A Systematic Review on Electric Vehicle Grid Stability based on Neural Network and Charging System

The current section provides the quick view of the review paper of EV grid stability-based energy efficiency performance. The grid stability of power was differentiated on the basis of the neural network and charging system techniques.  The neural network techniques consist of CBL [16], TCN [17] and light GBM [18] methods for improving the efficiency of grid stability. The charging station techniques comprises of FIWC [19], PIL based PV-EV [20] and PV with EVCS [21] for advancing the grid reliability performance. The methodologies, advantages and limitations of the existing research papers of grid stability performances are compared here. The existing techniques overcome issues such as energy consumption, cost efficiency and power scheduling. However, there still occur downsides such as power quality, voltage fluctuation, and boundary detection ability. Further the research field focus on modifying the conventional methods with the advanced strategic controllers for refining the functioning of EV grid stability by advancing the power quality.

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