Energy-Aware Optimal Data Aggregation in Smart Grid Wireless Communication Networks

Abstract

We propose a two-hop wireless communication architecture for smart grid (SG) consisting of smart meters (SMs), aggregators (AGs) and cellular base stations (BSs). The architecture is then considered to transfer the periodic traffic of the SMs to the BSs via the AGs with data concatenation or direct transmission. We formulate an optimization problem to minimize the energy consumption by the optimal AG selection for the SMs, data concatenation and transmit power allocation which turns out as a mixed integer non-linear programming. By means of several analytical formulations and an optimization tool, we solve the problem for many SG network instances and demonstrate that two hop communication architecture with the optimal configuration requires significantly less energy compared to a single hop communication architecture without data aggregation. We also investigate the effects of the number of the SMs, modulation order, wireless channel, and sizes of packets on energy consumption and provide various engineering insights. Further, a heuristic algorithm is developed for solving the optimization problem without any optimization tool. The effectiveness of the heuristic algorithm is verified by comparing the energy consumptions of the heuristic and the optimal algorithms. The comparison results show that the difference of the energy consumptions is not significant.