Track: A1. Investing in Climate Resilient Infrastructure

Background/Objectives

Electricity demand in the California Independent System Operator (CAISO) region is largely driven by temperature, reaching peak values on warm summer afternoons as a result of residential cooling. As heat waves are expected to become more frequent and extreme in the future, it is necessary to incorporate such climatic changes into capacity expansion models. Population growth may further exacerbate climate-driven demand changes if large centers of population increase coincide with areas that experience the most warming.

Approach/Activities

In this work, we use historical data to explore the impact of temperature and population on hourly electricity demand in California. We aim to constrain the relationship between population-weighted temperature and demand in different regions in order to estimate how future climate change and population growth may impact spatio-temporal changes of energy load in California. Using available data from future climate projections, we explore how future temperature changes may impact electricity load curves under a range of assumptions.

Results/Lessons Learned

A major challenge facing analyses such as ours is the need for high spatial and temporal resolution climate datasets, both present and future, necessary for this work. Future policy changes, such as increased electrification, present an additional source of uncertainty for estimating future electricity demand.