Asymmetrical response of California electricity demand to summer-time temperature variation

Abstract

Current projections of the climate-sensitive portion of residential electricity demand are based on estimating the temperature response of the mean of the demand distribution. In this work, we show that there is significant asymmetry in the summertime temperature response of electricity demand in the state of California, with high-intensity demand demonstrating a greater sensitivity to temperature increases. The greater climate sensitivity of high-intensity demand is found not only in the observed data, but also in the projections in the near future (2021-2040) and far future periods (2081-2099), and across all (three) utility service regions in California. We illustrate that disregarding the asymmetrical climate sensitivity of demand can lead to underestimating high-intensity demand in a given period by 37-43%. Moreover, the discrepancy in the projected increase in the climate-sensitive portion of demand based on the 50th versus 90th quantile estimates could range from 18 to 40% over the next 20 years. Electricity demand is influenced by many factors, including socio-demographic characteristics 4 , technology 5 , markets 6 , and climate 7-9. Here, we focus on understanding the climate sensitivity of residential electricity demand, which is a critical factor in ensuring the resilient operation of the grid under climate change 1-3. Recent work has isolated the effect of climate variability and change on both peak load (i.e., the highest load in a given time period) and total electricity consumption, indicating climate change will lead to greater electricity use, particularly in the residential sector 2,10-16. This has significant implications as unanticipated increases in cooling demand in the residential sector during heat waves (i.e., periods with sustained positive temperature anomalies) can lead to unexpected supply shortages 17 , distorted electricity market prices 18,19 , as well as increased morbidity and mortality 20 , particularly in vulnerable populations and disadvantaged communities 21. To minimize the economic and social costs of interrupted electricity service, researchers forecast the climatesensitive portion of residential electricity demand during extreme temperatures by harnessing methodologies from various fields, including econometrics 4,22,23 , engineering 23,24 , statistics and machine learning 13,15. However, the existing body of literature has primarily focused on modeling the temperature response of the central tendency (i.e., mean/median) of the demand distribution, as opposed to considering its entire distribution 2,25-27. We hypothesize that projections solely based on the mean/median values of the load distribution underestimate the climate sensitivity of high-intensity demand. Our central hypothesis is that while projections of the climate-demand nexus based on the mean/median values of demand distributions help to characterize the general trends in electricity use over time, they are likely inadequate in characterizing the climate sensitivity of the upper extremes of demand which are...

Implications of Increasing Household Air Conditioning Use Across the United States Under a Warming Climate

“…While the household‐days metric is estimated for the average household in different domains, the burden will not be equally felt across all households. Previous work has shown that low income households bear the brunt of extreme heat events within cities (Khosla et al., 2020; Sanchez‐Guevara et al., 2019), making them more vulnerable to climate‐induced temperature increases and subsequent electricity outages and blackouts (Khosla et al., 2020; Kumar et al., 2020). This higher vulnerability arises often due to a number of factors—from inferior housing structures and residing in areas with higher urban heat island effects to the inability to afford increasing electricity bills (Drehobl & Ross, 2016; Graff & Carley, 2020; Sánchez‐Guevara et al., 2017, 2019).…”

“…The first of which is the use of domain‐wide mean values within the climate data. There has been previous work using population‐weighted climate data to model electricity consumption (Kumar et al., 2020; Maia‐Silva et al., 2020). However, given that the household air conditioning use data were obtained as domain‐wide means, we opted to maintain a similar structure in the climate data.…”

“…Finally, Kumar et al. (2020) evaluated the impact of climate change on summer peak load across California. While peak load is a critical metric for managing the electric grid, understanding the climate change impacts at a larger time scale might be more beneficial for long‐term planning.…”

“…This is the first study, to our knowledge, that leverages publicly available datasets to evaluate and predict air conditioning use at the household level under future climate change scenarios, while also adopting a large spatial extent. Moreover, while previous work has focused on annual electricity consumption (Deschênes & Greenstone, 2011) or daily peak load (Auffhammer et al., 2017; Franco & Sanstad, 2008; Kumar et al., 2020; Wenz et al., 2017), the present study focuses on the summer‐time air conditioning use as a whole. Finally, we provide information on the shifts in air conditioning demand after two key warming thresholds‐1.5 and 2.0°C above pre‐industrial levels.…”

Energy and GHG Emissions Aspects of the COVID Impact in Greece

“…As the electricity demand depends on temperature, a correction needs to be applied to make comparisons meaningful. To this effect, the temperature dependence of the load is derived from multi-annual periods and for specific areas [12,13]. For the mainland grid, such a dependence [14] was updated recently [15] based on data for the 13-year 2006-2018 period, as illustrated in Figure 1, and has been utilized in this analysis.…”