Wholesale Gas Market (DWGM, Victoria) prices and volumes.

Usage

aemo_gas(market = c("sttm", "dwgm"), hub = NULL, start, end)

Arguments

Value

An aemo_tbl.

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  g <- aemo_gas(market = "sttm", hub = "sydney",
                 start = now - 7 * 86400, end = now)
  head(g)
})
options(op)

Generic constraint equations and RHS terms (GENCONDATA)

Description

Downloads the GENCONDATA table from the most recent MMSDM monthly archive. GENCONDATA contains the equation definitions for every generic constraint active in the NEM: the constraint ID, the type (equality/inequality), a description of what the constraint models (thermal limit, voltage stability, system strength, etc.), and the default RHS value.

Usage

aemo_gencon(constraint_id = NULL, type = NULL)

Arguments

Details

Pair this with aemo_constraints() to go from a binding dispatch interval to the underlying network equation. The workflow is: aemo_constraints() tells you which constraint bound and how hard (marginalvalue = shadow price); aemo_gencon() tells you what the constraint is (which elements and why the RHS was set at that level).

Value

An aemo_tbl with columns including genconid (constraint ID), constrainttype, description, genericconstraintrhs (default RHS value). Additional columns from GENCONDATA (effective dates, generic constraint equation weights) will be present when available.

Source

AEMO NEMweb MMSDM archive, GENCONDATA table. AEMO Copyright Permissions Notice.

See Also

aemo_constraints() for the real-time binding constraint shadow prices.

Other dispatch: aemo_bids(), aemo_constraints(), aemo_dispatch_units(), aemo_fcas_enablement(), aemo_interconnector(), aemo_market_notices(), aemo_outages(), aemo_rooftop_pv(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  # Find equations for the Heywood interconnector thermal limits
  g <- aemo_gencon(constraint_id = c("V::S_NIL_TBSE", "V::S_NIL_FCSPS"))
  head(g)
})
options(op)

NEM interconnector flows

Description

Returns MW flows, losses, and limits for one or more NEM interconnectors from DISPATCHINTERCONNECTORRES.

Usage

aemo_interconnector(flow = NULL, start, end, intervention = FALSE)

Arguments

Details

AEMO's METEREDMWFLOW is positive when power flows from REGIONFROM to REGIONTO. For per-interconnector direction conventions see aemo_interconnectors().

Value

An aemo_tbl.

See Also

Other dispatch: aemo_bids(), aemo_constraints(), aemo_dispatch_units(), aemo_fcas_enablement(), aemo_gencon(), aemo_market_notices(), aemo_outages(), aemo_rooftop_pv(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  i <- aemo_interconnector(flow = "V-SA",
                            start = now - 3600, end = now)
  head(i)
})
options(op)

NEM interconnectors

Description

Returns a static table of the seven NEM interconnectors. The seventh entry is Project EnergyConnect (PEC), whose Stage 1 was energised on 30 April 2025 with full ~800 MW capability expected mid-2026.

Usage

aemo_interconnectors()

Value

An aemo_tbl with columns interconnector_id, from_region, to_region, name, energised.

See Also

Other reference: aemo_dlf(), aemo_mlf(), aemo_participants(), aemo_price_caps(), aemo_regions(), aemo_settlement(), aemo_snapshot(), aemo_units()

Examples

aemo_interconnectors()

NEM market notices

Description

Returns the MARKETNOTICEDATA feed from MMSDM. Market notices are AEMO's free-text log of market-relevant events: Lack of Reserve (LOR1/2/3) declarations, Reliability and Emergency Reserve Trader (RERT) activations, market suspensions, market directions, unit withdrawals, system security events, administered price declarations, and operator advisories.

Usage

aemo_market_notices(start, end, notice_type = NULL, region = NULL)

Arguments

Details

Pair with aemo_constraints() and aemo_price() to sequence the causal chain of a price event. Rangarajan, Svec, Foley and Trück (2025, Energy Economics 141) use MARKETNOTICEDATA to order the intervention messages that mark entry to and exit from the June 2022 NEM suspension.

Value

An aemo_tbl with columns from MARKETNOTICEDATA: noticeid, effectivedate, typeid (notice category), originator, priority, reason (the notice text), externalreference, and where present regionid.

Source

AEMO NEMweb MMSDM archive, MARKETNOTICEDATA table. AEMO Copyright Permissions Notice.

See Also

Other dispatch: aemo_bids(), aemo_constraints(), aemo_dispatch_units(), aemo_fcas_enablement(), aemo_gencon(), aemo_interconnector(), aemo_outages(), aemo_rooftop_pv(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  # LOR declarations during the June 2022 NEM suspension
  n <- aemo_market_notices(
    start = "2022-06-13",
    end   = "2022-06-14",
    notice_type = "LOR"
  )
  head(n)
})
options(op)

Marginal Loss Factors (MLF) by DUID and financial year

Description

Returns the Marginal Loss Factor applicable to each DUID for the requested financial year(s). MLFs measure the incremental network loss at a connection point relative to the Regional Reference Node (RRN); a DUID with MLF = 0.97 receives 97% of the regional RRP per MWh generated.

Usage

aemo_mlf(year = NULL, duid = NULL)

Arguments

Details

MLFs are published annually by AEMO under NER 3.6.2 and are used in settlement calculations and in PPA revenue reconstruction. The function first attempts to download the TRANSMISSIONLOSSFACTOR table from the most recent MMSDM monthly archive; if that fails it returns a bundled static table covering FY 2020-21 to FY 2025-26 for ~20 well-known DUIDs.

Value

An aemo_tbl with columns financial_year, duid, connectionpointid, regionid, mlf. From a live MMSDM download additional columns (participantid, lastchanged) may also be present.

Source

AEMO MMSDM archive, TRANSMISSIONLOSSFACTOR table. AEMO Copyright Permissions Notice.

See Also

aemo_units() for the DUID registry, aemo_price() for regional RRPs.

Other reference: aemo_dlf(), aemo_interconnectors(), aemo_participants(), aemo_price_caps(), aemo_regions(), aemo_settlement(), aemo_snapshot(), aemo_units()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  mlf <- aemo_mlf(year = "2024-25")
  head(mlf)
})
options(op)

Download a NEMweb zipped CSV to the local cache

Description

Thin wrapper over the internal cache-aware downloader.

Usage

aemo_nemweb_download(url, cache = TRUE)

Arguments

Value

Path to the cached file.

See Also

Other low-level: aemo_nemweb_ls()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  files <- aemo_nemweb_ls("/Reports/Current/DispatchIS_Reports/")
  if (nrow(files) > 0) {
    f <- aemo_nemweb_download(files$url[1])
    file.exists(f)
  }
})
options(op)

List files in a NEMweb directory

Description

Returns a data frame of files in a NEMweb path, parsed from the Apache directory-listing HTML.

Usage

aemo_nemweb_ls(path)

Arguments

Value

A data frame with name, modified, size, url.

Source

AEMO NEMweb http://nemweb.com.au, published under the AEMO Copyright Permissions Notice.

See Also

Other low-level: aemo_nemweb_download()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  files <- aemo_nemweb_ls("/Reports/Current/DispatchIS_Reports/")
  head(files)
})
options(op)

Planned and forced network outages

Description

Returns the NETWORK_OUTAGEDETAIL table from MMSDM, which records every planned and forced outage on NEM transmission and distribution network elements. Outages are a primary driver of binding constraints and price spikes: when a line or transformer is out of service the network is more constrained, reducing the thermal limits that appear as RHS values in DISPATCHCONSTRAINT.

Usage

aemo_outages(start, end, element_id = NULL, outage_type = NULL, region = NULL)

Arguments

Details

Use case. Pair with aemo_constraints() to explain a price spike: aemo_outages() tells you which elements were off-service at the time; aemo_constraints() tells you which constraints bound; together they answer "why was SA spot price AUD 15,000 at 17:35?".

Value

An aemo_tbl with columns from NETWORK_OUTAGEDETAIL including outageid, starttime, endtime, substationid, equipmenttype, equipmentid, outagetype, regionid, and restarttimeunknown. Exact column set depends on the MMSDM version.

Source

AEMO NEMweb MMSDM archive, NETWORK_OUTAGEDETAIL table. AEMO Copyright Permissions Notice.

See Also

aemo_constraints() for the binding constraint shadow prices that these outages drive.

Other dispatch: aemo_bids(), aemo_constraints(), aemo_dispatch_units(), aemo_fcas_enablement(), aemo_gencon(), aemo_interconnector(), aemo_market_notices(), aemo_rooftop_pv(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  # Forced outages during a recent high-price period in SA
  o <- aemo_outages(
    start = "2024-03-01",
    end   = "2024-03-02",
    outage_type = "FORCED"
  )
  head(o)
})
options(op)

NEM market participants and their registered DUIDs

Description

Returns a mapping of NEM market participants (companies) to their registered Dispatchable Unit Identifiers (DUIDs), joined from the MMSDM PARTICIPANT and DUDETAILSUMMARY tables. Use this for corporate ownership analysis: rolling up generator output or bids from DUID-level data to the company level.

Usage

aemo_participants()

Value

An aemo_tbl with columns participantid, participantclassid (e.g. GENERATOR, LOAD, TRADER), name (company name), duid, stationid, regionid, dispatchtype, schedule_type. Rows are one per participant-DUID combination. If MMSDM is unreachable, returns an empty table with a warning.

Source

AEMO NEMweb MMSDM archive, PARTICIPANT and DUDETAILSUMMARY tables. AEMO Copyright Permissions Notice.

See Also

aemo_units() for DUID-level registry without participant mapping.

Other reference: aemo_dlf(), aemo_interconnectors(), aemo_mlf(), aemo_price_caps(), aemo_regions(), aemo_settlement(), aemo_snapshot(), aemo_units()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  pt <- aemo_participants()
  # DUIDs owned by AGL
  pt[grepl("AGL", pt$name, ignore.case = TRUE), ]
})
options(op)

Projected Assessment of System Adequacy (PASA)

Description

Returns short-term (STPASA, 1-7 day) or medium-term (MTPASA, 2-year) system adequacy projections.

Usage

aemo_pasa(
  horizon = c("short", "medium"),
  region = NULL,
  start = NULL,
  end = NULL
)

Arguments

Value

An aemo_tbl.

See Also

Other forecast: aemo_predispatch()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  p <- aemo_pasa(horizon = "short", region = "NSW1")
})
options(op)

Price and demand forecasts (P5MIN, PREDISPATCH)

Description

Returns AEMO's forecast prices and demand for a NEM region. Two horizons:

• "p5min": 5-minute-ahead forecast, 12 intervals ahead, published every 5 minutes.

• "predispatch": 40-hour-ahead predispatch at 30-minute resolution, published every 30 minutes.

Usage

aemo_predispatch(
  region,
  start,
  end,
  horizon = c("predispatch", "p5min"),
  run_datetime = NULL
)

Arguments

Details

The 7-day predispatch publication was retired when 5-minute settlement commenced; for longer horizons use aemo_pasa().

Vintages. PREDISPATCH and P5MIN forecasts are re-issued every 30 or 5 minutes respectively. Every vintage is archived by its RUN_DATETIME. By default (run_datetime = NULL) this function returns all vintages whose file timestamp falls in ⁠[start, end]⁠, i.e. all the forecasts issued during the window. The periodid / datetime columns on the returned rows give each forecast's target time.

For forecast-error research (comparing a forecast vintage against the realised dispatch) pass run_datetime to pin a specific vintage:

# The PREDISPATCH run issued at 15:00 on 1 June 2024 --
# 80 half-hour-ahead rows covering 15:30 out to 31:30 hours.
v <- aemo_predispatch("NSW1", start = "2024-06-01", end = "2024-06-02",
                      run_datetime = "2024-06-01 15:00")

This is the vintage-aware pattern used in Prakash (2023) NEMSEER (JOSS 8(92) 5883).

Value

An aemo_tbl.

See Also

Other forecast: aemo_pasa()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  p <- aemo_predispatch("NSW1", start = now - 3600, end = now)
  head(p)
})
options(op)

Wholesale electricity prices

Description

Returns 5-minute dispatch prices or 30-minute trading prices for a NEM region over a specified window. Filters intervention runs by default so the returned prices are the market clearing prices used in settlement.

Usage

aemo_price(
  region,
  start,
  end,
  interval = c("5min", "30min"),
  market = c("energy", "fcas"),
  intervention = FALSE
)

Arguments

Details

Timestamps are AEST (UTC+10, no daylight savings) to match AEMO's market clock. See the package-level documentation for the period-ending timestamp convention (a row stamped 00:05 is the 5-minute period ending at 00:05).

Intervention. DISPATCHPRICE contains both market pricing runs (INTERVENTION = 0) and physical / intervention runs (INTERVENTION = 1). The default filters to market runs. Pass intervention = TRUE to get both.

30-minute settlement and the 5MS transition. Before 1 October 2021 the NEM settled on 30-minute trading prices from TRADINGPRICE (TRADINGIS). On 1 October 2021 five-minute settlement (5MS) commenced and settlement moved to native 5-minute prices. When interval = "30min":

• For the pre-5MS period (start < 2021-10-01): prices are read from TRADINGIS (TRADINGPRICE).

• For the post-5MS period: prices are derived by taking the arithmetic mean of the six 5-minute dispatch prices within each 30-minute trading interval, consistent with how AEMO calculates the TRADINGPRICE column in TradingIS post-5MS.

Data availability. NEMweb Current-directory files retain the last ~30 days of 5-minute dispatch files. Historical queries use the Archive daily-rollup files automatically; for queries older than the Archive window, use aemo_nemweb_download() with an MMSDM URL directly.

Value

An aemo_tbl. Key columns include settlementdate (POSIXct AEST), regionid, rrp (AUD/MWh, energy) or the FCAS service RRPs (AUD/MW), and intervention.

Source

AEMO NEMweb http://nemweb.com.au, AEMO Copyright Permissions Notice.

See Also

Other price: aemo_fcas()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  p <- aemo_price("NSW1", now - 3600, now)
  head(p)
})
options(op)

NEM market price caps, price floor, and CPT by financial year

Description

Returns a static reference table of the Market Price Cap (MPC), Market Price Floor (MPF), Cumulative Price Threshold (CPT), and Administered Price Cap (APC) that apply in each NEM financial year (1 July to 30 June). These are set by the AEMC under NER 3.9.4 and indexed annually to CPI.

Usage

aemo_price_caps()

Details

Use this table to interpret spot-price extremes: any RRP hitting the MPC (typically AUD 15,000 to 17,500 per MWh depending on year) indicates a price cap event; when the rolling-seven-day cumulative price in a region exceeds the CPT (~AUD 1.5 million per MWh-equivalent), AEMO imposes the APC (AUD 300/MWh) until the CPT falls back below the threshold.

The table covers 2015-16 onwards and is updated on each package release. For the authoritative current values see https://www.aemc.gov.au/regulation/energy-rules/national-electricity-rules and the AEMO Reliability Settings publications.

Value

An aemo_tbl with columns year (financial year, "YYYY-YY"), market_price_cap_aud_per_mwh, market_price_floor_aud_per_mwh, cumulative_price_threshold_aud, administered_price_cap_aud_per_mwh, and source.

See Also

Other reference: aemo_dlf(), aemo_interconnectors(), aemo_mlf(), aemo_participants(), aemo_regions(), aemo_settlement(), aemo_snapshot(), aemo_units()

Examples

caps <- aemo_price_caps()
head(caps)

NEM regions

Description

Returns a static table of the five NEM regions with metadata. The market_timezone column is the AEMO market clock (AEST, UTC+10, no DST, year-round) that applies to every timestamp in NEMweb files; wall_timezone is the local civil time zone consumers experience (observes DST in NSW/VIC/TAS/SA).

Usage

aemo_regions()

Value

An aemo_tbl with columns region, name, state, wall_timezone, market_timezone, commenced.

See Also

Other reference: aemo_dlf(), aemo_interconnectors(), aemo_mlf(), aemo_participants(), aemo_price_caps(), aemo_settlement(), aemo_snapshot(), aemo_units()

Examples

aemo_regions()

Rooftop PV actuals and forecasts

Description

Returns AEMO's region-level estimate of rooftop PV generation, either actuals or forecasts. Published at 30-minute resolution.

Usage

aemo_rooftop_pv(region, start, end, type = c("actual", "forecast"))

Arguments

Details

The "actual" figure is an AEMO estimate derived from the APVI sampling model and weather data, not metered SCADA output. It is the best available public measure of aggregate rooftop PV generation but is subject to revision.

Value

An aemo_tbl.

See Also

Other dispatch: aemo_bids(), aemo_constraints(), aemo_dispatch_units(), aemo_fcas_enablement(), aemo_gencon(), aemo_interconnector(), aemo_market_notices(), aemo_outages(), aemo_spd_constraints()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  now <- Sys.time()
  r <- aemo_rooftop_pv("NSW1",
                        start = now - 3600, end = now)
  head(r)
})
options(op)

Settlement cash-flow and residue tables

Description

Returns settlement reconciliation tables from MMSDM. Three views are exposed, corresponding to the three tables gentailer hedging workflows most commonly need:

Usage

aemo_settlement(table = c("cashflow", "fcas_recovery", "residues"), start, end)

Arguments

Details

• "cashflow" (default): SETCFM (NEMDE-derived energy settlement amounts per participant per trading interval).

• "fcas_recovery": SETFCASREGIONRECOVERY (the recovery allocation of FCAS costs to customer load per region per trading interval).

• "residues": SETRESIDUECONTRACTPAYMENT (settlement residue auction (SRA) contract payments against interconnector settlement residues).

Access. These tables are in the MMSDM monthly archive (not the NEMweb Current retention). Expect two-month latency between trading date and availability.

Value

An aemo_tbl with the raw MMSDM columns for the requested table.

Source

AEMO NEMweb MMSDM archive, SETCFM / SETFCASREGIONRECOVERY / SETRESIDUECONTRACTPAYMENT. AEMO Copyright Permissions Notice.

See Also

aemo_mlf() for the transmission loss factors that scale settlement amounts; aemo_interconnector() for the flow side of the residue calculation.

Other reference: aemo_dlf(), aemo_interconnectors(), aemo_mlf(), aemo_participants(), aemo_price_caps(), aemo_regions(), aemo_snapshot(), aemo_units()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  s <- aemo_settlement(table = "cashflow",
                        start = "2024-06-01",
                        end   = "2024-06-02")
  head(s)
})
options(op)

Snapshot provenance for an aemo_tbl

Description

Returns a one-row-per-source provenance record for an aemo_tbl, suitable for inclusion in a paper appendix, a Zenodo deposit, or a CRAN-style data manifest. The snapshot captures:

Usage

aemo_snapshot(x)

Arguments

Details

• title: the human-readable title of the table;

• source: the NEMweb / MMSDM URL family the table was drawn from;

• licence: the AEMO Copyright Permissions Notice (always);

• retrieved: the POSIXct timestamp at which the table was constructed;

• rows, cols: observed dimensions;

• sha256: a SHA-256 digest of the table's printed body, stable across R versions and platforms.

The sha256 column is what makes the snapshot pinnable: if the same query returns a different hash, the underlying data has changed (or the row-order has, which is also worth knowing). Pair with a git commit of the analysis script to give a reader a closed reproducibility loop.

Value

A data frame with one row per table.

See Also

Other reference: aemo_dlf(), aemo_interconnectors(), aemo_mlf(), aemo_participants(), aemo_price_caps(), aemo_regions(), aemo_settlement(), aemo_units()

Examples

x <- structure(
  data.frame(settlementdate = Sys.time(), region = "NSW1", rrp = 80),
  aemo_title = "Demo",
  aemo_source = "http://nemweb.com.au",
  aemo_licence = "AEMO Copyright Permissions Notice",
  aemo_retrieved = Sys.time(),
  class = c("aemo_tbl", "data.frame")
)
aemo_snapshot(x)

SPD constraint tables (regions, interconnectors, connection points)

Description

Returns the SPD (Security and Projected Dispatch) constraint coefficient tables from MMSDM. Where GENCONDATA gives the high-level equation definition, the SPD tables give the per-term coefficients used in the NEMDE dispatch optimisation:

Usage

aemo_spd_constraints(
  table = c("region", "interconnector", "connection_point"),
  constraint_id = NULL
)

Arguments

Details

• "region": SPDREGIONCONSTRAINT (regional-demand and regional-generation terms).

• "interconnector": SPDINTERCONNECTORCONSTRAINT (interconnector-flow terms).

• "connection_point": SPDCONNECTIONPOINTCONSTRAINT (per-DUID connection-point terms).

These tables are required for NEM dispatch replication (the nempy Python package, Gorman, Bruce & MacGill 2022, JOSS 7(70) 3596, doi:10.21105/joss.03596, uses all three when reproducing NEMDE solves).

Value

An aemo_tbl with columns from the requested SPD table. GENCONID and FACTOR (the coefficient) are always present; other columns vary by table.

Source

AEMO NEMweb MMSDM archive, SPDREGIONCONSTRAINT / SPDINTERCONNECTORCONSTRAINT / SPDCONNECTIONPOINTCONSTRAINT.

See Also

aemo_gencon() for the equation-level metadata, aemo_constraints() for the 5-min binding-constraint feed with shadow prices.

Other dispatch: aemo_bids(), aemo_constraints(), aemo_dispatch_units(), aemo_fcas_enablement(), aemo_gencon(), aemo_interconnector(), aemo_market_notices(), aemo_outages(), aemo_rooftop_pv()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  s <- aemo_spd_constraints(table = "interconnector")
  head(s)
})
options(op)

Configure request throttling

Description

Controls the delay between successive NEMweb requests. Defaults to 1 second (half a request per second).

Usage

aemo_throttle(delay = 1)

Arguments

Value

Invisibly returns the previous value.

See Also

Other configuration: aemo_cache_info(), aemo_clear_cache()

Examples

old <- aemo_throttle(0.5)  # 2 requests per second
aemo_throttle(old)         # restore

NEM generators (DUID registry)

Description

Downloads the DUDETAILSUMMARY table from the most recent MMSDM monthly archive and returns one row per registered DUID (Dispatchable Unit Identifier) with station, region, dispatch type, classification, and schedule type. Typical output is 500+ DUIDs covering scheduled, semi-scheduled, and non-scheduled generators, bidirectional storage (BESS), and loads.

Usage

aemo_units(as_of = NULL)

Arguments

Details

Effective-date filtering. DUDETAILSUMMARY is effective-dated (START_DATE, END_DATE per row with multiple VERSIONNO vintages per DUID over time). The default (as_of = NULL) returns rows whose ⁠[START_DATE, END_DATE]⁠ interval covers the date the MMSDM archive was published: i.e. the current registry. Pass an as_of date to get the registry as it was on that date (essential for historical analysis: Liddell's four DUIDs were retired in April 2023; pre-2023 queries need them).

This matches the as-of-join pattern documented in Gorman et al. (2018) NEMOSIS (APSRC) for correct historical joins.

Value

An aemo_tbl keyed by duid. Columns include (from DUDETAILSUMMARY): duid, stationid, regionid, dispatchtype (GENERATOR / LOAD), connectionpointid, schedule_type (SCHEDULED / SEMI-SCHEDULED / NON-SCHEDULED), start_date, end_date.

Source

AEMO NEMweb MMSDM archive, DUDETAILSUMMARY table, AEMO Copyright Permissions Notice.

See Also

Other reference: aemo_dlf(), aemo_interconnectors(), aemo_mlf(), aemo_participants(), aemo_price_caps(), aemo_regions(), aemo_settlement(), aemo_snapshot()

Examples

op <- options(aemo.cache_dir = tempdir())
try({
  # Current DUID registry
  u <- aemo_units()

  # DUIDs as they were on 1 March 2023 (pre-Liddell retirement)
  u_2023 <- aemo_units(as_of = "2023-03-01")
})
options(op)

Print an aemo_tbl

Description

Print an aemo_tbl

Usage

## S3 method for class 'aemo_tbl'
print(x, ...)

Arguments

Value

Invisibly returns x.

Examples

x <- data.frame(settlementdate = Sys.time(), region = "NSW1", rrp = 80)
x <- structure(x, aemo_title = "Demo", aemo_source = "http://nemweb.com.au",
               aemo_licence = "AEMO Copyright Permissions Notice",
               aemo_retrieved = Sys.time(),
               class = c("aemo_tbl", "data.frame"))
print(x)