Work

Four Networks and Four Flows Integration with Digitalization and AI

Year: 2026

Type: article

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.

Source: Energies

DOI: 10.3390/en19174063

Authors: Chingchuen Chan, Wei Han, Xuxing Duan

Institutions: Hong Kong Polytechnic University, The Hong Kong University of Science and Technology (Guangzhou)

Language: English

Topic: Integrated Energy Systems Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $3,137