This paper investigates the impact of humidity on summer electricity demand prediction in the United States. The authors find that using air temperature alone underestimates cooling demand in many high-energy-consuming states, such as California and Texas, by as much as 10-15%. They demonstrate that near-surface humidity is a crucial factor in accurately modeling cooling load and should be included in predictive models.
Publisher
Nature Communications
Published On
Apr 03, 2020
Authors
Debora Maia-Silva, Rohini Kumar, Roshanak Nateghi
Tags
humidity
electricity demand
summer
cooling load
predictive models
temperature
energy consumption
Related Publications
Explore these studies to deepen your understanding of the subject.
