Cutting-Edge Developments and Innovations in Renewable Energy System Modeling and Control
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".
Deadline for manuscript submissions: closed (21 August 2024) | Viewed by 1377
Special Issue Editors
Interests: artificial intelligence of things (AIoT); digital twin; machine learning; virtual power plant; energy optimization
Interests: artificial intelligence; robotics; data analysis; machine learning; reinforcement; renewable energy
Special Issue Information
Dear Colleagues,
This Special Issue explores key aspects of designing, modeling, and controlling renewable energy systems. The main content is composed of five areas:
- Understanding Renewable Energy Systems: It is essential to understand the characteristics of various renewable energy systems.
- Modeling Renewable Energy Systems: Mathematical and simulation models are utilized to predict the behavior and performance of these systems.
- Renewable Energy System Control Techniques: Various control strategies and methods are applied to maximize efficiency and output in renewable energy systems.
- Integration of Renewable Energy Systems: The focus is on how to integrate various systems for a consistent power supply.
- Current Challenges and Future Directions: This issue examines challenges in technical, economic, and societal aspects and explores future trends and emerging technologies in the renewable energy field.
This Special Issue aims to provide a comprehensive understanding of renewable energy system modeling and control. It offers valuable insights, solutions, and future directions for researchers, academics, engineers, and policymakers in the energy sector.
Prof. Dr. Chang Gyoon Lim
Dr. Jun Jo
Dr. Dong-Ok Kim
Guest Editors
Manuscript Submission Information
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Keywords
- renewable energy systems
- system modeling
- simulation models
- energy system control techniques
- predictive control
- optimization techniques
- real-time control
- virtual power plant
- system stability
- microgrids
- energy management
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