# NEM timestamps: AEST, period-ending, and the 5MS transition

## The NEM market clock

The National Electricity Market operates on Australian Eastern Standard Time (AEST), UTC+10, year-round. This is not the same as the wall-clock time in Sydney or Melbourne, which advance one hour to AEDT (UTC+11) during Daylight Saving Time (October to April each year).

The legal basis is NER clause 2.2.6. Using wall-clock time for any AEMO data analysis is a common error: every summer timestamp will be parsed one hour ahead of the file clock, and timestamps at the DST transition boundaries will become ambiguous or `NA`.

The `aemo` package uses `"Australia/Brisbane"` as the timezone for all data. Queensland observes AEST year-round (no DST), which gives the correct fixed UTC+10 offset:

    library(aemo)

    # All timestamps come back in AEST (UTC+10, no DST).
    # The tzone attribute is "Australia/Brisbane" throughout.
    p <- aemo_price("NSW1", "2024-01-15 14:00", "2024-01-15 15:00")
    attr(p$settlementdate, "tzone")  # "Australia/Brisbane"

    # January is summer in Australia. Australia/Sydney would give UTC+11 here,
    # shifting every timestamp one hour ahead of the AEMO file clock.
    # Australia/Brisbane correctly gives UTC+10.
    format(p$settlementdate[1], "%Y-%m-%d %H:%M:%S %Z")

To display times in local wall-clock time for a specific state, convert explicitly:

    # Convert market time to NSW wall clock (observes DST)
    p$local_time_nsw <- format(p$settlementdate, tz = "Australia/Sydney")

    # Convert market time to SA wall clock (UTC+9:30 / UTC+10:30 with DST)
    p$local_time_sa <- format(p$settlementdate, tz = "Australia/Adelaide")

## Period-ending timestamps

Every interval in a NEMweb file is labelled with its period-ending timestamp. A row with `settlementdate = "2024-01-15 14:05:00"` covers the 5-minute dispatch interval from 14:00:01 to 14:05:00 (inclusive).

This is the AEMO convention throughout: the timestamp marks when the interval closes, not when it opens. For 30-minute trading intervals the same rule applies: a row stamped `14:30:00` covers 14:00:01 to 14:30:00.

When computing time-of-day statistics (e.g. peak demand by hour) use the interval end-time directly. When joining to external time series that use period-start timestamps, subtract the interval length:

    # Period-start timestamps for 5-min intervals
    p$period_start <- p$settlementdate - as.difftime(5, units = "mins")

    # Period-start timestamps for 30-min trading intervals
    t$period_start <- t$settlementdate - as.difftime(30, units = "mins")

## The 5-minute settlement transition (1 October 2021)

Before 1 October 2021 the NEM settled electricity on 30-minute trading intervals using `TRADINGPRICE` from the TRADINGIS reports. On that date five-minute settlement (5MS) commenced under NER clause 3.15.1A, and settlement moved to native 5-minute dispatch prices from DISPATCHPRICE.

Practical implications:

Query | What `aemo_price()` returns
--- | ---
`interval = "5min"`, any date | Native 5-min dispatch price from DISPATCHPRICE (DISPATCHIS)
`interval = "30min"`, date before 2021-10-01 | 30-min TRADINGPRICE from TRADINGIS
`interval = "30min"`, date from 2021-10-01 | Arithmetic mean of six 5-min dispatch prices within the trading interval
`interval = "30min"`, spanning 2021-10-01 | Pre-5MS portion from TRADINGIS; post-5MS aggregated from 5-min

When constructing long historical 30-minute price series that span the transition, the aggregation method matches: both the pre-5MS TRADINGPRICE and the post-5MS arithmetic mean are simple unweighted averages of the six dispatch prices within the trading interval (pre-5MS dispatch prices were held constant at the trading-interval price; post-5MS they vary).

## Intervention runs

DISPATCHPRICE contains two types of dispatch runs in every file:

- INTERVENTION = 0: the market pricing run. This is the price used in settlement and the one most analyses want.
- INTERVENTION = 1: the physical/intervention run, published when AEMO has issued an intervention direction (e.g. the June 2022 market suspension). Both runs coexist in the same file.

All `aemo` data functions default to `intervention = FALSE`, which filters to market-pricing rows only. Pass `intervention = TRUE` when you need to analyse the intervention pricing itself (e.g. the cost of directions during a suspension period).

    # Default: market pricing run only
    p_market <- aemo_price("NSW1", "2022-06-13", "2022-06-14")

    # Both runs (for intervention analysis)
    p_both <- aemo_price("NSW1", "2022-06-13", "2022-06-14",
                         intervention = TRUE)
    table(p_both$intervention)