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

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 "broadcasted" power from generation plants to large population of consumers on a suboptimal 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.

Performance of Advanced Metering Infrastructure using cellular communication based on uplink CDMA

“…To get the AMI stage it is necessary to perform an economical study which is related to the investment of the technological infrastructure, the cost of the electrical meter, the cost of the communication technology and the needed resources to store the information safety [6].…”

Performance analysis of data processing architectures for the Smart Grid

“…CDR uses data-centric and publish/subscribe based communication for secure, scalable and reliable DR systems. Scalability aspects of data storage and monthly bill processing in SG is investigated in [4] and [9]. Several data storage mechanisms like centralized relational database, distributed relational database and file systems are compared and evaluated, as well as how communication cost scales with the number of smart meters and sampling frequency.…”

A cost-benefit analysis of data processing architectures for the smart grid

“…Cloud based Demand Response (CDR) architecture using a distributed information infrastructure is proposed in [10]. Scalability aspects of data storage and processing of monthly bills in SG is investigated in [11]. Several data storage mechanisms like centralized relational database, distributed relational database and file systems are compared and evaluated.…”