A battery co-located behind an industrial load can access value pools that a standalone grid-scale project cannot. For the industrial consumer, that means lower energy costs and reduced wholesale exposure. For the battery developer, it means a higher margin ceiling than the merchant market alone provides. The same physical fact drives both: energy discharged on-site never touches the shared transmission network.
A standard front-of-meter battery project makes money in the wholesale energy market: charging when prices are low, discharging when they are high, and capturing ancillary services revenue along the way. Those returns are available to any grid-scale project, and are likely to compress as more batteries chase them.
The value of a ready-to-build project to a developer is set by buyers' confidence in those returns: a function of the price outlook, cost of capital, and the revenue model underpinning the forecast.
Behind-the-meter (BTM) batteries are located on the customer side of the network connection, sharing a grid connection with an industrial load. On top of the wholesale market revenue available to any grid-scale project, a BTM battery can access additional value pools. Who captures them depends on how the battery is operated and contracted.
Value pools available to a BTM battery
The size of each pool varies by site. Loss factors differ by connection point and shift as the network evolves with new connections. Tariff structures vary across network businesses and tariff classes. How much peak shaving is achievable depends on the load profile, and the same battery capacity cannot always serve multiple value pools simultaneously: a battery committed to peak shaving may not be available for energy market dispatch in the same interval. Quantifying the stack for a specific site, and understanding how those pools interact, requires modelling it.
If you're an industrial consumer
Your load, connection, and land are assets in the battery development market. A developer co-locating a battery with your site gets access to value that a standalone project cannot replicate, which can give you negotiating leverage.
A well-structured BTM arrangement could reduce your energy costs in two ways: lower demand charges from peak shaving, and a hedge against wholesale price volatility if you have spot exposure. The size of those savings depends on your network tariff structure, your load profile, your view of future energy price distributions and how the contract is written.
Your involvement can range from passive to active. At one end, you lease the land and connection to a developer and take a fixed payment or a share of savings. At the other, you develop the battery directly, taking on the capital and the upside. Most arrangements sit somewhere in between, with the industrial host contributing site access and the developer contributing capital, connection work, and operational expertise. What share of the value you capture is a function of what you bring and how you negotiate.
If you're a battery developer
Developer margin, the premium a ready-to-build project commands over development costs, is determined by the accepted market value of the project over its operational lifetime. For a merchant project, that expectation tracks the wholesale market outlook. As the BESS fleet grows and spreads compress, expected battery returns (and associated margins) are likely to soften.
If a partnership with a large industrial load is possible, a BTM project accesses value pools that sit outside the traditional merchant stack. Congestion avoidance, network tariff savings, and avoided transmission losses do not compress as the BESS fleet grows because they are driven by network conditions and site-specific factors, not by how many batteries are chasing the same wholesale spread. How that additional value is split between developer and offtaker is a contract question, but the existence of it raises the margin ceiling on both sides of the deal.
Aber Analytics models the BTM value stack for industrial consumers and battery developers, combining power market price modelling with site-level dispatch optimisation to quantify each value pool. Get in touch for more information.