Smart Grid Security Framework for Data Transmissions with Adaptive Practices Using Machine Learning Algorithm  

作　　者：Shitharth Selvarajan Hariprasath Manoharan Taher Al-Shehari Hussain Alsalman Taha Alfakih 

机构地区：[1]School of Built Environment,Engineering and Computing,Leeds Beckett University,Leeds,LS13HE,UK [2]Department of Computer Science and Engineering,Chennai Institute of Technology,Chennai,602109,India [3]Centre for Research Impact & Outcome,Chitkara University,Chandigarh,140401,India [4]Department of Electronics and Communication Engineering,Panimalar Engineering College,Chennai,600123,India [5]Department of Self-Development Skill,Common First Year Deanship,King Saud University,Riyadh,11362,Saudi Arabia [6]Department of Computer Science,College of Computer and Information Sciences,King Saud University,Riyadh,11543,Saudi Arabia [7]Department of Information Systems,College of Computer and Information Sciences,King Saud University,Riyadh,11543,Saudi Arabia

出　　处：《Computers, Materials & Continua》2025年第3期4339-4369,共31页计算机、材料和连续体(英文)

基　　金：supported by the Researchers Supporting Project number RSP2025R244,King Saud University,Riyadh,Saudi Arabia.

摘　　要：This research presents an analysis of smart grid units to enhance connected units’security during data transmissions.The major advantage of the proposed method is that the system model encompasses multiple aspects such as network flow monitoring,data expansion,control association,throughput,and losses.In addition,all the above-mentioned aspects are carried out with neural networks and adaptive optimizations to enhance the operation of smart grid networks.Moreover,the quantitative analysis of the optimization algorithm is discussed concerning two case studies,thereby achieving early convergence at reduced complexities.The suggested method ensures that each communication unit has its own distinct channels,maximizing the possibility of accurate measurements.This results in the provision of only the original data values,hence enhancing security.Both power and line values are individually observed to establish control in smart grid-connected channels,even in the presence of adaptive settings.A comparison analysis is conducted to showcase the results,using simulation studies involving four scenarios and two case studies.The proposed method exhibits reduced complexity,resulting in a throughput gain of over 90%.

关 键 词：Machine learning power systems SECURITY smart grid 

分 类 号：TM76[电气工程—电力系统及自动化] TP181[自动化与计算机技术—控制理论与控制工程]