Open AccessApplication of the information uncertainty measure when comparing planned and actual commercial losses of electricity
Author(s) -
N. V. Dulesova,
А. С. Дулесов,
D. J. Karandeev,
A. V. Malykhina
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/862/6/062019
Subject(s) - divergence (linguistics) , measure (data warehouse) , kullback–leibler divergence , electricity , entropy (arrow of time) , computer science , information theory , electric power , value (mathematics) , power (physics) , data mining , statistics , mathematics , engineering , artificial intelligence , electrical engineering , physics , machine learning , philosophy , linguistics , quantum mechanics
The paper considers methods for processing data on commercial losses in electric networks with subsequent analysis of the obtained results. The information processing tools included methods for determining the amount of divergence of electric power losses when comparing planned and actual data. Comparing the planned and actual values of electric power losses, a method is proposed that in the classical theory of information is called “Kullback-Leibler divergence”. The rationale for its use is based on the possibility of applying a measure of information uncertainty, where information entropy is taken as a measured value. Comparing the planned and actual values of electric power losses, discrepancies between these distributions are obtained based on the application of the Kullback-Leibler model. The obtained results not only confirmed the importance of the applicability of this method of information processing, but also allowed us to draw attention to the adequacy of the planned losses to the actual ones.