A Fog Computing Architecture for Energy Demand Scheduling in Smart Grid

The demand-side management is considered as an interesting functionality offered by the recent smart grid. This functionality allows the control and scheduling of consumer energy demand, which helps avoiding the problems of offer-demand gap and consumption peaks. The cloud is considered as a powerful tool that ensures scheduling appliances' energy demand in centralized manner. However, the distance between the end users and the cloud might be a problem for latency. In addition, the more and more increasing number of connected objects, generating a huge amount of data that must be transmitted over the communication network, worsens the situation. Fortunately, the novel paradigm of fog computing came to mitigate these issues. In this paper, we propose a cloud-fog computing architecture for the energy demand scheduling. We propose to use this architecture to improve the consumption distribution over the day to reduce the total energy cost for smart buildings. Our work includes two parts: a distributed game-based approach for demand scheduling, and a model for the selection of fog nodes that will perform this distributed approach. The simulation results of the two proposals show that the integration of the fog architecture helps to considerably reduce the energy scheduling delay while determining the optimal demand schedule.