A survey on energy routing approaches in energy internet
Résumé
Energy Internet (EI) represents a modern paradigm focused on peer-to-peer energy trading within a smart grid network. This requires bidirectional power and communication flows, that are facilitated by energy-routing algorithms and devices. Various methodologies, such as graph theory, game theory, and bio-inspired approaches, are employed in developing these algorithms. However, the integration of distributed renewable energy sources into the main grid has introduced new challenges that need to be addressed: Subscriber Matching, Energy-Efficient Path, and Transmission Scheduling. In this study, we comprehensively review existing EI protocols using three distinct categories: traditional, bio-inspired, and artificial intelligence-based approaches. By analyzing and comparing these approaches, we aim to classify their effectiveness in addressing the three problems mentioned earlier, as well as the challenges introduced by distributed energy routing. Our work aims to offer a comprehensive understanding of the field as well as the challenges, requirements, and context for future research in EI routing.