A Comparative Study of Data Storage and Processing Architectures for the Smart Grid

TL;DR

This paper compares various system architectures for storing and processing Smart Meter data, essential for enabling real-time, intelligent energy management in modern Smart Grids.

Contribution

It provides a comparative analysis of different data storage and processing architectures tailored for Smart Grid applications, establishing a foundation for future intelligent systems.

Findings

Identifies key architectural options for Smart Meter data management

Evaluates performance and suitability of architectures for real-time processing

Offers insights into optimal design choices for Smart Grid data systems

Abstract

A number of governments and organizations around the world agree that the first step to address national and international problems such as energy independence, global warming or emergency resilience, is the redesign of electricity networks, known as Smart Grids. Typically, power grids have broadcast power from generation plants to large population of consumers on a sub-optimal way. Nevertheless, the fusion of energy delivery networks and digital information networks, along with the introduction of intelligent monitoring systems (Smart Meters) and renewable energies, would enable two-way electricity trading relationships between electricity suppliers and electricity consumers. The availability of real-time information on electricity demand and pricing, would enable suppliers optimizing their delivery systems, while consumers would have the means to minimize their bill by turning on appliances at off-peak hours. The construction of the Smart Grid entails the design and deployment of information networks and systems of unprecedented requirements on storage, real-time event processing and availability. In this paper, a series of system architectures to store and process Smart Meter reading data are explored and compared aiming to establish a solid foundation in which future intelligent systems could be supported.