Advancements in optimization strategies for energy routing, demand response, and load forecasting in energy internet and smart grid: an overview

Abstract

Electricity plays a fundamental role in modern society, supporting essential services and contributing to economic and technological development. However, the centralized architecture of the traditional power grid and its dependence on fossil fuels have raised concerns regarding inefficiency, environmental impact, and limited operational flexibility. In response, Smart Grids (SG) and the Energy Internet (EI) have emerged as advanced paradigms that facilitate decentralized energy exchange, including peer-to-peer (P2P) energy trading. These systems introduce new challenges, particularly in energy routing, load forecasting, and demand response. Despite growing research in these areas, the literature remains fragmented, with limited integration across these interdependent components. This review addresses this gap by examining the development of the Energy Internet, comparing it with Smart Grids, and analyzing its physical and software infrastructure. The operational principles of the EI are briefly outlined, and the main challenges related to energy routing, demand response, and load forecasting are discussed. The study presents a comprehensive analysis of energy routing within the SG and EI frameworks, highlighting its dependencies on load forecasting and demand response. Existing solutions in the literature are classified by method into graph theory, game theory, autonomous, and heuristic-based approaches, and are systematically compared. The findings presented in this review serve as a valuable resource for researchers and practitioners seeking to advance the field of energy routing in the context of Smart Grids and the Energy Internet.