Energy Sources Integrated With Power Distribution Systems Using Machine Learning Approach

This article discusses the potential of machine learning (ML) to transform the energy distribution and consumption sectors, particularly in the context of distributed energy sources (DES) integrated into urban power distribution systems. The authors emphasize the need for interdisciplinary research and collaborative approaches to fully harness the benefits of ML in creating a cohesive, intelligent energy ecosystem. The Special Issue focuses on understanding the interplay between power distribution and energy systems, distribution energy sources, transportation systems, and building technologies with the integration of ML approaches.