Eastern-European Journal of Enterprise Technologies | 2026
Authors: Kuanyshtaeva A.; Kotov Y.; Smagulova K.; Abilzhanova F.
DOI: 10.15587/1729-4061.2026.352513
Journal: Eastern-European Journal of Enterprise Technologies
Year: 2026
Publisher: Technology Center
Document Type: Article
Open Access: All Open Access; Gold Open Access; Green Open Access
Cited by: 0
The object of the study is the power supply system of the mining enterprise NovaZinc LLP, located in Central region of Republic of Kazakhstan, which specializes in the extraction and enrichment of leadzinc ores. Reliable power supply in mining is challenged by heavy mechanical loads, vibration, and severe weather; this case study is used only as an example of conditions common in many mining regions worldwide. This study proposes a diagnostic-and-forecasting method for distribution power systems based on routinely available operational records and climatic indicators. The method was tested using outage data from 2020–2024. Using least squares, a multivariate regression model was obtained for feeder emergency outage duration as a function of cable damage (F5), transformer failure (F6), and the climatic factor (Climate). The model is significant overall (Ftest p < 0.01) and explains 68.7% of downtime variation (R2 = 0.687); residual diagnostics indicate normality and no autocorrelation. The average marginal effects are 7.561 h for cable failures, 3.314 h for transformer failures, and 2.418 h for climatic impacts, highlighting cables as the dominant driver of prolonged outages. To assess energy performance, a separate model was built for the loss share in the power system as a function of outage duration, phase clashing (F3), and Climate. This loss model has low explanatory power (R2 = 0.2013) and nonsignificant factor coefficients (p > 0.05). Finally, bivariate regressions show that Climate strongly affects phase clashing (F3) (R2 = 0.793) and moderately affects ground faults (F1) and insulator chipping (F2) (R2 = 0.533 each). The proposed method supports maintenance prioritization, climatemitigation measures, and continuous updating as new outage records are added, strengthening decisionmaking and system robustness Copyright © 2026, Authors.
diagnostics; failure prediction; mining enterprise; power supply; regression analysis; reliability