The Renewable Energy Storage Systems Laboratory is equipped with advanced experimental facilities including a Solar PV Emulator Trainer Kit, Solar PV Panels, PV Emulator, Micro Wind Energy Generator Module, Fuel Cell Trainer Kit, and a Battery Storage System. Utilizing this existing infrastructure, the proposed funded project aims to develop a hybrid renewable energy system integrated with intelligent energy management and storage optimization.

Renewable energy sources such as solar and wind are inherently intermittent and require effective storage and control strategies to ensure reliable power supply. This project focuses on integrating solar PV (both real-time panels and emulator-based testing), micro wind generation, and fuel cell systems with a battery energy storage system to create a stable and efficient hybrid microgrid model. The PV emulator enables controlled experimentation under varying irradiation and temperature conditions, while the wind module provides supplementary renewable input. The fuel cell system will act as a clean backup power source during low renewable generation periods. The battery storage system will be managed using state-of-charge (SOC) based intelligent charging and discharging control to enhance lifespan and efficiency.

The research will involve system modeling and simulation using MATLAB/Simulink, implementation of Maximum Power Point Tracking (MPPT) techniques, development of DC-DC converter control strategies, and real-time hardware validation using the available trainer kits. An intelligent controller with IoT-enabled monitoring may be incorporated for real-time data acquisition, performance analysis, and predictive energy management.

The expected outcomes of the project include development of a laboratory-scale hybrid renewable prototype, improved energy management algorithms, optimized storage utilization strategies, and performance validation under dynamic load conditions. The project aligns with national renewable energy missions, clean energy transition goals, hydrogen energy adoption strategies, and Sustainable Development Goal 7 (Affordable and Clean Energy). Since the core hardware infrastructure is already available in the laboratory, the requested funding will primarily support advanced controller development, embedded systems, sensors, software tools, research manpower, consumables, and dissemination activities such as publications and conferences.

The proposed project has strong potential for high-quality journal publications, patentable energy management techniques, student research training, and industry collaboration in smart microgrid and decentralized renewable energy applications.