Active and Reactive Power Load Profiling Using Dimensionality Reduction Techniques and Clustering
Abstract
This paper proposes a methodology to characterize active and reactive power load profiles. Specifically, the approach makes use of fast Fourier Transform for conversion into frequency domain, principle component analysis to reduce the dimension and K-means++ to determine the representative load profiles. The data set consists of five-year measurements taken from the Democritus University of Thrace Campus. Test days were also classified as working and non-working. From the results it is observed that the proposed methodology determines representative load profiles effectively both regarding active and reactive power.
Source
2019 54th International Universities Power Engineering Conference, UPEC 2019 - ProceedingsVolume
September 2019Collections
Keywords
clusteringelectricity load profiles
frequency domain
principal component analysis
reactive power
real power