Deadline for Submissions: 25 February 2024
Special Issue Editors
Dr. V. B Murali Krishna
National Institute of Technology Andhra Pradesh, India.
Dr. Rajesh Cheruku
Dayananda Sagar University, Devarakaggalahalli, India.
Dr. Abdul Wahid
University of Galway, Ireland
Dr. Bhanu Pratap Soni
Fiji National University, Fiji Islands
Special Issue Information
Renewable energy sources such as solar, wind, and hydro power offer tremendous potential to meet the world's growing energy demands while reducing carbon emissions. However, the inherent variability and intermittency of these sources pose intricate control problems. Traditional control approaches struggle to cope with the complexities arising from uncertain environmental conditions, load fluctuations, and the nonlinear dynamics of renewable energy systems. Furthermore, the increasing adoption of distributed energy resources and the emergence of smart grids demand adaptive and intelligent control solutions that can enhance the stability and resilience of the energy infrastructure. In this context, the integration of applied mathematics, machine learning (ML), Artificial Intelligence (AI), and image processing offers a promising avenue to overcome these challenges. By leveraging mathematical models, optimization techniques, ML algorithms, and AI techniques, we can develop controllers that are capable of learning from data, adapting to changing conditions, and optimizing performance in real-time. Image processing technologies further contribute by enabling accurate monitoring, fault detection, and condition assessment of renewable energy installations, thereby ensuring their optimal operation and maintenance.
This special issue entitled, “Applied Mathematics for Design of Controllers for Renewable Energy Applications” focuses on the convergence of applied mathematics, machine learning, artificial intelligence (AI), and image processing to address the critical challenges in designing effective controllers for renewable energy applications. This special issue aims to bridge the gap between mathematical modelling, computing technologies, complex analysis, industrial mathematics, computational mathematics, applied mathematics, advanced control techniques, and modern AI-driven methodologies, ultimately contributing to the efficient and reliable design of controllers for renewable energy application.
We invite submissions of high-quality papers on a wide range of topics including but not limited to the following topics:
This special issue is now open for submission.
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