APPLICATION OF SINGULAR SPECTRUM ANALYSIS FOR DETERMINING THE TIMING AND MAGNITUDE OF EXCESSIVE ELECTRICITY CONSUMPTION

• Datum: 2026
• Hauptverfasser: Kaurkin, Yevgen, Karpaliuk, Ihor
• Format: Artikel
• Sprache: Ukrainisch
• Veröffentlicht: General Energy Institute of the National Academy of Sciences of Ukraine 2026
• Schlagworte: voltage sags; excessive consumption; time series; singular spectrum analysis; thermal energy; interdependence of energy forms.
• Online Zugang: https://systemre.org/index.php/journal/article/view/956
• Назва журналу: System Research in Energy

One of the problems of the power system of Ukraine is the high level of electrical energy losses, which have various causes, one of which is the deterioration of power quality. The article considers the overloading of network sections that leads to a decline in electrical energy quality. The causes of excessive electricity consumption under conditions of insufficient heat supply and its impact on the operating modes of electrical networks are investigated. The interrelation between electrical and thermal energy consumption is substantiated, as well as the necessity of analyzing their time dependencies to detect disturbances in operating conditions. The aim of the study is to develop a method for detecting regimes of excessive electricity consumption arising from insufficient heat supply, which lead to the deterioration of power quality indicators and increased losses. Methodology – singular spectrum analysis of time series of electricity consumption and heat supply is applied using a procedure for detecting structural changes (regime shifts) based on the analysis of the spectrum of eigenvalues and eigentriples. The study is conducted using real data from a residential area over a one-year period. Results – the dependence of electricity consumption on ambient temperature and heat supply volumes is established; structural components corresponding to seasonal and operational factors are identified; the possibility of identifying moments of excessive consumption through the analysis of residual components of the time series is demonstrated. The proposed approach makes it possible to determine the parameters of excessive electricity consumption and to estimate the required level of heat supply for its reduction, thereby providing a basis for improving power quality and reducing losses.