DNV’s Solar + Storage O&M Cost Model is based on observed and received in-field equipment failure rate data.
Continuing our series on build-transfer agreements, today we’ll be considering the financial details in asset sale structures. Sellers face pressure to take an optimistic view of both production and O&M cost assumptions to maximize value of their assets. Below, read more about DNV’s thoughts on what sellers should review carefully.
In many cases, O&M budget forecasts may be based on broad brush, in-house estimates by the seller, or only on early-life failure rate information provided by equipment manufacturers. In our experience, there’s very little historical reliability data for solar plants spanning 30-40 years, so actual equipment failures and O&M costs—especially late in the project life—could be much higher than forecast, which could take a big bite out of revenue and cash flow for the Owner. To reduce this risk, buyers could either develop their own detailed model or work with a third party that has market and modeling expertise. DNV’s Solar + Storage O&M Cost Model is based on observed and received in-field equipment failure rate data and is augmented by the market experience of our solar team.
Inputs in the pro forma financial models: what’s key?
- Useful life. At DNV, we see an increasing trend of models assuming that projects will perform quite well for 40 years. Imagine a system installed in 1981 operating today (keep in mind that in 1981 personal computers were just introduced, Ronald Reagan was just elected President, and Brittney Spears had just been born). So while it’s potentially possible to keep a solar asset financially viable for so long, financial models we see often don't appropriately reflect realistic equipment failure rates and replacement costs, or system degradation and unavailability assumptions, especially in the later stages of the project operating life when owners are supposed to be pulling in high profits.
- Degradation rates. For system level degradation, DNV often observes the same 0.5% annual rate historically used in 25- or 30-year models just being dragged out to the right for 35 or 40 years. Increasingly, DNV has seen degradation assumptions getting pushed even lower. However, at some point, many module failure modes become sharply non-linear. Without strong O&M oversight and more spending on module replacements, this is likely to lead to significant module failures and production losses.
- System availability. Most models for larger projects assume a 99% system availability. This is a reasonable assumption for well-managed utility-scale systems in the early operation phase, but as time goes on, increased equipment failures—particularly for inverters—make it harder to consistently achieve high system availability.
- Equipment failure rates. In DNV’s opinion, the industry has done a decent job modeling inverter repair costs, but costs for most everything else including modules and trackers haven't been well-characterized. Corrective maintenance budgets for all non-inverter repairs often get lumped together in a O&M budget line item and are not well-supported by data or rigorous analysis. Even when data is employed to construct these budgets, manufacturers and modelers typically use early life failure rates as justification for late-life expectations, which most likely isn't accurate. We know from the typical equipment failure bathtub curve that random failures dominate early on in the operational life, but are eventually overcome by more significant wear-out failures; across a 35- or 40-year life, many components will fail more than once, which will compound the impact of increased costs over time.
Nobody in the industry has a crystal ball to definitively forecast long-term operational cost requirements, and the reality is that there’s a lot of uncertainty around how solar facilities will perform 3 or 4 decades from now. That said, based on DNV estimates, it looks like many of the models we review are more optimistic than the average P50 case they’re intended to reflect.