Weather impacts on electric power load: Partial phase synchronization analysis

Jinkyu Hong, Won Sup Kim

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Electricity demand is influenced by atmospheric conditions, and, therefore it is important to quantify their relationships suitably for accurate electricity demand forecasting and the implementation of power-saving policies. However, interdependencies and characteristics of covariance among meteorological variables within the same periodicities hinder the quantification of their direct and indirect impacts on electric power load. To investigate the strength of the direct correlation between atmospheric conditions and electric power load, this study harnessed a new partialization analysis method based on a partial phase synchronization index combined with wavelet transformation. The advantage of the proposed method is that it can be used to evaluate the degree of independent contribution of the variables over different spatiotemporal scales. Compared with traditional statistical analyses, this new partialization analysis shows that air temperature is the principal variable associated directly with electricity demand, but that the strength of the relationship varies with season and time scale. Relative humidity and wind speed have strong direct correlations with electricity in summer and winter, respectively. Insolation is directly coupled to the electric power load only on sub-diurnal time scales. This investigation indicates that for accurate forecasting of electricity demand, changes in the coupling strengths of different atmospheric variables should be incorporated into the electric power load forecasting process. The study shows that a partial phase synchronization index, combined with wavelet transformation, is a useful tool that could be used in other studies to assess complex interacting atmospheric oscillations that cannot be assessed properly by traditional approaches.

Original languageEnglish
Pages (from-to)811-816
Number of pages6
JournalMeteorological Applications
Volume22
Issue number4
DOIs
Publication statusPublished - 2015 Oct

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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