Non-Negative K-SVD as an element of the forecasting electricity demand system

The article describes the NN-K-SVD method based on the use of sparse coding and the singular value decomposition to specific values. An example of using the method is the compression of load profiles. The experiment of compression of 125022 power load profiles has been carried out with the use of re...

Full description

Saved in:
Bibliographic Details
Published inE3S Web of Conferences Vol. 84; p. 1003
Main Author Drechny, Marcin
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 01.01.2019
Subjects
Algorithms
Compression
Economic forecasting
Electric power demand
Electricity consumption
Forecasting
Households
Scaling factors
Singular value decomposition
Online AccessGet full text

Cover

More Information
Summary:The article describes the NN-K-SVD method based on the use of sparse coding and the singular value decomposition to specific values. An example of using the method is the compression of load profiles. The experiment of compression of 125022 power load profiles has been carried out with the use of registered profiles in households and small offices. Two matrices: patterns (atoms) and scaling factors are the result of the discussed algorithm. Features of the created matrices, which can be used in the creation of fast power demand forecasting systems, have been characterized.
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/20198401003