Radio Resource Allocation Scheme for Reliable Demand Response Management Using D2D Communications in Smart Grid

Abstract

Integration of renewable energy into power distribution network is a challenge because renewable output is intermittent. This problem can be tackled through demand response management which controls consumption demand by adjusting energy prices in real-time to match the available time-varying power supply. Such real-time pricing (RTP) requires an advanced communication network to collect data and to disseminate price information. We use cellular-assisted underlay device-to-device (D2D) communications to connect energy management units (EMUs) directly to the RTP control center. Such D2D transmissions can be interfered by concurrent cellular transmissions. This interference can affect reliability of the RTP operation. We quantify the reliability requirements given a tolerable financial loss and a supply-demand gap. The cost in satisfying the reliability requirement appears in the form of a lower sum-rate for all cellular nodes, because cellular rate is a revenue generator for communication service provider. We formulate an optimization problem to allocate radio resources in terms of communication channel and transmit power, to maximize the cellular sum-rate without compromising the RTP reliability requirements. Since the optimization problem is non-convex, we use a pair of iterative algorithms to assign communication channel using the Hungarian algorithm and to control transmit power using the difference of convex (DC) optimization. The effectiveness of the combination of the Hungarian algorithm and the DC optimization has been verified through extensive simulations, with the results compared against a benchmark scheme that randomly assigns communication channels.