Our lab hosts a dynamic group of scholars dedicated to advancing research in microgrids, smart grids, and power electronics. They focus on developing innovative solutions for sustainable energy systems, optimizing grid reliability and integration, and designing cutting-edge power conversion technologies to address the challenges of modern energy networks.

Research interests include coordinated power management of transient and steady state response in hybrid AC-DC microgrids through decentralized control schemes.

Research interests encompasses investigation on ancillary harmonic support in microgrids. Online instantaneous harmonic extraction and advanced control algorithms for harmonic compensation support from distributed generation unit.

Research interest includes the economic operation of microgrid and distribution network. Currently working on the optimal coordinated operation of multiple microgrid connected in active distribution network.

Research interests are modelling, state estimation and development of cell equalization techniques for Lithium-ion batteries in Battery Management System (BMS) for Electrical Vehicles as well as Microgrid applications.

Research interests include peak energy management using data-driven building automation and development of demand response techniques for residential and non-residential Indian building stock.

Research focuses on Volt/VAR control in active distribution networks, with emphasis on optimal integration of solar PV and Battery Energy Storage Systems (BESS). Work includes inverter control design using grid-following strategies, development of multi-level Volt/VAR optimization techniques for day-ahead and real-time operations, and application of machine learning methods for forecasting solar generation and load demand. Currently serving as a research intern at GE Vernova Advanced Research Center.

Research interests include advanced control algorithms for grid-forming and grid-following inverters, power electronics converter control in distribution networks, and machine learning applications in converter control algorithms.

Research Interests include Applications of Vehicle-to-Grid (V2G) and Renewable Energy (RE) Technologies for grid demand and carbon footprint management, Dynamic Economic Emission Dispatch in a Smart Grid Environment, Artificial Intelligence Applications in Power Systems. Currently working on optimal V2G scheduling of renewable-integrated power grids.

Research interests are ac-dc load flows in distribution systems, power system stability, smart grid, distribution power generation, hybrid power systems.

Smart grid analysis, Electric Vehicles, PHEV applications in Smart Grid environment. Power system analysis. Topic of research: “e-mobility infrastructure integrated distribution system analysis”.

Research area includes voltage regulation in a renewable rich distribution network with the optimal placing of multiple DG, Currently working in parallel operation of DGs without or with minimal communication.

Currently working in the area of distribution system optimization. Objectives are cost and loss minimization in the distribution grid.

Research interests include data-driven based forecasting of RES generation and load variation, modelling of uncertainties in RES.

The goal of my research is to develop breakthrough technologies that radically improve the performance of those power network systems by overcoming the barrier between the mathematical theories and real systems.

Research interests include Applications of Machine Learning in Power Systems

Applications of Data Driven Methods in Power Systems.

Research interests include modeling, analysis, and control of power electronic converter-based renewable energy sources.

Reconfigurable DC microgrid protection.

Coordinated operation of transmission and distribution system.

Research interests include designing power electronics converters to improve efficiency, reliability, and scalability, as well as developing advanced control strategies for multi-microgrid systems to enhance integration, stability, and renewable energy utilization.

DC microgrid application to electric vehicles.