Author

V. Bereznychenko

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Conference Sep 2026

Photovoltaic Fault Detection Using I-V Curve Analysis Coupled with Artificial Intelligence Methods

Fault diagnosis in photovoltaic (PV) systems is essential for ensuring reliable operation and maximizing energy yield. This paper presents an intelligent PV fault diagnosis framework based on real-time current-voltage (I-V) curve analysis and machine learning techniques. A monitoring device employing a DC/DC buck-boost...

A. Bebboukha, C. Labiod, R. Meneceur et al. · Automation, Control, and Inf... · 0 citations

Open access Jul 2026

Hybrid temporal deep learning and ensemble regression framework for remaining useful life prediction of lithium-ion batteries in energy storage systems

A hybrid data-driven framework integrating a Temporal Convolutional Network, Bidirectional Long Short-Term Memory, and Extreme Gradient Boosting for accurate LIB RUL prediction provides a robust and computationally efficient solution for intelligent battery health monitoring, predictive maintenance, and smart battery m...

T. Mariprasath, Kumaresh S. S., Seif Al Bustanji et al. · Energy Exploration & Exp... · 0 citations

Open access Aug 2026

A physics-constrained temporal modeling framework for robust short-term wind power forecasting

The integration of physics-guided constraints with the temporal convolutional architecture significantly enhances prediction accuracy, stability, and generalization capability, making it suitable for real-time wind energy forecasting applications, intelligent energy management systems, and microgrid power system operat...

S. Marisargunam, T. Mariprasath, Mohit Bajaj et al. · Energy Exploration & Exp... · 1 citation