Research Interest

• "Consumer-Driven Grid Variability with Electric Vehicle and Renewable Integration"

This study explores the integration of electric vehicles (EVs) and photovoltaic (PV) systems within a small-scale distribution network at Jashore University of Science and Technology (JUST). Using DIgSILENT PowerFactory, a quasi-dynamic simulation is carried out for the year 2024 to evaluate system performance under varying EV penetration levels and renewable energy scenarios. The research highlights operational challenges such as transformer overloading and increased system losses, and investigates possible solutions to support a stable and resilient grid as EV adoption grows. 

• "Machine Learning-based Fault Classification and Localization in Renewable Integrated Power Systems"

Traditional fault diagnosis methods are often complex, time-consuming, and dependent on expert input, making them less practical for real-time applications. This study presents a simplified machine learning-based approach for fault classification and localization in power systems with integrated EV and PV systems. By utilizing only three-phase voltage and current data from DIgSILENT PowerFactory simulations, the method avoids intricate feature engineering while aiming to deliver accurate and efficient fault diagnostics. Multiple machine learning algorithms were evaluated and optimized to identify effective models for practical implementation in intelligent power system protection.

• "Optimizing Grid Resilience with Cost-Effective Integration of EV, PV, and Electrolyzer Systems"

This research investigates economically viable pathways to enhance grid resilience while accommodating high penetrations of renewable energy. Through high-level modeling and optimization, the study explores combinations of solar PV, energy storage, demand response, and grid interconnections to ensure system flexibility and stability. By analyzing different integration scenarios and their impacts on grid performance, the research offers strategic insights for sustainable and cost-effective energy planning—serving as a practical guide for policymakers, utilities, and energy planners.