Author: Tom Michelman, Vice President & Senior Director, Distributed Energy Resources Practice Lead
Estimated read time: 10 minutes
Until recently, many Distributed Energy Resource (DER) market participants whose compensation is tied to some derivative of retail electric rates could afford to be somewhat imprecise about revenue forecasting.
Why? Because the market was forgiving.
When capital was abundant, debt was cheap, policy momentum was strong, and project economics often looked attractive under a wide range of assumptions, a directional revenue view could carry a lot of weight and be “good enough”. Developers could use crude or simplistic DER revenue, or price-to-compare (PTC), forecasts to screen markets. Investors could use them to keep diligence moving. Buyers could use them to compare portfolios. In many cases, a revenue forecast did not need to explain every moving part because the broader market environment gave projects room to absorb uncertainty.
That room is narrowing.
Today’s DER market operates under a different set of conditions. Costs have risen due to inflation, and dirt-cheap debt is no longer available. Federal incentives are sunsetting. As a result, project margins are under more pressure, and financing is more selective. Capacity prices have become harder to treat as background noise. Retail-rate-derived revenue streams are being shaped by increasingly complex interactions among wholesale markets, utility procurement practices, state policy, rate design, reconciliation mechanisms, REC markets, and customer-class allocation.
For community solar, virtual net metering, and other DER revenue models, the value of a project can turn on details that may not be visible in a simplified forecast.
That is the central problem with “good enough” forecasting in the current market. While such forecasts may produce a curve that may appear reasonable when compared to recent history, they cannot explain what is driving the forecast, what could change it, and which assumptions matter most, it may not be good enough for the decisions now being made in a less forgiving landscape.
From Exuberance to Scrutiny
To be fair, there have been good reasons why market participants relied on simpler forecasts in the past, more forgiving landscape.
For early-stage screening, a rough forecast was often adequate. Developers generally did not need a detailed, nuanced, diligence-ready revenue model to decide whether a market deserved a closer look. Investors did not need every tariff rider and reconciliation mechanism modeled in detail before deciding whether an opportunity belonged in the pipeline. In some settings, a low-cost, fast, directional view could serve a legitimate purpose.
And in the stronger, more forgiving market conditions of the times, forecast errors were easier to absorb. If expected project margins are wide, incentives are favorable, buyer demand is strong, and capital is available, a revenue assumption can be imperfect without necessarily changing the investment decision.
That was part of the environment we described in our earlier two-part series, Getting Comfortable with DER Level Merchant Risk. In 2022, the market still had a seller’s-market feel. Developers and investors were trying to get comfortable with variable $/kWh revenue streams, but many were also under pressure to deploy capital, build pipelines, and win projects. In that kind of market, simplicity had commercial appeal. A forecast that was easy to explain could sometimes be more useful in a transaction process than one that captured the nuance of underlying drivers of revenue volatility.
Even then, the warning signs were visible. In Getting Comfortable with DER Level Merchant Risk: Part 1, we emphasized that DER incentive programs varied widely regarding which revenue components were fixed versus variable. In Part 2, we noted that some DER investors risked becoming “a little too comfortable” with revenue volatility, especially when aggressive assumptions helped support competitive bids or portfolio valuations.
That concern is more relevant now in a less forgiving environment. What looked like a manageable risk in a hot market may become a survivability issue in a tighter one.
Revenue Streams are Derivatives of Numerous Drivers
The case for more nuanced revenue forecasting has become stronger because the moving parts are moving more.
Many DER revenue components are not simple market prices. Rather, they are derivatives of other drivers: utility retail rates, tariff structures, procurement plans, wholesale energy and capacity markets, rate classes, reconciliation mechanisms, REC markets, policy design, and regulatory timelines.
That chain of translation matters. A wholesale market price does not necessarily translate to a retail rate or PTC immediately or cleanly. It may be filtered through default service procurements, hedging structures, utility-specific rate design, wire charge cost and revenue drivers (e.g., T&D investment, load growth, allowed rate of return, etc.) state policy, customer-class allocation, line losses, reserve margins, and true-up mechanisms.
A model that treats a retail-rate-derived DER revenue stream as a simple escalation assumption, a generic customer-class average, or a curve disconnected from the machinery underneath it, will likely miss the factors that determine whether revenue trends are durable or temporary, or an outlook is financeable or speculative, attractive or mispriced.
In other words, the devil is in the details.
That phrase can sound cliché, but in DER revenue forecasting, the details are not decorative… they drive the revenue stream.
Case Study: Illinois
Recent developments in Illinois provide a useful warning label.
In our 2025 and 2026 work on ComEd and Ameren-IL PTC forecasts, the lesson was not simply that rates changed. The lesson was that rates changed for reasons that a credible forecast needed to understand and articulate.
For ComEd, forecasting the PTC requires careful treatment of the Purchased Electricity Charge, or PEC, which is the largest component of the retail PTC. The PEC is not a single simple input. It reflects layered energy procurements, spot electricity purchases, carbon mitigation credit (CMC) mechanics, capacity costs, transmission charges, and purchased electricity adjustments. In our ComEd analysis, we demonstrated that a trustworthy forecast needs to account for procurement layering, the evolving CMC hedge, and the transformation of PJM capacity prices from wholesale $/MW-day values into retail $/kWh impacts.
For Ameren-IL, the story has been different but equally instructive. In summer 2025, Ameren’s PTC rates increased sharply after MISO capacity prices rose dramatically and the actual level of capacity hedging fell far short of the Illinois Power Agency’s planning targets. That outcome mattered directly for community solar developers because elevated capacity costs flowed through to summer PTC rates. The broader lesson was clear: procurement design, auction outcomes, and hedge realization can all materially affect retail-rate-derived revenue streams.
Ameren also illustrates why subscriber mix and rate-class details matter. Residential DS-1 customers are not economically uniform. In non-summer months, Ameren allocates residential capacity costs to DS-1 Block 1, meaning the first 800 kWh consumed during a summer billing month (Block 1) carries a different embedded cost profile than Block 2 energy (all kWh above 800 kWh in a billing month). For community solar portfolios, the particular mix of subscriber composition is therefore not just a marketing question. Rather, it can and will affect realized revenue. A forecast that treats DS-1 as a blended residential average can smooth away a structural difference that is increasingly important in a rising-capacity-cost environment and ignoring this nuance risks locking in unacceptable margins or even losses.
Then there are one-time adjustments.
In December 2025, Ameren residential and small commercial customers received a large temporary credit tied to a FERC-approved settlement related to the 2015–2016 MISO Planning Resource Auction. That credit reduced the Purchased Electricity Adjustment, lowered the PEC, and therefore lowered the PTC for that month. But it did not represent a collapse in underlying energy costs. It was a one-time settlement distribution flowing through a PEC reconciliation mechanism. A model that treated that month as part of a new structural baseline would produce a distorted forward view.
That is the point. These are not footnotes. They are the machinery that turns market prices, statutes, utility filings, procurement outcomes, settlements, and customer characteristics into project revenue.
If the machinery changes, the revenue outlook changes. If the machinery is glossed-over or misunderstood, the forecast can be an inadequate measure of project viability for reasons that are difficult to detect until after a project has been priced, financed, acquired, or built.
The Problem is Not Just Forecast Error
Every forecast will be wrong in some respect. That is not the issue.
The more important question is whether the forecast is thoughtful, believable and trustworthy, its story illuminating the source of upside and risk in a manner that brings comfort to more discriminating audiences.
A strong and nuanced forecast should help a developer, investor, lender, buyer, or asset owner understand what is driving the result. Is the revenue outlook being driven by energy prices? Capacity prices? Transmission charges? REC values? Rate-case outcomes? Reconciliation mechanisms? Utility procurement timing? Customer-class allocation? Subscriber mix? Policy design? A temporary true-up? A structural change?
A forward curve without that context can create false comfort, miss upside potential, or downside risk.
That is especially dangerous in DER markets because retail rates often look simple from the outside. But the values that flow into DER compensation may be affected by multiple components and subcomponents, each with its own drivers, timing, volatility, and regulatory context.
Consider two forecasts, one created by simple extrapolation, the other grounded in nuanced analysis of market fundamentals, tariff mechanics, procurement rules, and policy analysis. On the surface, both may look similar. However, in diligence, they provide very different outcomes. When confidence matters under tighter market conditions, the former provides information, while the latter can provide confidence.
Investment decisions are not made only on expected value. They are made on confidence that upside potential and downside exposure can withstand critical interrogation from investment committees, budget holders, or buyers.
In a forgiving market, unexplained forecast risk can be easier to ignore. In a tougher market, unexplained forecast risk becomes harder to finance.
What Better DER Revenue Forecasting Requires
That means analyzing each market independently. A DER revenue stream in Illinois may behave differently from one in Maine, Massachusetts, New York, Pennsylvania, Maryland, or New Jersey. Community solar, virtual net metering, VDER, net energy billing, REC-based structures, and retail-rate-derived credits each carry different forms of variability. Even within a single state, utility-specific rate design and customer-class rules can produce materially different outcomes.
It also means going deeper than annual averages. Monthly analysis can matter because revenue drivers are often seasonal, procurement-specific, or tied to billing periods. Capacity values may affect summer and non-summer periods differently. Reconciliation charges may appear in one month and reverse or disappear later. Customer usage blocks may matter in certain months but not others.
Better forecasting also requires separating structural changes from temporary noise. A rate spike may reflect a new market reality, or it may reflect a one-time adjustment. A low month may indicate declining fundamentals, or it may reflect a temporary credit. The forecast should not only show what happened; it should explain why it happened and whether it should influence the forward view.
Finally, better forecasting needs documentation. A revenue curve is more useful when accompanied by the explanation needed to defend it: major assumptions, key drivers, tariff and policy mechanics, historical context, and base, low, and high cases that help decision-makers understand risk. Providing such detail, explaining such nuance is impossible in a one or two-page market update snapshot.
A Better Question for The Market Ahead
The useful question now is not simply whether a DER revenue forecast looks reasonable.
The better question is whether it is reliable for the decision it is being used to support.
A rough forecast may still be appropriate for an early market screen. But the closer a project gets to financing, acquisition, portfolio valuation, subscriber pricing, or strategic market entry, the more important it becomes to understand what is actually driving the revenue outlook.
For developers, that means knowing whether projected revenue is being shaped by durable market fundamentals, temporary adjustments, rate-class details, customer mix, or policy mechanisms that could change. For investors and lenders, it means understanding downside exposure, assumption sensitivity, and whether the forecast can withstand diligence. For buyers and asset owners, it means distinguishing between a portfolio that is attractively priced and one that is carrying misunderstood revenue risk.
That is the idea behind SEA’s Revenue Stack Advantage approach.
As we described in our 2025 blog post, SEA’s Revenue Stack Advantage Approach for Analyzing and Forecasting Distributed Solar Variable Revenue Streams, DER revenue forecasting requires more than applying a generic escalation rate to a current tariff value. It requires understanding the components and subcomponents of the revenue stack, how they interact, and how they may change over time.
At Sustainable Energy Advantage, our DER revenue analysis and forecasting work is built around the idea that revenue curves should be grounded in the market, tariff, policy, procurement, and customer-class mechanics that determine how revenue is actually realized. The point is not to make forecasts more complicated than they need to be. The point is to make them useful, explainable, and reliable when the stakes are high.
That is what we mean by Revenue Stack Advantage.
The answer may not always be simple. But it should be knowable.
In a forgiving market, “good enough” sometimes was good enough. In a more discriminating market shaped by inflation, higher interest rates, sunsetting tax credits, tariff uncertainty, affordability concerns, and tighter scrutiny of project economics, the details are no longer optional.
If your current approach to DER revenue forecasting no longer feels good enough for the decisions you need to make, we would welcome the conversation. Reach out to SEA to discuss whether our off-the-shelf forecasts, customized revenue analysis, or broader Revenue Stack Advantage approach can help you better understand the revenue streams driving your projects, portfolios, or market-entry decisions.
For more on the Illinois examples discussed above, see our posts on ComEd and Ameren-IL PTC forecasting:
What insightful commentary by the author ;)