Fog Computing‐Based Communication Systems for Modern Smart Grids

A new age of electrical energy management is driven by modern communication systems. Technologies such as the Internet of Things (IoT) and cloud and fog computing are becoming seriously considered by the industry as a replacement for old communication systems in modern distribution networks, such as existing supervisory control and data acquisition (SCADA). Large amounts of data, produced by millions of customers, will be used by power system operators in the near future, with the ultimate goal of creating a fully automated and self‐conscious Ssmart Grid (SG). Cloud computing proved to be a very successful technology with applications in many areas, but bandwidth‐ and latency‐related issues raise questions about its efficient application for near real‐time calculations required by SGs. On the other hand, fog computing technology supports fast local data calculation and analysis, which could be the key for near real‐time data management. Power system operations are governed by many devices with different data processing time requirements, e.g. digital relays used for power system protection are often required to operate and communicate with each other in less than 50 ms. On the contrary, smart meters, collecting data for load balancing, are required to communicate just once in several minutes. Sampling rates of modern SCADA systems are often one sample per second. These significant differences in data transmission and calculation speeds pose a big challenge to modern communication systems. This chapter primarily aims to investigate the possibilities of fog computing–based communication system applications in the SG. Existing IEEE test grid topology is used as a basis for the creation of the SG model in MATLAB/Simulink. The developed SG model is made of energy and communication parts adjusted to operate simultaneously in a real‐time simulation environment. A special fog computing–based communication system is recommended and tested for state estimation and load flow calculation. Obtained results of near real‐time simulations proved applicability and efficiency of the proposed communication system for monitoring and regulation of voltage profile in the test grid.