Edge-Intelligent Energy Management Architecture for IoT-Integrated Smart Power Systems

Abstract

The accelerated development of smart grid structures and the prevalence of the Internet of Things (IoT) technologies have drastically changed the conventional power systems into smart, interconnected, and networked systems driven by data. The energy management of efficiently using the growing distributed energy sources, variable demands of energy, and the necessity of managing and controlling their energy in a real-time aspect have become a critical issue. Traditional cloud based energy management systems typically have a number of drawbacks such as high level of communication latency, high bandwidth usage as well as the possibility of security breaches that can limit the ability to make timely decisions in large scale intelligent power system. In order to overcome these challenges, this paper suggests an Edge-Intelligent Energy Management Architecture (EIEMA) aimed at internet of things (IoT)-enabled smart power settings. The architecture proposed uses edge computing to conduct local data processing and real-time analytics, and reduce the reliance on centralised cloud services, which brings the data processing and analysis nearer to the data source. With this model, IoT sensors and smart metres constantly gather operational information on voltage, current, power consumption, and even renewable energy production of various parts of the grid. This data is collected by edge nodes that are positioned close to sub stations or micro grid controllers and processed and analyzed to facilitate decentralized decisions, load balancing and quick fault identification. The cloud layer is an extension of the system to offer a big data storage and analysis, model training to predictively optimise data. The proposed architecture allows maximising energy consumption, increasing system responsiveness, and grid stability, with the use of IoT sensing, edge intelligence, and cloud coordination. The outcome of simulations illustrates that the EIEMA framework can reduce greatly system latency, and communication overhead, and enhance the effectiveness of energy utilisation at large scale compared to traditional cloud-based energy management systems, hence it can be adopted by new generation smart power system.