Quantitative Analysis and Optimal Control Model of Information Flow for Energy Internet

Energy Internet, as a key force to promote the transformation of the global energy system to a more green, efficient and intelligent direction, its core idea is to build an integrated energy network that seamlessly connects different regions and spans multiple energy forms. In the architecture of the energy Internet, information flow plays a crucial role. Like a nervous system, it realizes the deep integration and collaboration of energy flow, business flow and data flow. In order to further improve the operation efficiency and stability of the energy Internet, this paper innovatively proposes a quantitative analysis and optimization control model of information flow for the energy Internet. This model accurately captures and analyzes the complex and changeable information flow laws in the energy Internet, and combines advanced artificial intelligence (AI) algorithm and big data technology to carry out refined management and optimal scheduling of information flow. The experimental results show that the model can significantly improve the information processing speed of the energy Internet, optimize resource allocation strategies, reduce energy waste, enhance the system’s response to emergencies, and provide a strong technical support for the sustainable development of the energy Internet.