Cloud-Based Optimal Energy Forecasting for Enabling Green Smart Grid Communication

In a smart grid, micro-grids can exchange energy among themselves in order to provide reliable energy service to customers. Therefore, the micro-grids need to exchange their real-time energy status with other micro-grids, which, in turn, maximizes the energy consumption and CO2 emissions to them. In this paper, we propose a cloud-based energy forecasting scheme to minimize the energy consumption and CO2 emission towards enabling a green smart grid communication technology. Additionally, we device an optimal strategy for the proposed cloud-based energy forecasting scheme to minimize the energy consumption furthermore. Numerical results show the effectiveness of the proposed scheme over without cloud-based approach in terms of message overhead, energy consumption, and CO2 emissions of the micro-grids. We see that the proposed scheme can minimize the energy consumption and the CO2 emissions involved in the forecasting process significantly, which supports the green architecture of the smart grid communication technology. Additionally, the message overhead for energy forecasting can also be minimized.