The smart grid, as a communication network, allows numerous connected devices such as sensors, relays and actuators to interact and cooperate with each other. An Internet-based solution for electricity that provides bidirectional flow of information and power is internet of energy (IoE) which is an extension of smart grid concept. A large number of connected devices and the huge amount of data generated by IoE and issues related to data transmission, process and storage, force IoE to be integrated by cloud computing. Furthermore, in order to enhance the performance and reduce the volume of transmitted data and process information in an acceptable time, fog computing is suggested as a layer between IoE layer and cloud layer. This layer is used as a local processing level that leads to reduction in data transmissions to the cloud. So, it can save energy consumption used by IoE devices to transmit data into cloud because of a long range, low power, wide area and low bit rate wireless telecommunication system which is called LoRaWAN. All devices in fog domain are connected by long range wide area network (LoRa) into a smart gateway. The gateway which bridges fog domain and cloud, is introduced for scheduling devices/appliances by creating a priority queue which can perform demand side management dynamically. The queue is affected by not only the consumer importance but also the consumer policies and the status of energy resources.
A Hybrid Genetic Wind Driven Heuristic Optimization Algorithm for Demand Side Management in Smart Grid
