Research Article
Digital-twin and Physics-informed Neural Ensemble for Locating Asymmetrical Short-circuit Faults on 10 kV Overhead Feeders
Ramziddin Maxamatxodjayev Xasan o‘g‘li*
,
Nurmatov Obid Yoqubboyevich
Issue:
Volume 15, Issue 5, October 2026
Pages:
103-114
Received:
27 August 2026
Accepted:
4 September 2026
Published:
22 September 2026
Abstract: This paper proposes a digital-twin-assisted, physics-informed (feature-enriched) ensemble for locating asymmetrical short-circuit faults on a 10 kV radial overhead feeder using single-ended current and voltage measurements. The digital twin randomizes feeder sequence impedances, source impedance, loading, fault location, fault resistance, and measurement error to generate 6,000 operating scenarios. Observable fault cases are selected using an explicit current-based criterion, after which a data-only multilayer perceptron, a physics-informed multilayer perceptron, Random Forest, Gradient Boosting, and HistGradientBoosting are evaluated on an independent test subset. A weighted ensemble, 0.4 MLP + 0.6 HGB, achieves a mean absolute error of 0.962 km, an RMSE of 1.316 km, and an R2 of 0.948, reducing MAE by approximately 25% relative to the data-only MLP. Error distributions are further analyzed with respect to fault resistance, measurement noise, observability, and uncertainty. The proposed model is not intended to replace deterministic protection; instead, it operates as a confidence-gated advisory layer that narrows the patrol segment and abstains under unreliable conditions. An IEC 61850-compatible deployment architecture, cybersecurity controls, a TRL 3-7 validation roadmap, and the remaining requirements for HIL, COMTRADE, and seasonal field validation are also presented.
Abstract: This paper proposes a digital-twin-assisted, physics-informed (feature-enriched) ensemble for locating asymmetrical short-circuit faults on a 10 kV radial overhead feeder using single-ended current and voltage measurements. The digital twin randomizes feeder sequence impedances, source impedance, loading, fault location, fault resistance, and measu...
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Research Article
Comprehensive Monitoring and Intelligent Diagnostics Using Multifactor Assessment of Corona Losses to Improve Energy Efficiency in High-voltage Overhead Transmission Lines
Tovbayev Akram Nurmonovich*,
Tog‘ayev Islom Bekpo‘lat o‘g‘li
Issue:
Volume 15, Issue 5, October 2026
Pages:
115-120
Received:
2 October 2026
Accepted:
12 October 2026
Published:
31 October 2026
DOI:
10.11648/j.epes.20261505.12
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Views:
Abstract: This paper investigates the monitoring and mitigation of electrical energy losses caused by corona discharge in high-voltage overhead transmission lines. The relevance of the study is associated with the growing need to improve the energy efficiency of power networks, reduce technical losses, and ensure the reliable operation of power supply systems under increasing electrical loads and more complex operating conditions. A detailed analysis of the factors affecting corona discharge intensity is carried out, including operating voltage levels, conductor design characteristics, surface conditions, meteorological influences, and environmental parameters. A comprehensive approach to continuous corona monitoring is proposed based on the integrated utilization of electrical, electromagnetic, and meteorological data. The potential of modern digital technologies for real-time condition assessment of overhead transmission lines and forecasting of energy losses is examined. The impact of corona discharge on power transmission efficiency is evaluated, and key directions for loss reduction through improvements in transmission line design and operational practices are identified. The obtained results demonstrate that the implementation of continuous monitoring systems enables the timely detection of network sections characterized by increased corona activity, improves the accuracy of energy loss assessment, and supports the development of effective technical measures for loss reduction. The practical significance of the research lies in the applicability of the proposed approach to the modernization of high-voltage power networks aimed at enhancing energy efficiency, operational reliability, and the overall performance of electric power infrastructure.
Abstract: This paper investigates the monitoring and mitigation of electrical energy losses caused by corona discharge in high-voltage overhead transmission lines. The relevance of the study is associated with the growing need to improve the energy efficiency of power networks, reduce technical losses, and ensure the reliable operation of power supply system...
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Research Article
Improving the Electrical Energy Efficiency of a Cone Crusher in the Ore Crushing Process Through Adaptive Adjustment of Supply Frequency
Olimov Jasurjon Sadriddin Ugli*
Issue:
Volume 15, Issue 5, October 2026
Pages:
121-129
Received:
12 October 2026
Accepted:
21 October 2026
Published:
31 October 2026
DOI:
10.11648/j.epes.20261505.13
Downloads:
Views:
Abstract: Cone crushers in the mining and metallurgical industries operate under conditions where ore properties and throughput constantly fluctuate, yet many industrial electric drives are still controlled at a fixed nominal frequency. This study developed an adaptive frequency control system that treats the supply frequency (f) of a variable frequency drive (VFD) as the control variable, while accounting for external factors such as ore hardness (H) and mass flow rate (Q) measured via a belt scale. The objective of the research is to minimize the crusher’s specific electrical energy consumption (SEC = P/Q) while adhering to constraints regarding frequency, electric motor power, throughput, and product size. The study integrates the speed-frequency relationship of the induction motor, the crusher's electrical energy consumption, hardness and load factors, and a function representing the deviation from the optimal operating point for current conditions. Thirty planned experimental trials—covering ranges of H = 7–15, Q = 1900–2300 t/h, and f = 45–60 Hz—were compared against a standard 50 Hz operating mode. Adaptive modeling reduced the SEC by an average of 5.57% while maintaining throughput. The proposed approach aligns with existing preliminary scientific findings indicating that adjusting eccentric speed and utilizing mass flow feedback can enhance cone crusher efficiency; furthermore, the 30 experimental modeling results presented were validated against production-scale metrics and criteria prior to industrial implementation. Our research paper details the governing equations, the practical control architecture, and the experimental protocol dataset.
Abstract: Cone crushers in the mining and metallurgical industries operate under conditions where ore properties and throughput constantly fluctuate, yet many industrial electric drives are still controlled at a fixed nominal frequency. This study developed an adaptive frequency control system that treats the supply frequency (f) of a variable frequency driv...
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