Research on optimising the absorption capacity of feeders in medium and low-voltage distribution networks based on deep learning

Key Points

• The aim is to enhance the efficiency of absorption capacity in electrical distribution networks using deep learning techniques.
• Utilized deep learning models to analyze feeder performance
• Assessed medium and low-voltage distribution networks
• Performed simulations to test optimization strategies
• Demonstrated improved absorption capacity in various tested networks
• Showed significant efficiency gains over traditional methods