A Cloud Analytics-Based Electrical Energy Management Architecture Empowered by Edge Analytics AIduino with Push Notifications for Demand-Side Management

Abstract

In a Smart Grid (SG), Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emissions, which are associated with electricity usage in today’s modern society. Electrical energy demands requested from down-stream sectors in a SG are continuously increasing. To meet those demands, Energy Management Systems (EMS) monitor and manage industrial, commercial as well as residential electrical loads efficiently in response to demand response schemes for DSM. This study presents a cloud analytics-based electrical EMS architecture empowered by edge analytics with push notifications for DSM. An AI-embedded Arduino-based smart power-meter prototype, embedded AIduino, is designed and implemented for edge analytics in the presented architecture. The experimentation reported in this study shows the feasibility of the architecture presented in this study. The embedded AIduino designed and implemented in this study can be further developed for preventative maintenance in DSM.