Advancing the Energy Internet: Innovations and Solutions for a Sustainable Energy Future

Dear Colleagues,

The Energy Internet represents a transformative paradigm integrating advanced power systems, distributed renewable energy, and digital technologies to achieve efficient, resilient, and sustainable energy management. As global decarbonization efforts intensify, the Energy Internet’s core components—including smart grid situational awareness, renewable integration optimization, AI-driven microgrid control, and cloud-based big data analytics—are critical to addressing challenges in grid stability, energy equity, and carbon neutrality. Notably, the convergence of artificial intelligence, edge computing, and IoT technologies with power systems has unlocked unprecedented opportunities for real-time decision-making, predictive maintenance, and demand-side management. However, the complexity of multi-energy synergies, cyber-physical security risks, and the volatility of renewable generation necessitate innovative solutions in data-driven modeling, adaptive control, and scalable infrastructure design. This Topic invites cutting-edge research on theoretical advancements, empirical case studies, and technological innovations to propel the Energy Internet toward scalability and interoperability.

Contributions may address, but are not limited to, the following areas:

• Situational awareness and dynamic stability analysis for smart distribution grids;
• Optimization control strategies for high-penetration renewable energy integration;
• AI/ML applications in microgrid energy management and fault diagnosis;
• Blockchain-enabled peer-to-peer energy trading and decentralized governance;
• Big data analytics for load forecasting, asset management, and grid anomaly detection;
• Cyber security and resilience in cyber–physical power systems;
• Edge-cloud collaborative computing for distributed energy resource coordination;
• Standardization and policy frameworks for Energy Internet deployment;
• Socio-economic impacts and business models for transactive energy systems;
• Digital twins and virtual power plants for grid flexibility enhancement.

Dr. Leijiao Ge
Dr. Dou An
Topic Editors