
The increasing penetration of renewable energy sources such as solar and wind into modern power systems presents both opportunities and challenges. While renewable generation reduces reliance on fossil fuels and contributes to decarbonization, its intermittent and stochastic nature poses risks to grid stability, voltage regulation, and power quality. Smart grids provide an intelligent platform for managing these complexities through advanced monitoring, communication, and control technologies. This paper investigates advanced control strategies that enable effective integration of renewable energy into smart grids. Approaches such as model predictive control, adaptive control, and artificial intelligence-based techniques are discussed for their ability to mitigate variability and uncertainty in renewable generation. The role of demand-side management, distributed energy storage, and coordinated microgrid operation in enhancing reliability and resilience is also examined. Simulation studies and reported case applications demonstrate that these strategies significantly improve frequency stability, reduce curtailment of renewables, and enhance overall grid efficiency. The findings highlight that advanced control frameworks are essential for transitioning toward a secure, flexible, and sustainable power grid.
Smart Grids, Renewable Energy Integration, Advanced Control, Model Predictive Control, Adaptive Control, Artificial Intelligence, Grid Stability, Energy Storage
Smart Grids, Renewable Energy Integration, Advanced Control, Model Predictive Control, Adaptive Control, Artificial Intelligence, Grid Stability, Energy Storage
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