Distributed Monitoring for Energy Infrastructures: A Two-Tier Analysis over Wireless Networks

Wireless networks (e.g., 5G networks) enable distributed energy infrastructures to be connected even when they are geometrically isolated. Intelligent monitoring from remote sites therefore becomes possible, allowing decision makers to examine the status of distributed energy infrastructures from a central location. The major challenge is when local devices cannot perform the monitoring independently; transmitting every signal back to the central server triggers enormous amounts of wireless communication. To address this, we propose a two-tier AI system by offloading computations to multiple devices. Specifically, we build lightweight AI models for deployment on edge clients (i.e., edge sensors) and a large-scale AI model for the central server. These two types of AI models are trained with different criteria: the models on the edges act as the filtering tools to detect abnormal events and maximally avoid making false negative predictions, whereas the server model is supposed to be an expert for accurate predictions. By validating on a power theft dataset, we show that such a cascading methodology could filter out sufficient negative examples on the edge side while still being able to provide precise predictions on the second-round analysis.

Introduction

Energy infrastructures in many scenarios are naturally distributed over multiple locations. For example, distributed energy resources (DERs) provide electricity consumers commercially competitive alternatives to the conventional centralized grid. Infrastructures on the consumption side tend to be even more distributed: devices are generally located in different households, factories, or even districts. This geometric isolation brings some practical difficulties when performing monitoring or maintaining tasks. Manual maintenance and anomaly detection often need engineers to check the status of distributed infrastructures, compare abnormal meter readings with normal ones, or examine a bypassed power transmission line on site. This would require enormous human resources to be deployed, along with other issues such as time consumption and costs.