A Novel Edge-Supported Cost-Efficient Resource Management Approach for Smart Grid System

The smart grids, a new-generation power supply system, have the capacity to lowering the cost, can increase service provision tremendously, and make surroundings greener as compared to conventional power supply systems. To interact with the physical world and widen its capabilities, integrated smart grid cyber-physical system (SG-CPS) can be used for computation, communication, and control. To support smart grid (SG), cloud components are employed for storing and processing users' power demand and control flow information generated at different control components like smart meter (SM), home energy management (HEM), phasor measurement units (PMUs), and soon. But storing smart grid data to cloud and processing incurs unacceptable delays. This paper addresses quality-of-service (QoS) requirements of SGs by integrating fog computing along with cloud computing infrastructure for realizing an Edge Computing integrated Smart Grid (EC-iSG). To that end, this paper presents novel heuristics for resource management of such integrated infrastructure that accounts for parameters such as uplink and downlink communication costs, cost for VM deployment, and cost for communicating among base stations. The results presented demonstrate the efficacy of the proposed methodology.