Why Australia needs locational pricing

Australia’s electricity market was not designed for the system we are now building. It was designed for a world of large generators, predictable flows, and relatively stable demand, where a handful of regional prices could reasonably approximate what was happening across the grid. That world is fading quickly. In its place is something far more dynamic: millions of rooftop systems, rapidly growing batteries, increasingly binding transmission constraints, and flows that shift not just seasonally, but hourly. The physical system has fundamentally changed, but the way we price it has not.

At the heart of the issue is a simple mismatch. Electricity is inherently local. It is produced at a specific point, consumed at another, and transported across a network that has limits. Those limits matter. When a line is congested, electricity cannot flow freely, and the value of energy on one side of that constraint diverges from the value on the other. Yet in the National Electricity Market, we compress all of that complexity into a single price per region. Five regions, one for each of the NEM states, five prices, and within each, a vast amount of hidden variability.

We do not eliminate those differences by averaging them. We simply push them out of sight. They reappear elsewhere, in the form of constraint costs, curtailment, volatile marginal loss factors, and increasingly blunt attempts to steer investment through administrative mechanisms. The chart below shows the increasing impact of network constraints in the National Electricity Market over time using AEMO's “binding constraint impact” as a proxy for congestion severity. When the grid cannot move electricity freely, the system has to intervene — redispatching generators, curtailing output, and managing flows manually. The underlying cost of those constraints has risen sharply, particularly during periods of system stress. We are not avoiding locational pricing. We are paying for it elsewhere.

Congestion isn’t new. What’s new is how fast it’s growing — and how little of it is reflected in price.

When a solar farm is curtailed because the network cannot carry its output, that is a price signal trying to exist without a price. When batteries cluster in locations that are convenient rather than optimal, that is a signal that never quite made it into the market. When transmission spending rises sharply in response to congestion that could have been partially solved with better siting and coordination, that too reflects the absence of clear locational incentives.

Other markets confronted this problem earlier. Their response was not to eliminate complexity, but to expose it in a usable form. Locational marginal pricing does exactly that. It separates the price of electricity into its underlying components: the cost of producing the next unit of energy, the cost of congestion on the network, and the cost of losses as power flows across distance. The result is not a single regional average, but a set of prices that vary across the grid, reflecting real conditions in real time.

The effect of this is not academic. It changes behaviour. Storage is drawn to locations where it can relieve congestion or arbitrage meaningful spreads. Generation is incentivised to locate where its output can actually be delivered. Demand response becomes more valuable where the system is tight, and less so where it is not. Congestion, instead of being an opaque operational issue, becomes visible and, crucially, hedgeable through financial instruments. In short, money begins to align more closely with physics.

That alignment matters way more now than it did in the past. Australia is entering a phase where the marginal value of coordination is rising quickly. We have already succeeded in deploying huge volumes of solar panels, and we are now accelerating into batteries, both grid-scale and behind the meter. The next challenge is not simply to add more capacity, but to orchestrate what we already have. A system with millions of distributed devices cannot be efficiently managed with coarse signals. It requires prices that carry information about where flexibility is needed, not just when.

None of this is to suggest that locational pricing is a trivial upgrade. It is not. The complexity is real, and so are the risks. Moving from regional pricing to a nodal system introduces basis risk between locations. It requires the development of robust hedging instruments such as financial transmission rights. It complicates contracting, increases the demands on participants, and raises legitimate concerns about transition costs and political acceptability. These are not minor considerations, and they explain why Australia has been cautious. Making any major changes to our NEM, which involves five states and three regulatory bodies, is notoriously difficult.

But it is important to be clear about the alternative. Retaining the current structure does not avoid these costs; it redistributes them. Instead of explicit congestion prices, we get implicit ones embedded in losses, curtailment, and system interventions. Instead of transparent signals for investment, we rely more heavily on planning frameworks and administrative overlays. Instead of aligning incentives directly, we attempt to approximate alignment through a growing set of rules and adjustments. The system does not become simpler. It becomes opaque.

There is also a question of timing. The case for locational pricing strengthens as the system becomes more constrained and more distributed. Transmission bottlenecks are binding more frequently. Storage is scaling rapidly. Distributed energy resources are no longer peripheral; they are becoming central to how the grid operates. In that context, the cost of imprecise signals rises. What might once have been a tolerable simplification begins to look like a structural limitation.

This does not mean the path forward must be binary. Full nodal pricing is one option, but it is not the only one. There are intermediate steps: increasing the number of zones, publishing shadow nodal prices to expose underlying conditions, improving congestion metrics, or enabling more granular sub-regional signals through market or overlay mechanisms. Each of these can move the system closer to reflecting physical reality without requiring an immediate, wholesale redesign. They also create a pathway for participants to adapt gradually, rather than abruptly.

What matters is the direction of travel. The grid is becoming more local in its constraints and more distributed in its resources. Pricing that remains coarse in the face of that evolution will increasingly struggle to coordinate outcomes efficiently. Whether through formal locational marginal pricing or through credible approximations of it, the system will need to find a way to express location in price.

The question, then, is not whether location matters in electricity markets. It already does, and it is shaping outcomes every day. The question is whether we choose to recognise that explicitly, through prices that reflect the true state of the system, or continue to absorb it indirectly, through costs that are harder to see and harder to manage.