A Real-Time Monitoring Network for Charge Consumption in Distributed Energy Stations

Traditional charge consumption prediction methods are hindered by the challenges posed by the dispersed locations of distributed energy stations, the complexity of network planning, and the stringent requirements for operational efficiency, leading to difficulties in providing accurate and efficient forecasts. This paper proposes the VAGnet network, which utilizes a VAE-GAN architecture for predicting charge consumption in distributed energy stations. VAGnet integrates a multi-source heterogeneous information fusion strategy, enabling real-time monitoring across various operational states. A collaborative planning strategy based on multidimensional data sharing is also introduced to enhance real-time tracking accuracy. Experimental results demonstrate that VAGnet can effectively predict charge consumption at future time intervals, significantly improving the efficiency of real-time monitoring systems. This scalable solution meets the growing demands for precision and responsiveness in distributed energy station networks.