Storage

This page covers how storage is modelled in the National Electricity Market (NEM) fundamentals model. Storage includes grid-scale batteries, pumped hydro and coordinated consumer energy resources (CER) such as household batteries.

Storage units

Each storage unit has a power capacity in megawatts (MW), a duration in hours, a round-trip efficiency and a set of bid prices. Its state of charge is tracked through time, so a unit can only discharge energy it has already stored.

An individual battery can reach full output within one settlement period, but the whole fleet rarely does so at once. The battery fleet’s ramp rate is therefore limited so that the fleet takes 10 minutes to reach full discharge.

Battery bidding

A battery has no fuel cost to anchor its bids, only the wear on its cells, so the model sets its bids against the coal and gas in the same state.

For each state and each day, the model sorts the bids of coal, gas and other thermal plant into price steps, cheapest first, and finds the step that would set the price at the day’s peak residual demand (the demand left after wind and solar). The battery fleet’s power is then split into three kinds of bid:

• Most of the fleet bids at the cost of cell wear: the forecast-year cost of replacing the cells, spread over the energy they discharge in their life. This capacity discharges whenever the price covers the wear cost and the energy it charged with.
• A small slice bids just below the coal and gas it can displace: up to two of the price steps beneath the price-setting step, taking a small share of each. The battery takes that plant’s place in the merit order without moving the price-setting step, so the peak price does not fall.
• The rest is held back for high prices: a ladder of bids above the price-setting step, never below the all-in cost of a new battery of the same duration. A further share of each battery, larger for shorter durations, bids near the market price cap.

These bids set how the battery fleet shapes forecast prices; the Dispatch Model then optimises an individual battery against those prices.

With bids just below coal and gas, batteries dispatch against thermal plant from the first forecast years. Battery spreads rise around the major coal closures and widen again through the 2040s as the last coal units leave. As the fleet grows and batteries set the price more often, lower spreads weaken the case for new batteries in the Capacity Expansion Model (CEM), which slows the buildout until an equilibrium is reached.

Pumped hydro

Pumped hydro has a round-trip efficiency of 75%, so charging 100 megawatt-hours (MWh) returns only 75 MWh and it must discharge at a price at least 33% above its charging price. Most of its capacity bids at a low fixed cycling cost based on public sources. Some is withheld for higher spreads.

Battery costs and lead times

Battery energy storage system (BESS) capex is set by Modo Energy’s own market intelligence, independent of Australian Energy Market Operator (AEMO) and Commonwealth Scientific and Industrial Research Organisation (CSIRO) cost benchmarks. The current cost curve (February 2026) covers 2-hour, 4-hour and 8-hour batteries, and the 12-hour cost is extrapolated from the 4-hour and 8-hour costs. The HIGH scenario applies the same 1.10x capex multiplier used for generation technologies.

The CEM builds batteries in 2-, 4-, 8- and 12-hour durations, all with a 3-year lead time. The lead time comes from AEMO’s Integrated System Plan (ISP) and covers development and approval before construction begins.

Near-term battery buildout

Near-term battery buildout follows a probabilistic view of which pipeline projects will be built, and when. Projects are grouped by status, and each group has its own delay probabilities and share of capacity that comes online, based on historical NEM project timelines and market expertise. Projects classified as “Discontinued” are excluded, and multi-stage developments are tracked stage by stage.

The table gives the delay assumptions for the central scenario, which represents the most realistic worldview. Each row shows the probability that a project in each status category reaches the given timeline outcome.