With the increasing integration of distributed photovoltaics, energy storage systems, electric vehicle chargers, and intelligent terminals, accurate identification of heterogeneous edge-end devices in distribution networks has become challenging due to their diverse operating characteristics and similar current signatures. This paper proposes an identification method based on current time–frequency features and Random Forest. Equivalent grid-connected current models are developed for five types of edge-end devices, considering different capacity levels, operating states, ripple characteristics, and transient behaviors. A 13-dimensional feature set is extracted from time-domain, frequency-domain, and time–frequency characteristics, covering 11 device subclasses. Feature analysis is conducted to evaluate the separability of the extracted features, and Random Forest is employed for multi-class device identification. The results show that the proposed method achieves an overall accuracy above 98% on independent test samples and 96.91% in the IEEE 33-bus validation case, demonstrating its effectiveness for distribution-network edge-end device identification.
The findings demonstrate that the proposed intelligent protection framework provides accurate and reliable fault detection, classification, and location through optimized DWT-based feature extraction and SVM-based decision making under the investigated simulation scenarios.
E. M. Shalby, A. Abdelaziz, Eman S. Ahmed et al.· Scientific Reports· 0 citations
As renewable energy resources continue to be deployed on a larger scale, integrating distributed generation into smart-grid environments has become an increasingly important aspect of modern power system development. This paper focuses on the major issues encountered during the grid connection of distributed energy res...
Jiayi Zhang· Applied and Computational En...· 0 citations
An edge computing-enabled optimal control method is proposed for low-voltage distribution networks organized as distribution transformer clusters (DTCs) that reduces overvoltage occurrences in TQ1 by 81.0% and eliminates undervoltage occurrences under four PV scenarios with SOP-based balancing.
The large-scale integration of inverter-interfaced renewable generation has made the steady-state short-circuit current of renewable energy stations increasingly important for setting protections, planning, and fault analysis. Traditional single-unit multiplication methods are computationally efficient but often ignore...
Jian Li, Bo Zhou, Yunyang Xu et al.· Electronics· 0 citations
A feature-distance-weighted dynamic localization algorithm is designed, incorporating a multi-node time-series coordination mechanism to update location results, which validates the effectiveness of frequency-energy feature analysis for distribution ground fault location.
Ke-Yu Yue, Yu Zheng, Zhi-Gang Wang et al.· European Conference on Elect...· 0 citations
In-depth analysis shows that the CEC-VVC architecture has reduced the system's Total Response Time from 609ms (TCC) down to a minimum of 121.8ms, achieving an 80% improvement and meeting the real-time response criteria and the sensitivity analysis proves the robustness of the architecture.
T. H. Tran· RA Journal Of Applied Resear...· 0 citations
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