Managing Financial Risk Trade‐Offs for Hydropower Generation Using Snowpack‐Based Index Contracts

Abstract

Hydrologic variability poses an important source of financial risk for hydropower-reliant electric utilities, particularly in snow-dominated regions. Drought-related reductions in hydropower production can lead to decreased electricity sales or increased procurement costs to meet firm contractual obligations. This research contributes a methodology for characterizing the trade-offs between cash flows and debt burden for alternative financial risk management portfolios, and applies it to a hydropower producer in the Sierra Nevada mountains (San Francisco Public Utilities Commission). A newly designed financial contract, based on a snow water equivalent depth (SWE) index, provides payouts to hydropower producers in dry years in return for the producers making payments in wet years. This contract, called a capped contract for differences (CFD), is found to significantly reduce cash flow volatility and is considered within a broader risk management portfolio that also includes reserve funds and debt issuance. Our results show that solutions relying primarily on a reserve fund can manage risk at low cost but may require a utility to take on significant debt during severe droughts. More risk-averse utilities with less access to debt should combine a reserve fund with the proposed CFD instrument in order to better manage the financial losses associated with extreme droughts. Our results show that the optimal risk management strategies and resulting outcomes are strongly influenced by the utility's fixed cost burden and by CFD pricing, while interest rates are found to be less important. These results are broadly transferable to hydropower systems in snow-dominated regions facing significant revenue volatility.

From Stream Flows to Cash Flows: Leveraging Evolutionary Multi‐Objective Direct Policy Search to Manage Hydrologic Financial Risks

“…These first two objectives, adopted from Hamilton et al (2020), are representative of the risk/return tradeoff analysis that is common in financial applications (Hull, 2009;Markowitz, 1952). However, financial researchers have found that higher-dimensional problem framings can more accurately represent managers' behavior in the empirical data (Spronk et al, 2005;Zopounidis et al, 2015).…”

“…Synthetic records are found to closely match the historical record in terms of statistical properties, while providing a much wider sampling of extremes. The impact of non-stationarity on policy performance and robustness is further discussed in Section 5.4, and the reader is referred to Hamilton et al (2020) for further details on the stochastic generator.…”

“…The CFD (Figure S3 in Supporting Information S1) provides payouts to the utility in low-SWE years (below 24.7 inches), when it expects to have low hydropower and thus low revenue, in return for the utility making payments in high-SWE years (above 24.7 inches), when the utility expects to have abundant hydropower and surplus revenue. The negative correlation between hydropower revenue and CFD payout has been found to significantly reduce the volatility of the combined cash flow, suggesting its value as a financial risk management tool (Hamilton et al, 2020). The second risk management tool is a reserve fund, into which the utility can deposit surplus cash flows.…”

“…, as chosen by the control policy at the end of the previous year (Section 3.1). The reader is referred to Hamilton et al (2020) for more details on construction of the CFD.…”

“…For both problems, the feasible solution space is restricted to solutions satisfying the sustainable debt constraint (Equation 28). The two-objective problem is the same as that used by Hamilton et al (2020), allowing for a direct comparison, while the four-objective problem provides more nuanced insight into risk management tradeoffs.…”