Webinar — How to Manage Uncertainty in BESS | 17 June, 2 pm
The battery energy storage system (BESS) market is growing at a rapid pace. However, the gap between the revenues projected in business plans and those actually generated remains a poorly documented – and often underestimated – issue. How can one build a robust financial model in a market where the rules are changing as fast as the technology itself?
This is the central question of a webinar organised jointly by Greensolver, Compass Lexecon and StackEase, on 17 June at 2.00 pm CET (duration: 1 hour 15 minutes).
A four-part programme
Greensolver will open with a re-analysis of the BESS business plans drawn up between 2020 and 2025: what are the discrepancies between projected and actual revenues? What lessons can be learned for future financial modelling? Léo Chalon, Director of Financial Advisory, will also present market developments, the new rules of the game and best practices from the UK market.
Compass Lexecon will contribute its expertise in market price modelling: scenarios and methods for forecasting long-term prices in a context of structural uncertainty.
StackEase, a BESS optimiser, will outline its fundamental modelling approaches to revenue stacking: assumptions, typical results and sensitivity analyses to refine revenue projections.
Why take part?
From CAPEX and OPEX to revenue assumptions and sensitivity analyses, the robustness of a BESS financial model depends on real-world data and multidisciplinary expertise. This webinar will provide you with the tools to challenge your assumptions and strengthen the bankability of your energy storage projects.
📅 17 June 2026 — 2.00 pm CET — 1 hour 15 minutes 👉 Register for the webinar →
How can Greensolver help you?
- Financial modelling and review of the BESS business plan
- Revenue stacking modelling et analyse de sensibilité
- Technical and advisory services from BESS throughout the entire lifecycle
- BESS technical due diligence and support with bankability
Written by Paul Prieto, Marketing Manager
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