A Comparative Study of Data Storage and Processing Architectures for the Smart Grid
This addresses the need for efficient information networks in Smart Grids to enable two-way electricity trading and optimization, but it is incremental as it focuses on comparative analysis of existing architectures.
The paper tackles the challenge of designing data storage and processing architectures for Smart Grids to handle real-time information from Smart Meters, comparing various system architectures to establish a foundation for future intelligent systems.
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.