A novel optimal management method for smart grids incorporating cloud-fog layer and honeybee mating optimization algorithm

As a result of cloud-fog (CF) technology, today's society is experiencing low delay, great performance, improved safety, and lower operating costs. As a result of integrating Smart Grid (SG) into the CF platform, the power supply is of higher quality, and the transmission, distribution, and production of power are secure; management of demand and supply is continuous. The study proposes integrating SG with CF-driven environments to improve source distribution. There are 6 fogs in various areas. Every fog connects to a cluster, and there are 500 smart houses in every cluster. Home energy demands are fulfilled by fogs using various load balancing algorithms (LBAs), which are implemented on Digital Twin Virtual Machines (DTDTVMs) and provided with a fast response time (RT) and processing time (PT). The study proposes a Honeybee Mating Optimization Algorithm to balance loads using improved service broker policies. After comparing the outcomes of the suggested LBA to the particle swarm optimization algorithm (PSO), it can be concluded the suggested LBA performs better in comparison with PSO. All the simulation results and comparisons have been performed on digital twin environment to provide more realistic framework for this study.

Automated summary

By integrating Smart Grid (SG) into Cloud-Fog (CF) technology, it is possible to improve the quality and continuity of power distribution, achieve low delay, great performance, improved safety, and lower operating costs.