BESS Software Comparison
Choosing the right BESS modelling tool.
Generic models miss the physics. Spreadsheets break under complexity. Here is what to look for — and how Catalyst compares.
The four approaches teams use today
Spreadsheet models (Excel / Google Sheets)
Common, but limitedStrengths
- +No licence cost
- +Fully customisable
- +Easy to share
Limitations
- –No physics-based degradation — flat percentage assumptions only
- –Revenue stacking across FCR, aFRR, and arbitrage is manual and error-prone
- –No market data integration — assumptions go stale immediately
- –Audit trail is non-existent — lenders cannot verify assumptions
- –Scenario analysis at scale (50+ configs) is practically impossible
- –Grid fee and regulatory changes require complete manual rework
Acceptable for rough screening. Inappropriate for investment-grade analysis or lender due diligence.
Generic project finance / DCF models
Structural gapStrengths
- +Finance teams already know the structure
- +Handles debt/equity splits cleanly
Limitations
- –Not designed for dispatch simulation — treat BESS revenue as a flat annual assumption
- –Cannot model dispatch constraints, round-trip efficiency, or state-of-charge limits
- –Multi-market stacking requires manual layer-by-layer construction
- –EEG co-location rules not supported
- –Results cannot be validated against historical market data
Use downstream for project finance structuring — not as the primary techno-economic model.
In-house proprietary tools
High cost, bespoke riskStrengths
- +Tailored to specific markets and assets
- +No licence dependency
Limitations
- –Typically 6–18 months to build at significant engineering cost
- –Single-team expertise — no continuity if key developers leave
- –Ongoing maintenance burden as markets and regulations evolve
- –Cannot benefit from industry-wide data and methodology improvements
Reasonable for large-scale IPPs with dedicated engineering teams. Prohibitive for most project developers.
Catalyst by phelas
Purpose-built for BESSStrengths
- +Physics-based battery degradation (cycle and calendar aging)
- +Multi-market revenue stacking: FCR, aFRR, Day-Ahead, Intraday
- +Co-location modelling: Wind + BESS, PV + BESS with EEG constraints
- +Live market data integration for German, Austrian, and Swiss markets
- +Audit-ready outputs: every assumption logged and traceable
- +Bankable project finance documentation generated directly from the model
- +Run 50+ configurations in minutes — not weeks
Limitations
- –European market focus (DE, AT, CH, expanding)
- –SaaS subscription required
The only purpose-built platform combining dispatch simulation, degradation modelling, and bankable documentation for European BESS projects.
What separates purpose-built BESS software from generic tools
Dispatch simulation with real constraints
A BESS does not earn a flat annual revenue. It dispatches based on market prices, state-of-charge, round-trip efficiency, minimum rest periods, and grid connection limits. Generic models ignore these constraints. Catalyst models them with the same physics a real dispatch optimiser uses — so the revenue projection actually reflects what the asset will earn.
Battery degradation that matches reality
Capacity fade and efficiency loss are not linear. Cycle aging depends on depth of discharge, temperature, and C-rate. Calendar aging continues even when the battery is idle. A flat "-2% per year" degradation assumption can overstate revenues by 15–30% over a 10-year project lifetime. Catalyst uses empirical degradation models validated against real-world battery data.
Regulatory and market data stays current
FCR tender volumes, aFRR capacity prices, grid fees (§ 19 StromNEV, Offshore-Umlage), and EEG market premiums change constantly. Catalyst integrates updated market data so your model reflects current conditions — not figures from a spreadsheet that has been circulating for six months.
Bankable outputs for investment committees and lenders
Project finance banks and investment committees cannot work with a cell-linked Excel file. They need traceable assumptions, sensitivity ranges, DSCR analysis, and output formats they can present to credit committees. Catalyst generates these directly from the same model that ran the technical analysis — no reformatting, no translation risk.
When to use Catalyst
Site screening and early-stage feasibility
Run fast scenario sweeps across asset sizes and revenue strategies to identify the most promising projects before committing engineering resource.
Bankable feasibility studies
Produce investment-grade analysis with traceable assumptions and audit-ready documentation for project finance and equity investors.
Portfolio stress testing
Apply consistent methodology across all assets in your portfolio to identify revenue sensitivity to FCR price movements, regulatory changes, or CapEx revisions.
Due diligence support
Provide third-party verifiable analysis for M&A transactions, refinancing, or equity raises — with full assumption traceability.
See how Catalyst models your project.
We run a live analysis of your specific site in 30 minutes. No generic demo — your project, your numbers.