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.