Four Networks and Four Flows Integration with Digitalization and AI

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Abstract
Against the backdrop of the accelerating global low-carbon transition, the mismatch between intermittent renewable energy generation and inflexible energy demand has become a major bottleneck for sustainable energy development. To address this challenge, this paper proposes an AI-driven 4N4F (Four Networks and Four Flows) multi-network convergence system. The paper first clarifies the conceptual connotation and theoretical foundation of 4N4F integration and then systematically constructs an overall technical architecture built on three core pillars: intelligent connected electric vehicles as mobile energy nodes, intelligent networked building-integrated photovoltaics as stationary energy carriers, and an integrated energy management system as the global coordination hub. The effectiveness of the proposed framework is examined through representative engineering cases covering commercial buildings, hybrid energy storage, off-grid microgrids, and sustainable campuses. The results demonstrate that the 4N4F system breaks down traditional silos among energy, information, transportation, and human networks, significantly improving renewable energy utilization and overall energy efficiency. These findings highlight the framework’s scientific contribution as a new technical paradigm for modern energy-system construction and sustainable development.
Funding Information
  • Guangdong Basic and Applied Basic Research Fund (2025A1515012012)
  • Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone (HZQB-KCZYB-2020083)
  • National Natural Science Foundation of China (52277004)
  • Ningbo “Sci-Tech Innovation Yongjiang 2035” Key Research and Development Program (2026Z016)

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