Title of article :
An intellectual procurement innovation of smart grid power system with wireless communication networks based on machine learning
Author/Authors :
Sathya, M. Department of CSE - Islamiah Institute of Technology, Bangalore, India , Gunalan, K. Department of EEE - R. M. K College of Engineering and Technology, Chennai, India , B S, Manohar Department of ECE - JSS Academy of Technical Education, Bengaluru, India , Anil Kumar, T CH Department of Mechanical Engineering - Vignan’s Foundation for Science Technology and Research, Andra Pradesh, India , Shafi, Shaik Department of ECE - B V Raju Institute of Technology, Telangana, India , Johncy, G. Department of CSE - St.Xavier’s Catholic College of Engineering, Kanyakumari, India
Abstract :
The phased array antenna is one of the most significant applications in fifth-generation mobile net-
works. It is one of the most important applications in fifth-generation networks. An electric power
source that powers the whole application, including the antenna’s root, is required. Even with the
most outstanding design, if the programme does not have a sound power supply system with min-
imal packet loss and cant Path find performance, it will be rendered ineffective. When seen from
the perspective of the multiplex information, Machine Learning comprises a communication network
based on the Internet that transmits information to the control centre via the objects (IOT). To
put it another way, the proposed communication infrastructure, via the provision of, and the chance
micro-grid state to collect, analyze, and two-way communication link control information, offers the
chance to resolve the voltage regulation issues. This cutting-edge communication infrastructure, as
well as a suggested state estimation filter focused on improving speed and performance in renewable
energy production, are both examples of creative communication infrastructure. Current research is
focused on analyzing and enumerating a range of energy abundances in the context of smart grids,
which are now in their fifth generation. Rather than concentrating on the future development plan,
which should be a problem of illusion, it should concentrate on the composition of the future po-
tential of smart grid communications framework. An in-depth investigation to give evidence to the
Machine learning will help intelligent networks in the future conduct a thorough evaluation.
Keywords :
Internet of things (IoT) , Machine learning , communication infrastructure provides , Smart grid power supply system
Journal title :
International Journal of Nonlinear Analysis and Applications