Assessing the Hedging Value of Wind Against Natural Gas Price Volatility

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2014-04-25

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Abstract

In recent years, natural gas prices in the U.S. have reached historic lows and utilities have been rapidly replacing coal with gas-fired generation. Natural gas prices are historically volatile, and overreliance on natural gas can lead to high electricity prices in the event of rising fuel costs or price spikes. We examine how utilities can use wind energy from long-term power purchase agreements (PPAs) as a tool to hedge against natural gas price volatility and future environmental regulations. We assess how federal and state policies affect wind’s hedging value, and provide a case study on how utilities in the Southeast are increasingly importing wind from high capacity regions.

We quantify wind’s hedging value by comparing the net present value (NPV) of investment costs for a natural gas combined cycle plant with and without wind generation to meet future demand under uncertainty. We use wind prices from the Lawrence Berkeley National Laboratory national wind PPA sample, and analyze six investment options over a 30-year period using the U.S. Energy Information Administration’s (EIA) AEO 2013 natural gas price scenarios with and without carbon tax, and our own scenarios created using Monte Carlo simulation and Random Walk.

Assuming a least-cost framework, we find that the utility would only invest in gas generation under the EIA reference scenario. In our model, the utility will have an NPV cost band from $4.7 to $10.1 billion if they do not hedge with wind, whereas if they add 20% wind to their portfolio, the maximum cost will decrease by $774 million if the worst-case gas price scenario were to occur. By procuring wind energy at fixed prices through long-term PPAs, utilities can reduce their exposure to unfavorable cost outcomes, particularly if a carbon tax of $10 per ton or more is enacted.

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Inda, Ada, Jill Wu and Dan Zhou (2014). Assessing the Hedging Value of Wind Against Natural Gas Price Volatility. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/8582.


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