Integrating Elastic Energy Management with Mixed Reality Interfaces for Local Balancing in Prosumer Low-Voltage Networks

Abstract

This paper introduces the integration of smart appliances and Internet of Things technologies for the local balancing of low-voltage power distribution networks, particularly in response to the proliferation of prosumer renewable energy sources. The primary objective is the incorporation of the Elastic Energy Management algorithm with Mixed Reality and Augmented Reality interfaces to facilitate intuitive demand-side management. The methodology employs the GRASP heuristic algorithm alongside advanced on-device 3D point cloud segmentation, enabling the system to identify physical energy consumers within a residential environment. Simulation results demonstrate high algorithmic convergence and the capacity for the system to provide real-time updates to visual interfaces. The findings indicate that the utilization of AR and MR goggles significantly enhances interaction with energy infrastructure by providing hands-free operation and overlaying digital data directly onto physical components. This approach enables more effective grid balancing and increased self-consumption of renewable energy while maintaining user comfort and reducing the technical knowledge required for efficient household energy management.