What type of study is this?

This is a Quantitative Study study.

November 4, 2025International Journal of ClimatologyOpen Access

Exploring the Efficacy of Multivariate Air Masses as a Predictor of Electricity Demand: A Case Study in the Northeastern United States

View Full Paper

Ask AI

Bookmark

Authors

CLCameron C. LeeKent State University ESErik T. SmithElectric Power Research Institute

Discussion

Member takes

Implication

Observational analysis identified thermal comfort and air masses as significant predictors of electricity demand, indicating potential for enhanced demand modeling.

Key Points

Electricity demand modeling shows high accuracy in predicting demand based on air masses and thermal comfort.
The study highlights a 94% explanation of variability in electricity demand using air mass data.
Analysis indicates significantly higher electricity demand spikes during humid-warm and dry-cool air mass conditions.
Future research should expand to include various geographic regions and advanced modeling techniques.

Cite This Study

Lee et al. (2025) studied this question.

synapsesocial.com/papers/690945348f2297dc13532f52 https://doi.org/10.1002/joc.70170

View Full Paper

Ask AI

Bookmark

Implication

Observational analysis identified thermal comfort and air masses as significant predictors of electricity demand, indicating potential for enhanced demand modeling.

Exploring the Efficacy of Multivariate Air Masses as a Predictor of Electricity Demand: A Case Study in the Northeastern United States

Discussion

Member takes

Implication

Key Points

Cite This Study

Exploring the Efficacy of Multivariate Air Masses as a Predictor of Electricity Demand: A Case Study in the Northeastern United States

Discussion

Member takes

Implication

Key Points

Cite This Study

Also Consider

Also Consider