Work place: Department of Electrical and Electronics, University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, Tamil Nadu, India
E-mail: anbu@aubit.edu.in
Website:
Research Interests:
Biography
Anbalagan P. received his B.E degree in Electrical engineering from Bharathiar University, Coimbatore, Tamil Nadu, India. He obtained his M.E degree in Power Systems Engineering from Anna University, Chennai, Tamilnadu, India and PhD degree in Faculty of Electrical Engineering from Anna University, Chennai, Tamil Nadu, India. He is currently working as Assistant professor in Electrical Engineering at BIT campus, University College of Engineering, Anna University, Tiruchirappalli, Tamil Nadu, India. His research area covers the application of power electronics in renewable energy systems, Power quality, Information and Communication Technologies.
By J. B. Shriram P. Anbalagan A. Vegi Fernando Srikanth Mylapalli
DOI: https://doi.org/10.5815/ijitcs.2026.01.01, Pub. Date: 8 Feb. 2026
Expansion of Internet of Things (IoT) technologies has greatly enhanced monitoring and management of energy systems, especially in Hybrid Renewable Energy Systems (HRES). This paper presents an IoT-based HRES smart grid framework with a modified Brain Storm Optimization (BSO) algorithm for routing optimization and an Improved Quantum Key Management (IQKM) is a quantum inspired protocol for better data security. The enhanced BSO algorithm, hosted in the cloud infrastructure, optimizes IoT sensor data routing paths, thus diminishing packet transmission latency and improving the network throughput. In contrast to conventional BSO techniques, the enhancement is through dynamic cluster refinement and adaptive node prioritization, designed specifically for real-time cloud-integrated energy systems. In order to protect sensitive energy transmission information, the IQKM protocol includes strong quantum-aided encryption processes and dynamic key creation. These enhancements directly counter the dangers of man-in-the-middle and replay attacks, which exceed capabilities of standard encryption approaches by facilitating low-latency, quantum-resistant communication between HRES nodes. Both Photovoltaic (PV) and wind-based energy sources are utilized by the system to provide power consistently, with cloud-based analytics and IoT sensors ensuring real-time monitoring. Experimental testing via the Adafruit platform reports a 23% Packet Delivery Ratio (PDR) enhancement and 17% encryption/decryption delay reduction compared to baseline and traditional routing algorithms. Such findings ensure the potential for stable, secure, and scalable grid performance by the proposed system.
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