Determining the Required Return on Equity (ROE) Value for Regulated Electric Utilities: Challenges and Opportunities for Designing Regulatory Decision Support Tools
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2013-04-26
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Public utility commissions (PUCs) across the country face challenging decisions as regulated electric utilities adapt to the opportunities and risks within the new energy landscape. The natural gas boom, the need for replacement of aging infrastructure, and the threat of potential environmental regulations have brought the energy future of the United States to a crossroads. Consequently, PUCs have seen an increase in the number of rate cases filed by electric utilities to recover capital and operating costs of new and existing electric generation infrastructure. In general, rates are approved or adjusted based on a “cost-plus method,” which is comprised of a utility’s operating costs and capital investments plus a risk-adjusted profit margin, also referred to as the return on equity (ROE). Determining the required ROE for an electric utility is the most contentious and difficult component of a rate case due to its highly subjective and variable inputs. PUCs are responsible to approve an ROE that corresponds to a utility’s level of risk, so that it can attract the capital needed to ensure safe and reliable service at reasonable costs for consumers. As utilities and consumer advocates present arguments for different ROE values, PUC decision making becomes extremely challenging. This study analyzes the major challenges in estimating ROEs through a case study of the Duke Energy Carolinas rate cases from February 2013 and July 2011. This analysis identifies the objective and subjective components of a required ROE determination and highlights the need for setting standards and developing decision support tools to enhance the transparency and efficiency of PUCs decision making process regarding this contentious issue.
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Ketchum, Whitney, and Jenny Kim (2013). Determining the Required Return on Equity (ROE) Value for Regulated Electric Utilities: Challenges and Opportunities for Designing Regulatory Decision Support Tools. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/6863.
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