January 20, 2017

Whitepaper by Brattle Economists Examines Effective Hedging Instruments for Renewable Resource Development

A whitepaper by Brattle economists examines how wind generators could use standard electric and gas forward contracts to hedge its revenue to reduce risk over mid- to long-term horizons. The whitepaper also demonstrates how to set effective hedge ratios to reduce merchant risk for a wind plant when a utility purchase power agreement (PPA) is not available. Its recommendations take into account the complexities of the seasonal and intraday timing of wind output and how it tends to be negatively correlated with spot power prices.

The steady and rapid growth of renewable generation resources in the U.S. over the last several years has caused many states to be well ahead of their renewable portfolio standard (RPS) targets. Accordingly, there is increasing interest in developing renewables as merchant assets not secured under a long-term PPA for their energy or renewable energy credits (REC) back to a utility.

The Brattle whitepaper demonstrates hedging methods from the point of view of a single wind asset, as opposed to a plant embedded in a large generation portfolio. The authors point out that the portfolio problem is a more diversified one, but the approaches demonstrated in their analysis are still applicable to what could be done on the margin to a portfolio as more wind is included in the fleet and region. Although wind assets in the Electric Reliability Council of Texas (ERCOT) region are the focus of the whitepaper, many of the analytical concepts presented could also apply to solar energy, and the framework is applicable in other market regions, subject to adjustments for features like capacity pricing.

“Due to the uncertain volume of production from a weather-dependent resource, it will be impossible to fully or perfectly hedge, especially over very short horizons,” notes C. Onur Aydin, a Brattle senior associate and co-author of the whitepaper. “However, the average output from a renewable resource over horizons of a year or longer is more predictable and can be hedged, and it is not risk-minimizing to simply sell this expected amount of output forward at a trading hub.”

The authors discuss how the volume of wind generation will generally have a negative correlation with spot market power prices, both because wind tends to blow more heavily at off-peak periods and when it blows more than expected, it also tends to depress prices (in areas where there is a significant renewable participation in the market). As a result, the average forward price for available electric hedges will likely be higher than the average spot price received by wind assets, and variances will not have symmetric price effects. (The extent of these effects will also vary seasonally.) Thus, the appropriate hedge ratio must be determined with consideration of several risk factors.

The Brattle whitepaper also discusses that standard gas forwards could also be used as hedges for wind output, provided there is a strong and persistent correlation between gas and spot electric prices, there are good seasonal estimates of the conversion from gas to electricity via expected market heat rates, and basis risk for gas delivery locations vs. power sales locations are taken into account. The authors note that these can all be managed, but they likely require a structural forecast of market conditions over a horizon of more than a few years, because the ongoing penetration of more renewables will itself change the gas-electric correlations over time.

The whitepaper, “Managing Price Risk for Merchant Renewable Investments: Role of Market Interactions and Dynamics on Effective Hedging Strategies,” is authored by Brattle Senior Associate C. Onur Aydin, and Principals Frank Graves and Bente Villadsen. It is available for download using the link below.

Associated Experts
Aydin 087
Senior Associate
Mr. Onur Aydin is a senior associate with an engineering background and over 10 years of experience in energy economics, electricity market modeling, and transmission planning. More icon f02782c24cccaf6d90e1da53920c42f20e5a8955f54ac2ca5727ec7dc89987b4