Applications of Advanced Control and Optimization Paradigms in Renewable Energy Systems

Dear Colleagues,

To achieve net-zero carbon emissions worldwide by 2050, energy transition from traditional power generation towards clean, flexible, and affordable renewable power generation is needed instantly. However, there are many technical issues in deploying renewable power generation. The highly variable, non-controllable, and stochastic nature of renewable energy generation creates power quality, stability concerns, and inconsistency in power systems. Using proper control and optimization methods would yield superior power quality and stability within the standard parameters imposed by the power industry and energy market. This Special Issue aims to disseminate state-of-the-art research and contribute to the applications of control and optimization paradigms in renewable energy systems. The application topics of interest include, but are not limited to:

• Advanced control methods (fuzzy, artificial intelligence, neuro-fuzzy control, sliding-mode control, backstepping control, adaptive and predictive control, data-driven control, etc.);
• Optimization methods (swarm optimization, genetic algorithms, Newton–Raphson, bacterial foraging optimization, simulated annealing, linear programming, hybrid optimization methods, etc.);
• Other methods (any improved control and/or optimization method dealing with renewable energy systems.

Dr. Tariq Kamal
Dr. Syed Zulqadar Hassan
Guest Editors

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