Case Study: Dominion Energy

 Greetings Readers,

I am eager to provide the first climate risk transfer case study on the Climate Risk Valuation blog! For case studies, I will identify current events (or memorable ones from my 20-year career in this space) that demonstrate how valuing and transferring climate risk can create value and advance sustainable development goals.

I will structure case studies following the template shown below. Hopefully you will find these examples relevant and enlightening!

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Institution exposed to climate risk: Dominion Energy's Coastal Virginia Offshore Wind Project (CVOW)

Sector: Renewable energy

Physical climate risk: wind speed and timing

Financial risk: Income statement (variable business cost of goods sold)

Problem: Dominion is exposed to unforeseen electricity replacement costs. If the wind speed and resulting electricity generated are below a guaranteed threshold, then the utility must procure replacement energy to meet the guarantee deficit. Furthermore, the Virginia State Corporation Commission (SCC) requires that Dominion shareholders--not its customers--bear the cost of replacement energy.  

Solution: Dominion, as owner and operator of the offshore wind farm, can purchase a proxy generation swap. Dominion would effectively pay a climate insurer a risk premium in order to fix its generation revenue risk: 

-if generation falls below the mandated guarantee threshold, then the insurer pays Dominion an amount equal to the value of the electricity deficit.

-if generation falls above the threshold, then Dominion pays the insurer an amount equal to the value of the electricity surplus.

Additional commentary:

The CVOW Project is described further here.

This is an interesting risk management scenario within the energy sector. Many utilities rely upon rate setting as a means to smooth profitability. For example, if a utility builds or repairs infrastructure; recovers from unforeseen low profitability; refinances its debt; or makes other capital cost decisions; then the utility typically will raise rates on its customers to help meet financial obligations.

The 'rate lever' is one reason why utilities can be less likely execute innovative financial hedging strategies. During my 20 years in the climate insurance market, rate setting has derailed multiple hedging discussions with utilities (e.g. a water utility in the western U.S. decided not to execute a $25 million drought hedge after 12 months of work with them designing and structuring a customized insurance product for them). In the renewable energy sector, this has meant that special purpose vehicles (and their investor or utility owners) are more likely to purchase proxy generation swaps rather than the utilities themselves.

In this case, however, Dominion is facing a specific regulatory constraint: the SCC ruled that:

"...for the life of the project, customers shall be held harmless for any shortfall in energy production below an annual net capacity factor* of 42 percent, as measured on a three-year rolling average."

A natural question becomes: how much financial risk does a capacity factor shortfall represent to Dominion?

With some assumptions, we can estimate the amount of financial exposure.

Average annual capacity factor for an offshore wind farm: 29-52%**

Theoretical (though unlikely) minimum capacity factor: 0%

Size of CVOW project: 176 turbines x 14.7 MW per turbine = 2,587 MW

Spot price of electricity in the Dominion zone of the PJM market (the market within which the state of Virginia is a part) in September 2022: $61 / MWh

Annual number of hours of operation: 24 hours/day x 365 days/year = 8,760 hours/year

Annual $ exposure = (Actual CF - SCC CF threshold) x Project size x Electricity price x 8,760 hours/yr

Realistic downside scenario (29% CF):

-$180 million = (29% - 42%) x 2,587 MW x $61 / MWh x 8,760 hours/yr

Theoretical maximum downside scenario (0% CF):

-$581 million = (0% - 42%) x 2,587 MW x $61 / MWh x 8,760 hours/yr

Clearly, variable wind speed and timing can pose extreme financial risk to Dominion. Calculating the capacity factor on a 3-year rolling basis could reduce the annualized financial risk slightly, but Dominion would be dealing with a 9 figure exposure nonetheless. Such risk can cause myriad issues including increased volatility of quarterly earnings, increased cost of debt, amongst others. A proxy generation swap would make Dominion's project revenue more predictable. This in turn can create value for Dominion by demonstrating to shareholders, lenders, and the broader market that Dominion is managing its risk in prudent fashion. 

References:

* The United States Department of Energy defines the capacity factor of a wind turbine as its average power output divided by its maximum power capability.

**International Energy Agency

Regards,

Prime