Wireless Sensor Network Based Smart Grid Supported by a Cognitively Driven Load Management Decision Making

The Smart Grid (SG) provides the bi-directional flow of data to overcome problems like shortage of electricity, electricity billing, managing fault, home automation so on. For the transfer of data, the integration of Cognitive Radio (CR) in sensor networks makes efficient communication possible in real-time monitoring. SG uses different technologies like WiFi, cellular network, ZigBee, optical cables depending upon the area of application. For effective communication, CR is used to allocate the unutilized spectrum from the Primary User to the Secondary User by sensing. This paper proposes a technique called Fuzzy Long Sort Term Memory based Crow Search Optimization Algorithm (FLSTM–CSOA) to allocate the best available spectrum with minimum delay. By comparing our proposed method with the existing technique, the simulation result shows that the FLSTM–CSOA has better performance in terms of BER (10−1), throughput (200 kbps), and latency (10 ms).