Getting Comfortable with DER Level Merchant Risk: Part 2

Maybe a Little Too Comfortable, Eh?

Written by: Tom Michelman, Senior Director and Distributed Energy Resources (DER) Practice Lead
Publish Date: November 17, 2022
Estimated Reading Time: 10 minutes

Current Outlook: The Future’s So Bright, I’ve Gotta Wear Shades—and That’s Potentially Problematic

If you only had one word to describe RE+ 2022 in Anaheim it would be exuberance. 

More than 27,000 of my closest friends attended RE+ 2022 in September—as pointed out by the organizers, the largest energy related conference in the country. The attendees were awash in the afterglow of the Inflation Reduction Act’s passage in August, after the doldrums of the failure of Build Back Better to be enacted. Today, as a couple of months ago, even with all the friction caused by inflation at recent historic highs, interest rate hikes looming, and supply chain issues lingering, the industry is (and was) super optimistic. Demand for renewables and storage is growing rapidly, natural gas prices are high with no indication they will soon subside leading to high electricity prices in many markets to which mark against. 

So, the exuberance is not definitively irrational, but it’s something to keep an eye on. Such scrutiny is the theme of this Part 2 blog. 

It’s a Seller’s Market

Clearly there is a lot of money in the market and pressure to invest. One market participant put it this way: after years of developers chasing financing, it is now financiers chasing project investments or a “wildcatter” market. Almost every market participant I spoke with noted they had lost out on purchasing early-stage portfolios because of what they perceived as aggressive revenue assumptions by other bidders. To that point, another developer noted the use of “curve shopping”, meaning purchasing multiple forward wholesale electricity and capacity price forecasts in order to use the one that justifies the largest investment. 

It seems like most everyone is feeling the pressure to deploy capital and build their pipeline of projects, and only a few are resisting successfully. 

Nonetheless, one shouldn’t blame the developers, as developers are going to do what developers do—and that is, of course, develop. 

Some of the money wanting to be deployed is from investors who are not seasoned veterans in the renewable energy industry (or even the electricity sector). It is clear from discussions, that DER developers spend an inordinate amount of time finding and educating “outside investors” in how to get comfortable with investing in DER projects and portfolios. One respondent noted that the national EIA data show that utility retail rates have gone up historically over the last 10-20 years 2%, so he and the outside investors were comfortable assuming a 1.5% increase. He fully admitted that this was not a sophisticated approach, but one that outside investors can wrap their arms around (K.I.S.S.). This approach can leave upside on the table for developers/sponsors by justifying less leverage (e.g., less debt and 3^rd party equity, and thus more developer or sponsor equity at a lower assumed rate of return), but the respondent was comfortable taking this more conservative approach. Others parroted the conservative approach of not trying to extract every last dollar of other people’s money for development. 

A Better Way to Build DER Revenue Outlooks

Of course, there are more thoughtful (and justified) methods to DER $/kWh revenue outlooks than leveraging EIA all-in retail price trends. Methods akin to and including the following were described by some market participants:

• Have tight internal controls or use third-party firms to inform price forecasting either top down or bottom-up to blunt internal biases for more optimistic outlooks (yeah, I know, this is self-serving, because SEA is a third-party firm who provides such revenue outlooks. Tough nuggets, the blog is free, and you get what you pay for). 
• Use sensitivities and case analyses with downside and upside cases to gauge risk. Vary as applicable, natural gas, capacity REC prices, and utility wire charges. 
• Increase the hurdle rate of return when unclear how to gauge the variability of certain revenue streams. Better yet, lay off some of that risk on the offtakers. 

My take is that many (perhaps most) market participants use some variation of this approach. The issue is the devil is in the details. How does one create DER variable rate forecasts? How good is one’s REC forecast?

Our best practices for analyzing DER revenue based on a derivative of retail rates tied to specific utility tariff rate classes (as most variable DER $/kWh revenue is) are as follows:

• Collect and analyze historic utility tariff rate class rates by components (e.g., generation, distribution, transmission, etc.) and subcomponents
  • For example, for distribution rate subcomponents, collect and analyze not just the overall component level distribution rate on a customer’s bill but the subcomponents including the base distribution rates, and all its riders that in aggregate make up the distribution component
• Model default service energy charges as a function of forward energy and capacity rates at the time of the default service procurement
  • Adjust for procurement layers as applicable
  • Forecast future default service energy charges as a function of forward/forecasted energy and capacity charges, and as applicable REC prices
• Analyze wire charge tariff filings to understand the drivers to the rate subcomponents
  • Forecast at the individual subcomponent level
  • Take into consideration “exogenous” drivers that impacts load and investment: e.g., energy efficiency, electrification, transmission investments, distribution investments, utility return on equity, upcoming rate cases, aberrations to rates caused by revenue true-ups, etc. 
• Create revenue sensitivity cases (e.g., base, low, and high cases overall and individually on important components)
  • Note P50 / P90 / P95 type of analysis provides illusory precision and would be super expensive to implement (for example, 1) those of you who have implemented Monte Carlo or other types of sophisticated simulations, imagine the variance-covariance matrix one would have to create and justify, and 2) there is certainly not enough data to implement machine learning algorithms)

DER $/kWh Revenue Outlooks in Practice

Interestingly, we found indications that outside investors may not (in practice) be able to or want to digest DER $/kWh revenue forecast best practices approach.

One respondent noted that they generally share historic context on DER and REC $/kWh revenue with investors, and they do not necessarily share the best practices forecasts we provided to the developer with their outside investor; the developer keeps such revenue curves and the justification for them in their back pocket if they get push back on simpler revenue assumptions. 

On the surface I was surprised by such behavior (why wouldn’t you want to share SEA’s well thought out analysis with third party investors) but on reflection it totally makes sense. Investors in projects have many risks to assess, including:

• kWh production uncertainty
  • Causes of erosion of gross revenue including offtaker payment risk, community solar or offtaker management, electric distribution company (EDC) costs, etc.
  • Development and construction risks (e.g., supply chain, site control and permitting, interconnection costs and timing, etc.)

And so on. Which means, of course, $/kWh revenue variability is only one of a litany of risks that underwriters must confront and consider. If one is trying to get a deal done, the simpler the better. Our client was ready to justify $/kWh revenue assumptions but didn’t want to muddle the issue with too many details unless asked and our analysis was needed to justify pro-forma revenue assumptions. 

We know of one large third-party forecaster that provides retail rate $/kWh forecasts at the customer class level (i.e., residential, commercial, industrial vs. rate class level), and is based on all in costs (i.e., includes monthly connect and kW demand charges vs. just based on $/kWh charges). Such an approach is a first order approximation and would be appropriate for a cheap (which I doubt that it is given the purveyor) quick and dirty analysis but comes with pitfalls that may lead to misleading DER $/kWh rate outlooks. 

As requested, (or needed because of time constraints), we also conduct simpler (and less expensive) $/kWh revenue analysis for our clients, and know such analyses have been used to help justify investments. So, we are not dismissive of such approaches, but it is one more indication that a lot of money is being deployed without a more complete and detailed understanding of the drivers of $/kWh revenue volatility. 

How about Hedging?

In our research we asked about the use of hedges including more sophisticated approaches. 

A favored approach is to pass the hot-potato risk onto others, including when possible or appropriate the offtaker. That is for kWh assigned to the offtaker via $/kWh utility bill credits provide a PPA to the offtaker based on a fixed $/kWh (or a fixed $/kWh with escalation schedule e.g., 2.5% annual increase) cost for the bill credits. This implicitly assigns the $/kWh volatility risk of those utility bill credits (e.g., the offtaker’s $/kWh bill credit not covering the cost of the fixed $/kWh price of bill credit) to the offtaker (i.e., assigns the risk of the deal being underwater to the offtaker). 

While not asked explicitly, only one market participant we spoke with volunteered market geographic diversification as a risk mitigating strategy, though other respondents were in multiple markets and may be using such a strategy implicitly. 

When asked about more sophisticated hedging strategies, there was no indication they were being deployed. $/kWh rate insurance is too expensive, even if available. Further, apart from the NY VDER market the non-REC $/kWh revenue is based on derivatives of utility retail rates, and there are no equivalents to robustly traded wholesale electricity spot and futures markets to hedge against.

Thus, except for the NY VDER market, nothing even approximating a perfect hedge exists for holders of DER $/kWh revenue rate volatility (note we will detail the NY VDER market in an upcoming blog). 

We did discuss the theoretical possibility of using dirty hedges (e.g., approximate hedges such as collars on wholesale electricity or natural gas forwards) with one market participant, but neither he nor we have heard of such a strategy currently being deployed to hedge volatile DER $/kWh revenue.

Conclusions: Is Winter Coming?

My most important takeaway from all we have learned is sobering; many DER investors are likely saddled with the winner’s curse because they are either ignoring revenue volatility to some degree (sometimes for good business reasons), don’t understand the magnitude of volatility they are buying into, or may just have internal pressure to couch revenue forecasts high. This may (though not inevitably) lead to a bursting bubble of the DER market.

One need only glance at forward electricity prices to understand that current retail electric rates are very likely to drop substantially in the coming years (and therefore for DER $/kWh revenue based on those retail rates to drop substantially in the coming years). 

Whether investors who have amassed a large portfolio of DER projects dependent on variable $/kWh revenue ever rue the day they took on equity or debt positions for their DER portfolios is dependent on how aggressive they were with their revenue assumptions, the terms of their deals, and whether outside factors result in lower $/kWh DER revenue. 

In the end, someone has to hold the hot potato of variable DER $/kWh rate risk, and my take is that someone is more likely than not going to get burned if and when DER $/kWh rates fall from its current stratospheric levels. 

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If you would like to discuss $/kWh rate variability (either retail rate derived, NY VDER wholesale market derived, or REC based) and/or the various analysis SEA can conduct for you do not hesitate to reach out (tmichelman@seadvantage.com) or read more information about how SEA works with Distributed Energy.