Have a model that needs to clear an IE this quarter?
Initial scoping calls are complimentary. We work in NREL SAM, PVsyst when the project requires it, and PySAM for portfolio-scale automation.
A SAM model on its own is a starting point, not an answer. The default assumptions are reasonable averages, the resource files cover everywhere and nowhere in particular, and the loss stack is whatever the user typed in. We rebuild the model from resource data up, calibrate it against actual operating projects, and deliver a yield distribution your tax equity counsel and lender's IE will fund against.
Modules and inverters get sold on optimism.
Manufacturer energy estimates assume best-case soiling, mismatch, and availability. We back-calculate the implied loss stack and tell you exactly where they stretched.
The EPC's model exists to defend the contract.
An EPC's energy estimate sets the performance guarantee floor. Theirs runs low to make the LDs unreachable. Ours runs honest because we own the owner-side P&L.
Defaults are not assumptions.
Most dev teams run SAM with stock loss factors and call it a day. We tear the loss stack down to first principles, cite each input, and produce sensitivity bounds a lender will accept.
The IE works for the developer.
Independent engineers are paid by the sponsor. We sit on the owner side of the table when the IE delivers, and we know what numbers they will push back on before they do.
NSRDB, TMY3, Solargis, ground-station data. Multi-year, P50, and P90 weather files compared and reconciled. Climate adjustment for long-term trend, not just historical mean.
Module-inverter pairing, DC/AC ratio optimization, tracker type, ground coverage ratio, bifacial gain. Configuration trade-offs run in parametric mode, not picked from a vendor catalog.
Soiling, snow, shading, mismatch, wiring, transformer, availability. Each loss factor cited to a published source or calibrated to operating data. No round numbers, no defaults.
P50, P75, P90, P99 generated from Monte Carlo over weather years and degradation paths. Performance ratio carried out over the asset life. This is the output tax equity will price the deal against.
Behind-the-meter peak shaving, front-of-meter merchant arbitrage, capacity firming, standalone storage ITC modeling. Dispatch strategy modeled against actual rate structures and tariff data.
Tornado diagrams on the inputs that actually move the financial outcome. Scenario sweeps on technology, financing terms, and incentive structures. Breakeven analysis on the variables that matter to the lender.
Modeled output checked against operating data from comparable projects in the same resource zone. Year-over-year actual vs forecast variance benchmarked. Calibration adjustments documented for the IE.
Median annual production. The number sponsor pro formas typically run. Useful for IRR projection, not for sizing debt.
75 percent probability of exceedance. Often the figure tax equity asks for in base case sizing.
90 percent probability of exceedance. The number lenders typically use to size senior debt and DSCR.
One-year-in-a-hundred low production scenario. Used in stress testing, downside modeling, and DSCR floor analysis.
A techno-economic file that holds up under tax equity diligence, lender's IE review, and IRS substantiation. Everything cited, nothing proprietary, all of it transferable to a successor advisor if you ever choose to bring modeling in-house.
Initial scoping calls are complimentary. We work in NREL SAM, PVsyst when the project requires it, and PySAM for portfolio-scale automation.