Multi-Criteria Strategic Planning for Climate Risk and Adaptation in the Electric Power Industry

All components of the electric power industry face complex issues created by climate change, advancing renewable energy technology, and evolving patterns of demand. Decisions and strategies about climate change and the response of the enterprise must be broad and consider both direct and intangible effects on operational and financial performance, on internal and external stakeholders, and on the community and the environment itself.

Effective long-term strategic and capital expenditure plans thus require an integrated analysis involving three critical elements:

• Probabilistic scenarios of the likely change of relevant environmental variables derived from supercomputer simulations of the 21^st century climate;
• A mathematical and numerical model of the electric power system that produces quantitative operational and financial projections of the consequences of climate change, technology advance, and other forces;
• A method for taking account of multiple criteria derived from a variety of corporate and community values and goals.

Multi-criteria strategic climate change planning in the electric power industry is thus a big data problem with a number of dimensions.

The supercomputer climate change simulations prepared by a wide range of national and international centers for the Coupled Model Intercomparison Project (most recently CMIP5 and CMIP6) of the World Climate Research Program (WCRP) provide a very large dataset with which to construct probabilistic scenarios for mild, moderate, and severe climate change projections. Using model anomalies relative to a simulated first decade reduces scatter, increases confidence, and allows results to be scaled to present conditions.

A numerical model of the electricity generation process and its costs integrates and illustrates the 21^st century consequences of the change in customer demand, of possible environmental policy requirements, and of the evolution of the generation fractions and cost of both renewable and fossil sources of energy. The model quantifies the interactions of changing climates and the increasing fractions of renewable energy sources as their costs continue to decrease.

The wide ranges of possible climate scenarios, changes in demand, and generation energy source configurations with varying cost patterns produce an extended set of possible 21^st century options for utilities. A multi-criteria decision system then applies corporate values to select the most appropriate options, focusing on profitability, reliability, and responsibility as an illustration. This process is demonstrated with a model of PJM, the electricity balancing network of the northeastern United States, that summarizes the experience of a range of generation facilities.

This example illuminates the critical components of effective long-range planning and risk management. First, we must have suitable environmental and technological scenarios for some future time and then we must have a financial or business model that reveals the consequences of various actions and events quantitatively in user terms. Often the plots of financial return or cost versus their volatility are a key statistical output of the modeling process. These demonstrate for the long-term planners the quantitative consequences of the various options for attempting to meet the expectations of the corporate and community values.

Acknowledgment

ClimBiz Ltd research reported here was supported by the U.S. Department of Energy with award DE-SC0011284.