Batteries Are Cheaper Than Peaker Plants. The Grid Queue Is the Holdup.

Arjun Mehta — Sat, 08 Aug 2026 00:00:00 GMT

The cost argument for grid-scale storage is settled. In most markets a four-hour battery system now undercuts a new gas peaking plant on levelised cost for the same service, and the gap has widened for four consecutive years. What has not changed is how long it takes to connect one, and that number is now the thing determining how much storage gets built.

The bottleneck moved from a spreadsheet to a filing cabinet, which is a harder problem to solve because nobody’s cost curve fixes it.

The queue, in the only terms that matter

Interconnection queues in most large markets contain multiples of the capacity that will ever be built. That is not inherently a scandal; speculative applications are cheap to file and many were never serious. The problem is what the volume does to timelines for the projects that are serious.

Three structural features do most of the damage.

Serial study processes. Each project is studied against the assumed presence of everything ahead of it. When a project ahead withdraws, downstream studies can require redoing, which cascades.
Cost allocation uncertainty. A project’s network upgrade cost is not known until late in the process and can change dramatically based on the behaviour of unrelated applicants. Financing around that uncertainty is expensive.
No meaningful entry cost. Where deposits are small relative to project value, filing broadly is rational, which inflates the queue that everyone else must be studied against.

We can procure a battery system in nine months and energise it in four years. Nobody in this business is waiting on cells.

Why storage suffers more than it should

Storage is disadvantaged by queue processes that were designed for generators. A battery is a flexible asset whose grid impact depends on how it is dispatched, but most study processes evaluate it at maximum output as though it were a thermal plant running at full load.

That assumption inflates the network upgrades attributed to it. Several markets have introduced flexible or limited interconnection arrangements, where an asset accepts curtailment during constrained periods in exchange for a faster and cheaper connection. Where those arrangements exist and are well designed, they work: connection timelines fall substantially and the operational cost of accepted curtailment is usually far lower than developers feared.

Adoption is uneven, and the details matter. A flexible connection with unbounded curtailment risk is not financeable, so the arrangements that succeed cap the exposure.

Queue reform, and what actually moved the needle

The reforms with the best measured record share a common shape: they impose a cost on occupying a queue position and study projects in groups rather than one at a time.

Cluster studies replace serial evaluation with batched analysis, which prevents the cascade problem and produces cost allocations that are stable enough to finance against. Higher, escalating deposits push out applications that were never going to be built. Readiness requirements, such as demonstrated site control, do similar work.

Markets that implemented both together have seen queue volumes fall and completion timelines improve. Markets that raised deposits without reforming study processes mostly just made speculation more expensive without accelerating anything.

The part that is genuinely hard

Some of the delay is not process at all. It is transmission. Where the network physically cannot carry additional output from a location, no reform to study methodology changes the answer, and building new lines takes the better part of a decade largely for permitting and land reasons.

That is the residual problem, and it is the one that will still be here after queue reform is done. Storage helps at the margin because it can absorb generation that would otherwise be curtailed, which is one of the better arguments for co-locating it. But it does not substitute for wires.

For the adaptation side of the same infrastructure question, see our reporting on how cities are budgeting for heat.

Cities Are Budgeting for Heat. Most of Them Still Measure It Wrong.

Arjun Mehta — Tue, 21 Jul 2026 00:00:00 GMT

Heat has finally become a budget line. Cities that had no adaptation plan five years ago now have heat officers, cooling centre networks, and capital programmes for shade and reflective surfaces. The planning is real and mostly sensible. The measurement underneath it is not.

Most municipal heat policy is triggered by readings from a small number of official weather stations, and those stations are frequently sited in exactly the conditions least representative of where people live.

The siting problem

Official meteorological stations are placed for consistency and aviation, which means open ground, good airflow, grass surfaces, and often an airport. Those are reasonable choices for a climate record. They are poor proxies for a dense neighbourhood of asphalt, low albedo roofing, and no canopy.

Mobile and distributed sensing campaigns consistently find large intra-city differences that a single station cannot see.

Within-city spreads of several degrees between the hottest and coolest neighbourhoods at the same hour are routine, and the spread is larger at night than at midday.
Night-time minima are where the divergence matters most physiologically, because inability to cool overnight drives mortality more than peak afternoon temperature.
The gradient correlates with income and canopy cover, which means a city-wide average conceals a distribution with a predictable social pattern.

Our threshold was met four times last summer according to the airport. Our own sensors in three neighbourhoods crossed the same threshold nineteen times.

Why the wrong metric produces the wrong programme

If a heat emergency is declared based on a reading that understates conditions in the worst-affected areas, three things follow mechanically.

Cooling centres open late and close early, because activation is tied to the threshold. Outreach to vulnerable residents is triggered on the same signal, so it also arrives late. And retrospective evaluation of the programme uses the same understated series, which makes interventions look more adequate than they were.

There is a fourth, subtler effect. Capital allocation for shade, canopy, and roof programmes is often prioritised using modelled heat exposure calibrated against the official station. Neighbourhoods whose actual exposure is highest can therefore be systematically underweighted in the investment that would help most.

What better measurement looks like

The technically correct answer is to measure what the body experiences rather than air temperature alone. Heat stress depends on humidity, radiant load, and air movement, which is why wet-bulb globe temperature and similar composite indices exist.

The practical answer is more modest and more achievable. Cities that have improved their measurement did three things: deployed a distributed low-cost sensor network with enough density to resolve neighbourhood differences, calibrated it against the official station rather than replacing that station, and rewrote activation thresholds to trigger on the hottest monitored areas rather than the city average.

The cost is small relative to any capital programme it informs. The institutional obstacle is larger, because it requires accepting that the number the city has been reporting for decades was not describing what residents experienced.

The accountability angle

There is a reason some administrations are slow to adopt better measurement, and it is worth stating directly. Denser monitoring produces a higher count of threshold exceedances, more declared emergency days, and a documented record of which neighbourhoods bear the load.

That record creates obligations. It also creates the evidence base needed to justify the spending, which is why the cities furthest along on measurement tend to be the ones that have already committed capital and need to defend it.

For the generation-side infrastructure that heat demand strains, see our reporting on why storage is stuck in the interconnection queue.

Our Times — Climate