Intelligent energy management of a grid-connected PV–battery electric vehicle charging station using CNN-BiLSTM-based control

Puntos clave

• Effective energy management optimizes photovoltaic and battery resources for electric vehicle charging operations.
• The study finds a significant increase in charging efficiency, improving grid stability and lowering costs.
• Analysis integrates convolutional neural networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) for improved demand prediction.
• The results may enable broader adoption of renewable energy sources in electric vehicle charging systems.