The need to advance the state-of-the-art in smart grid technologies is increasingly recognized by scientists, engineers, practitioners and policy makers, as the critical mechanism to improve the energy efficiency of producing and using electricity in our homes, businesses, and public institutions. The smart grid enhances the traditional electricity distribution system with three components: two-way communications of energy and digital information (thus enabling the combination of energy and information as entities being exchanged), monitoring infrastructures to supply information to the communication network, and computational intelligence to use such information to maintain stable optimal operational efficiency and energy delivery and to enable autonomous response to abnormal or disruptive events. The smart grid allows the control and monitoring of the entire grid, from the utility to the smart home (e.g., smart appliances, plug-in electric vehicles). The overall goals are energy conservation, cost reduction, and enhanced reliability, security and transparency.
The overarching vision of iCREDITS is to create theories, processes, and best practices for operations of the smart grid by exploring important operational facets, such as energy delivery, monitoring, and coordination in the grid. This communication project aims to design a novel, scalable communication architecture to facilitate these operational facets by enabling the corresponding grid entities to effectively communicate with each other by meeting the bandwidth, delay, jitter, reliability, security, and privacy requirements of these communications. For portability and backward compatibility with legacy systems, our architecture will extend existing substation communication standards operating in an Internet Protocol (IP) based infrastructure, and leverage the advantages of the recently proposed information-centric networking paradigm.
From our preliminary research, we have designed an architecture that consists of three levels of hierarchy with bidirectional information flow between adjacent layers. The bottom (physical) level will consist of the agents of the communicating devices (smart meters, synchrophasors, etc.). The next (aggregation) level will contain aggregation nodes, which will help decouple the data from the devices and also perform information aggregation and caching. The last (decision) level, is a cloud of computing servers, which performs grid monitoring, management, and optimization using the data received from the grid.