The most common question we hear from municipal utilities is not: “Is a battery storage system worthwhile?” It is: “How robust is the economic calculation—and what risk are we taking on?”
That is the crucial difference. Those who only ask about ROI think in point forecasts. Those who ask about predictability and risk corridors think like serious investors. It is precisely this second perspective that determines whether a BESS project passes the supervisory board—or fails because of it.
This article maps the three central economic levers of a battery storage system, ranks them by predictability, and shows which role model typically fits which municipal utility size and risk appetite.
What “controllable value creation” means for your municipal utility
“Controllable value creation” is not a marketing term—it refers to something precise: the part of the BESS business case that you can secure with your own data, independent of market price developments or regulatory changes.
What this means in concrete terms depends on your municipal utility size:
Small municipal utility (<€500 million annual revenue): Controllable value creation here primarily means grid relief and security of supply—levers that can be directly measured and planned using your own load profile. The critical question is not “What does FCR yield?” but rather: “How much demand charge reduction is realistic based on our load curve data?”
Medium-sized municipal utility (€500 million–€2 billion): Structured flexibility marketing comes into play here. A dedicated battery storage project with an external asset manager or optimizer enables systematic access to balancing energy markets (FCR, and depending on project setup, also aFRR)—with foreseeable revenue corridors based on historical market data.
Large utility (>€2 billion): Multi-asset strategy, portfolio optimization, in-house trading expertise. Controllable value creation here means hedging market risks strategically—for example, through a PSA (Power Sales Agreement) that secures a minimum revenue while selected marketing windows remain open for upside.
Common to all three: The most predictable lever is always the one based on your own data.
The three revenue levers—ranked by predictability
A battery storage system unlocks multiple revenue sources simultaneously. What matters is how reliably these sources can be calculated in advance.
Lever 1: Grid charge optimization—directly measurable
Demand charges account for 30–50% of grid charges at many municipal utilities. A battery storage system can shave load peaks and thereby reduce the demand component—based on your own load curve data. The savings potential can be precisely modeled before project start: not a scenario, not an assumption, but a calculation using your measured values.
This lever is not spectacular, but it is bankable—it can be documented with historical consumption data and creates the stable base revenue of any business case.
Lever 2: Balancing energy marketing—historically verifiable, but volatile
FCR (primary control reserve), and depending on project setup also aFRR, is the best-known revenue path for battery storage systems. Historical EPEX data allow modeling of revenue corridors—but: markets change. FCR prices have shifted significantly in recent years.
For a robust business case, this means: balancing energy markets belong in the sensitivity analysis, not in the base case. A stress test that still shows a positive net present value with a 30% revenue decline is more meaningful than an optimistic point forecast.
Lever 3: Avoided grid expansion—CAPEX comparison
Those who avoid or postpone grid expansion through a battery storage system achieve an indirect economic benefit: The CAPEX comparison between cable expansion and BESS investment often shows that the storage system is the more cost-effective solution—while additionally offering revenue potential that conventional grid expansion does not deliver.
This lever is the most difficult to monetize, but in many grid planning scenarios it is the strongest strategic argument before the supervisory board.
TCO predictability: Why the investment sum does not determine the business case
The most common question about the BESS business case is: “What does it cost?” The right question is: “What does it cost over the entire lifetime—and how do revenues and costs develop in different scenarios?”
Total Cost of Ownership (TCO) over 15 years includes:
- CAPEX: Acquisition, installation, grid connection—the most visible, but not the sole decisive part
- OPEX: Maintenance, insurance, monitoring, control center access, grid charges for internal consumption
- Degradation: Capacity loss over the lifetime—typically 2–3% p.a. for LFP technology
- Augmentation: When must capacity be retrofitted to maintain revenue profiles?
- WACC: Financing costs and return requirements of your municipal utility
The core: Those who only optimize CAPEX are planning blind. An offer with a low list price but high OPEX costs and no clear augmentation option can be more expensive over 15 years than a higher initial investment with a transparent TCO structure.
For the financial buyer, this means: The business case must be presented as a sensitivity model. A tornado analysis covering CAPEX deviation, revenue decline, degradation rate, and WACC shows which assumptions most strongly influence the result. This is not uncertainty—this is methodological rigor.
Role models as an economic framework
How much risk your municipal utility wants and can bear determines the right business case more than the technology choice. Four role models are available:
| Role Model | Risk Profile | Revenue Potential | Internal Effort |
|---|---|---|---|
| Contracting / JV | Very low | Low | Minimal |
| PSA (Power Sales Agreement) | Low | Low–Medium | Low |
| Ownership + Optimizer | Medium | Medium–High | Medium |
| In-house Operation | High | High | High |
Contracting / JV: An external partner finances, builds, and operates—the municipal utility provides land and grid connection, receives usage rights or a stake. No CAPEX, minimal risk, but also little operational control.
PSA (Power Sales Agreement): A marketer takes over the storage project and guarantees the municipal utility a minimum revenue—the upside remains with the marketer. Maximum predictability with moderate returns.
Ownership + Optimizer: The municipal utility invests, an external asset manager handles ongoing marketing optimization. Full owner returns with limited internal operational effort.
In-house operation: The municipal utility assumes full responsibility—from investment to balancing energy marketing. Highest return potential, but also highest know-how and resource requirements.
Classification framework: Which model fits your municipal utility?
No two municipal utilities are alike. But three factors determine which role model typically fits best:
- Internal capacity: Do you have an in-house team that understands and can operate balancing energy markets?
- Grid connection status: Is a suitable grid connection realizable in the foreseeable future—or is the grid connection the actual bottleneck?
- Risk appetite: Which downside scenario is acceptable for your municipal utility without jeopardizing political and economic support?
Small municipal utility, low risk appetite: Contracting or PSA. No dedicated BESS team required—but full participation in the energy transition.
Medium-sized municipal utility, medium risk appetite: Ownership + Optimizer. Own asset, external knowledge provider, board resolution based on a clear TCO analysis.
Large utility, high risk appetite and in-house trading expertise: In-house operation with multi-asset strategy.
Important: The right entry point is not the “best” business case on paper—but the one that can actually be implemented in your organization and gains approval from internal boards.
Conclusion: Controllable value creation begins with your data
A BESS business case is not decided by the current market price for FCR—but by the quality of the data foundation, the choice of the right role model, and a TCO analysis that remains robust even under unfavorable scenarios.
The first step is always the same: your load profile. It shows which revenue lever has the greatest controllable potential for your specific consumption and feed-in behavior—and which role model fits accordingly.
Have your load profile analyzed—free and without obligation. Controllable value creation begins with data.