Aims & Scope
The Journal of AI-Driven Renewable Energy Systems (JADRES) is an international, peer-reviewed journal that focuses on the application of artificial intelligence in renewable energy systems, modern power systems, power electronics, and energy-related electromechanical and thermal systems.
The journal aims to publish high-quality, original research that advances the development of intelligent, efficient, and sustainable energy systems. It provides a global platform for researchers, academics, and industry professionals to present innovative solutions, emerging technologies, and data-driven methodologies in AI-driven energy applications.
JADRES covers a broad range of topics including, but not limited to:
- Artificial intelligence in power system analysis, operation, and control
- AI-based control and optimization of power electronic converters
- Smart grids and digital energy systems
- Renewable energy integration, forecasting, and optimization
- Microgrids and distributed energy resources (DERs)
- Electric vehicles, vehicle-to-grid (V2G), and smart charging systems
- Power quality monitoring, mitigation, and enhancement
- Data-driven modeling, estimation, and predictive control
- Machine learning and deep learning applications in energy systems
- Intelligent protection, fault detection, and diagnostics
- Energy management systems and advanced optimization techniques
- AI applications in electromechanical energy systems (motors, drives, generators)
- Thermal and mechanical aspects of renewable energy systems
- Wind energy systems, turbine modeling, and control
- AI-based optimization of thermal systems and energy conversion processes
The journal welcomes original research articles, review papers, and short communications that contribute to the advancement of intelligent, resilient, and sustainable energy systems, including interdisciplinary research bridging electrical, mechanical, and energy engineering domains.
