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Original research AI-DRIVEN SMART GRID CONTROL: A COMPARATIVE REVIEW OF MACHINE LEARNING–ENHANCED PREDICTIVE, ADAPTIVE, AND ROBUST STRATEGIESPages 175-184 Abstract
Ensuring stability and performance efficiency in today electrical grids becomes central to the integration of advanced control strategies in power systems. In this paper, the current trends and noticeable developments on the area of control methodologies have been discussed especially on model predictive control, adaptive control and robust control. Such strategies are needed to deal with the complexities that are brought about by an increased use of renewable energy sources and changing load demands.
The given work uses a literature review and analysis conducted during the period of 2016-2024 to investigate the current progress and contemporary trend in the field of power system control. The article examines research articles, industry reports and case studies to know how advanced control methods stand with respect to improving the performance of the grid. The investigation is divided into algorithm optimizations, real life scenarios and application of control measures in different industries.
A review of the current trend in the advance control methods reveals that further innovation and advancement is crucial in the future of the power systems in the coming years. The results show that the advanced control methods especially the model predictive control, the adaptive control and the robust control greatly enhance the stability, efficiency of the grids. The paper supports the need of interdisciplinary methodologies to ensure the full potential of the advanced control methods are utilized to enable reliable and sustainable future electrical grids.
Keywords:
Advanced Control Strategies, Power Systems Stability, Electrical Grid Efficiency, Model Predictive Control,
Adaptive Control, Robust Control, Renewable Energy Integration, Grid Reliability.
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Asaad Ali Muhsen 
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