A utility-scale revenue analysis, BTM and FTM modelled together
`[CLIENT-OK NEEDED FROM LUCA]`
A Zurich-area utility commissioned a detailed revenue analysis for a single-digit-MW utility-scale BESS the utility intended to install at one of its industrial customers. One advisory mandate, one report - and a workflow the utility can repeat on every additional industrial customer it evaluates. (fact-base §3.2; client-references-policy.md "single-digit MW" public-safe form)
The client
A Zurich-area utility - a sophisticated, German-speaking-Switzerland buyer evaluating BESS for one of its industrial customers. (anonymised per client-references-policy.md)
The mandate opened around a clean analytical question: does the BTM business case at the industrial customer's site qualify the project, and what FTM optionality sits on top? The buyer needed an independent answer before committing capital - defensible enough to survive an internal review, comparable enough to apply across the rest of the portfolio.
The mandate
A single advisory engagement. One report covering load-profile modelling, BTM scenarios, FTM scenarios, and a sensitivity-modelled investment view. Repeatable on every additional industrial customer the utility evaluates - the methodology is the asset. (fact-base §3.2)
The methodology - four analysis blocks
Load-profile modelling
Hourly and 15-minute load profiles built into SIMULA. Demand-charge composition broken out. On-site generation overlap where relevant. The output feeds the dispatch simulation directly.
BTM scenarios
Peak shaving (reducing the highest 15-minute power draw, the dominant driver of demand-charge economics in Switzerland). Demand-charge reduction. Optimised self-consumption against on-site generation. Each scenario modelled on the actual load profile, not a typical-day approximation.
FTM scenarios
Ancillary-service participation - aFRR (automatic frequency restoration reserve), mFRR (manual frequency restoration reserve). Wholesale arbitrage modelled at Swiss spot prices, with a clear note that the spread is thin today.
Sensitivity model
Excel-side scenario tree. Key drivers tested: electricity price trajectory, ancillary clearing levels, demand-charge tariff structure. The output is a defendable range, not a single-point answer.
The deliverable
A detailed analytical report - technical and financial. An executive presentation of the findings. A sensitivity-modelled Excel of the underlying business case. The same deliverable suite as the broader Advisory line. (fact-base §2.2)
Read the Advisory deliverables →
What we learned
Modelling the BTM and FTM stacks together - rather than sequentially - surfaces interaction effects a stack-at-a-time analysis would miss. Reserving capacity for peak shaving reduces the dispatch availability for FTM services in the same hour, and vice versa. The right structure of the deliverable lets the buyer see those interactions in a single sensitivity view, not across two reports the reviewer has to reconcile by hand.
The value to the utility is repeatability. Every additional industrial customer they evaluate is a candidate for the same workflow, on the same engine, with comparable outputs. The methodology, not any one project, is what scales across the portfolio.
Independent of any OEM
The analysis is unbiased. GridSphere does not represent a battery manufacturer; the deliverable is methodology and a defended business case, not a hardware preference. The buyer chose this engagement specifically because the analysis would not be steered by a vendor relationship. (positioning brief §6 point 3)
A conditional onward path
If the project is built, the asset is a candidate for the GridSphere Platform in a hybrid BTM + FTM configuration. Reporting, dispatch optimisation and trader access then run from there - same business case the asset arrived with from SIMULA. (fact-base §3.2, §2.5)
How an asset arrives platform-native → - What ec-storage does once the asset is operational →
Quote
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