Making Battery Degradation Measurable: Why Cost-Aware Operation Is Essential

As renewable energy becomes the foundation of electricity systems around the world, the importance of stationary battery storage is no longer in question. Lithium-ion batteries are being deployed at unprecedented rates to support grid reliability, integrate variable generation, defer infrastructure upgrades, and provide flexible capacity across multiple electricity markets.

These systems are now considered critical infrastructure. Their ability to charge and discharge energy on demand gives grid operators and energy providers a powerful tool to balance supply and demand, respond to price volatility, and support decarbonization.

Yet, while batteries are increasingly central to system planning, the strategies used to operate them remain largely focused on short-term revenue. This gap between operational reality and technical potential creates a risk: that batteries, if not managed correctly, will fall short of their expected value—economically, technically, and environmentally.

Most Battery Operations Prioritize Short-Term Gains

In the current market environment, battery energy storage systems (BESSs) are typically controlled through revenue-optimizing algorithms that respond to short-term market signals. Whether participating in frequency regulation, trading across day-ahead and intraday markets, or engaging in reserve or capacity mechanisms, the majority of optimization frameworks are designed to maximize immediate profit.

This approach is understandable. Market opportunities are real, and operators are under pressure to deliver returns on capital-intensive assets. The problem is that these decisions rarely account for battery degradation, which introduces a hidden cost that compounds over time.

Degradation reduces usable capacity, limits power output, and in some cases increases safety risks. If not properly managed, it can significantly shorten the useful life of a system or lead to costly replacements. In some business cases, degradation-related losses can account for a large fraction of the total cost of ownership, particularly when project life is assumed to extend over 10 or 15 years. Despite this, degradation is often ignored in daily operation because it is difficult to quantify, and even harder to include in optimization frameworks that favor simplicity and speed.

Battery Degradation Is Not Just Technical—It’s Economic

The physics of battery degradation are complex. Factors such as the depth and rate of charge or discharge, resting states of charge, temperature, and calendar time all influence how quickly a battery loses capacity and efficiency. Different chemistries and designs degrade in different ways, and degradation profiles are often nonlinear, with certain thresholds or conditions accelerating damage disproportionately.

From an economic standpoint, this variability presents a challenge. If degradation cannot be measured and priced accurately, it cannot be factored into dispatch decisions. As a result, operators face a structural blind spot: the systems are making choices that optimize short-term margins while potentially destroying long-term value. In practical terms, this might mean over-responding to price spikes, engaging in high-throughput trading strategies that shorten asset life, or failing to reserve enough capacity for high-value services like frequency regulation later in the project lifecycle.

The Missing Piece: A Degradation Cost Function

One promising way to bridge this gap is to implement a cost function that quantifies battery degradation in monetary terms and integrates this cost into the optimization process.

A cost function is a mathematical model that estimates the financial impact of a given operational action on battery health. For example, if a high-rate discharge at low state of charge is known to accelerate degradation, the cost function assigns a penalty to that action. This cost is then compared against the expected market revenue of the action, allowing the operator or algorithm to weigh short-term gain against long-term impact.

This approach aligns with how other critical infrastructure is managed. In thermal plants, for example, operators account for startup costs and wear-and-tear in dispatch planning. In aviation, flight control systems include maintenance cost considerations in route and engine use optimization. There is no reason battery storage should be any different.

However, for this to work, the cost function must be credible. It cannot rely on simple proxies such as number of cycles or total energy throughput. Degradation in modern lithium-ion batteries is too nuanced to be captured by one-size-fits-all rules. Instead, the cost function must be informed by detailed models that reflect battery-specific ageing behaviors under different conditions.

These models may be physics-based, data-driven, or hybrid in nature. Ideally, they are validated against real-world operational data and tailored to the actual battery system in use. Without this rigor, there is a risk that the cost function either underestimates degradation, leading to overuse, or overestimates it, leading to missed opportunities.

Operational Implications and Market Potential

Integrating a degradation-aware cost function into BESS operation can fundamentally improve system performance. Operators can maintain higher capacity over time, reduce maintenance and replacement costs, and plan reinvestments more accurately. In projects with long-term power purchase agreements (PPAs) or multi-year capacity commitments, this can make the difference between a profitable and an unprofitable investment.

Furthermore, this approach opens the door to new forms of asset management. Storage portfolios can be benchmarked not only on energy dispatched or revenue earned, but also on degradation efficiency—how much value is extracted per unit of capacity lost. Over time, this can become a standard performance indicator, encouraging best practices across the industry. System operators and aggregators can also use degradation cost functions to harmonize control strategies across heterogeneous assets, improving fleet-level performance.

Cost Functions Provide Actionable Insight

Battery energy storage systems are key to the stability and flexibility of tomorrow’s energy systems. But their long-term value depends not only on how much energy they move, but on how wisely they are operated. Integrating degradation into operational decision-making is no longer optional; it is a necessary step toward responsible, sustainable, and economically viable storage deployment.

Cost functions that translate technical ageing into financial terms offer a practical solution to this challenge. When built on accurate models and integrated into dispatch algorithms, they enable a more balanced strategy, one that recognizes both immediate market opportunities and long-term asset health. By making battery degradation measurable and actionable, we can unlock smarter storage and more resilient energy systems.

—Laura Laringe is CEO and co-founder of reLi Energy GmbH.