au.com.nempulse/nempulse

Tools

• get_battery_detail

  Deep-dive metrics for one battery by DUID (e.g. HPR1 = Hornsdale): revenue, dispatch, SOC, FCAS. WARNING: rev_today, energy_rev_today, fcas_rev_today and contingency_fcas_rev_today are MONTH-TO-DATE by default, not daily (matching the rev_mtd keys in fcas_breakdown) — do not report them as 'today's revenue'. throughput_cycles, throughput_mwh, avg_dispatch_price, avg_charge_price and efficiency_pct cover the same window. Pass date_from and date_to (both required together) to scope this window explicitly, e.g. to a single day, instead of relying on the month-to-date default. For a true daily time series use get_battery_revenue. Also returns commercial_context (e.g. TOLLED, CONTRACTED) and commercial_note — ALWAYS check commercial_context before comparing this unit's revenue against another unit's: tolled/contracted units do not trade merchant and their spot figures are not comparable.

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• get_battery_optimal

  Actual vs LP-optimal dispatch revenue, per-DUID summary, over a date range (energy-only, perfect-foresight benchmark). NOT a revenue-total source — use get_battery_revenue for that. Both the 'actual' AND the 'optimal' figures here are MLF-adjusted (get_battery_revenue's is gross) — the LP's objective is solved on MLF-adjusted prices, not just settled at them afterward — and both cover solved LP days only (days where the solver failed are dropped from both), so the two tools' totals will not match even for the same DUID and date range. The requested date_to may also be silently truncated to the latest date with sufficient fleet-wide LP coverage. Pass duid to restrict to one battery — omitting it scans every DUID and can time out even on a ~3-week range; even a single-DUID, single-month scan has been observed to time out, so keep date ranges short and retry narrower on a timeout.

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• get_battery_revenue

  Daily gross-spot revenue by market (energy + FCAS) for one battery (DUID) over a date range. Daily grain only. This is the tool for total revenue questions — use get_battery_optimal only for the actual-vs-perfect-foresight benchmark, not as a revenue source (its 'actual' figure is MLF-adjusted and solved-days-only, so it will not match this tool's totals). Each day also carries energy_rev_mlf_adjusted (null if the LP backcast hasn't run for that day yet, not zero) alongside the gross energy_rev, so MLF-adjusted figures are available here too without switching tools.

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• get_event_detail

  Summary stats for one market price event by id (per-interval dispatch during the event is not exposed).

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• get_fleet_summary

  Fleet-wide snapshot: unit count, total capacity, revenue month-to-date, average spot price.

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• list_bess_units

  List every NEM-registered grid-scale battery (DUID, station, region, MW/MWh, MLF, coordinates, is_commissioning, commercial_context). rev_per_mw_yr is trailing 365-day energy + FCAS revenue (NOT FPP), gross (no MLF), divided by Max Cap MW, then annualised over the days the unit actually had dispatch data — not over a fixed 365-day denominator. This is a rough simulator guide, NOT a performance ranking. It is distorted for any unit with is_commissioning=true or commissioned within the last 365 days, because that span-annualisation extrapolates a few months of ramp-up behaviour out to a full year (scale-up factors of 1.5x-2.4x are live in the current data), which magnifies both weak and negative figures rather than diluting them — do NOT try to 'correct' it by rescaling to the unit's operating span, as that double-counts the annualisation. It is also inflated for small FCAS-primary units, and structurally biased against longer-duration units (shorter-duration units can concentrate power into the highest-price intervals). Do not use it to compare units, rank performance, or answer 'which battery earns most' — use get_battery_revenue over a matched window, or get_battery_optimal for capture. Before comparing any two units' revenue, check commercial_context on each — TOLLED/CONTRACTED units don't trade merchant and their spot revenue is not comparable. Null until the first background refresh completes.

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• list_events

  List NEM spot-price events (negative, elevated, spike, extreme), optionally filtered by region.

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• query_nem_data

  Ask a natural-language question about NEM BESS data; returns generated SQL, result rows and a plain-English explanation. Scope each question to roughly one region-month or less — aggregates spanning more (e.g. a full year by region, or per-day top-N across all regions) can exceed the 15s query timeout. For per-day top-N / bottom-N questions, phrase them so the generated SQL uses a window function (ROW_NUMBER/RANK) rather than a per-day correlated subquery — the latter has been observed to silently return all-null rows with no error. Only dispatch_prices, daily_revenue, optimal_dispatch, bess_price_profile and market_events are reachable here; the market_* cache tables (market_monthly, market_regression, market_corr_tracker, market_daily_price, market_daily_fleet) behind the market-analysis page live in a separate database and are NOT queryable through this tool — a question about them will be recomputed from dispatch_prices instead, which is slower and easy to phrase incorrectly.

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