Main Article Content
Wireless networks are becoming ubiquitous and as the cost of equipment decreases and performance increases, it becomes both economically and technologically feasible to deploy wireless networks in power systems and industrial environments for a wide range of applications. They have advantage of providing diverse controlling features through a unified communication platform. Application of such networks in the smart grid/industrial environments is under active research and expected to become an integral part of the power system. This research propose novel technique smart grid communication in wireless 5G networks for monitoring and controlling management. Here the smart grid designing has been done based on wireless communication networks. The smart grid network for renewable energy has been controlled using Stackelberg equilibrium based SCADA (supervisory control and data acquisition) method. The control method based collected data has been monitored for detection of malicious activities in the network using supervised radial basis fuzzy systems. The experimental analysis has been carried out based on control system and network malicious activities. Here the control system based parameters analysed are Scalability of 65%, QoS of 71%, Power consumption of 41%, Network Efficiency of 92%. Then machine learning based malicious activities detection in terms of accuarcy of 96%, network security of 88%, throughput of 94%, Network delay of 41%. Proposed method supports interoperability of multiple types of inverters, is scalable and flexible, and transmits data over a secure communication channel.
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