Climate Change Strategies for Electric Utilities

Strategies electric utilities might use to adapt to climate change are explored with the aid of a Climate Change Information System for Business and Industry (ClimBiz) being developed as part of a Department of Energy Small Business Innovation Research (SBIR) initiative. The strategies are based on the climate change simulations prepared for the 2013 Fifth Assessment report of the Intergovernmental Panel on Climate Change (IPCC) and archived as part of the Climate Model Intercomparison Project 5 (CMIP5). Energy utilities and other climate sensitive activities can attempt to ensure resilience by examining a range of possible scenarios in formulating a long-range capital investment plan.

   We construct a generic mathematical model of an electric utility that includes the possibility of change in demand or load, change in the availability of solar and hydro power, and change in the cost of generation by renewables and fossil fuel sources. Fossil-fuel generation is used to meet demand after the contribution of renewable sources is determined. The target hypothetical utility expects to use an increasing fraction of renewable energy as the 21st century proceeds. The present study uses temperature to model customer demand, insolation for solar power, and precipitation as a proxy for flow volume for hydro power. ClimBiz is developing the capability to create actual flow volume scenarios from CMIP5 model results.

   The model produces 21st century scenarios for moderately severe climate change in which an assumed decrease in the cost of the renewable sources permits them to be used in increasing fractions to meet increasing demand at an overall decrease in the cost of generation.

   A probabilistic approach was also developed in order to obtain a broader perspective. Five fractions of both solar and hydro generation were selected, giving a total of 25 configurations. The 21st century was divided into five 20-year periods, thus giving a total of 125 cases. The time dependent distributions of the physical variables were modeled with the CMIP5 data and generation cost trends were modeled as with the earlier scenarios. Then 1000 cases were computed with the model for each of the 125 cases, giving reasonably stable estimates. The results are described with a plot of the expected generation expense versus the expected volatility (standard deviation) in the same manner that return is plotted against risk or volatility in analysis of investment performance. The sets of options for each double decade outline an efficient frontier indicating a minimum cost for a selected volatility or a minimum volatility for a selected expense.

The study demonstrates that utilities have a range of options to consider depending on the relative priorities assigned to various energy sources and to expected expense versus expected volatility. Thus they can take advantage of studies such as this one to develop a long-range capital investment strategy that will provide resilience to climate change.