Original title: Lifetime Profit-Maximising Co-optimisation of Multi-Service Stacking for Battery Storage
Yuxin Xia, Frederik Schiele, Yihong Zhou, Volkan Kumtepeli +3 · September 2026
Giant batteries on the power grid can earn money by selling electricity and helping keep the grid stable. But using a battery wears it out. Figuring out which jobs to combine to make the most money over its entire life is hard. Decisions compete for limited battery space, follow strict grid rules, and cause wear and tear. Researchers built a planning tool that schedules these jobs while tracking battery wear. The tool looks ahead in time and balances battery charge levels with grid rules. Testing it with real market data from Great Britain, they found that planning for battery wear boosts lifetime revenue by up to 32%. Using a more detailed wear model adds up to another 16% in revenue. To maximize profit, operators must change their mix of jobs as batteries grow older, and they consistently favor jobs that respond to positive grid frequency shifts.
Imagine you have a car that you use for both short city trips and long highway drives. Short trips cause more wear per mile, but long drives might pay better if you're a delivery driver. You need to decide how to use the car each day to make the most money over its lifetime, considering that the car ages differently with each type of use. In this paper, the battery is like the car, and the services are like different types of trips. The method helps decide the optimal mix by accounting for how the battery ages over time.
Battery storage operators can earn significantly more profit by planning for how their batteries age over time. This affects the economics of renewable energy storage and grid management, potentially leading to better use of storage assets.
The study is demonstrated only for the Great Britain market and specific frequency response services, so results may not generalize to other regions or market structures. It does not account for all possible battery technologies or degradation mechanisms, and the abstract does not discuss computational constraints.
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Lifetime Profit-Maximising Co-optimisation of Multi-Service Stacking for Battery Storage — Yuxin Xia, Frederik Schiele, Yihong Zhou et al.
Abstract licence: CC0
Explanation generated by Synthesis from the abstract — it is not the original paper. This is a preprint, so it hasn't necessarily been peer reviewed.