• Renewable energy
• Multi-model energy systems
• Data-driven modeling
• E-mobility

Work experience

Worked as a research assistant at Otto von Guericke University Magdeburg for one year with following accomplishments:

• Analyzed the impact of the rise of electric vehicles (EVs) on grid operation. 
• Developed simulation models to calibrate the electric vehicle load from the traffic model data.
• Automated the data-processing using python which decreased the error probability and improved the handling efficiency by 8.4%.
• Improved the voltage stability by 5.6%, by considering the short-term uncertainty in the EV load for a multi-model energy system. 
• Proposed solution algorithm that decreased the computational time of the planning problem by 13.2%.

Projects

Stochastic optimization for planning and operation in microgrids considering long-term uncertainty in charging station

• Developed a smart multi-model microgrid system that integrated energy and transportation sector.
• Improved the planning model of microgrids by including the long-term uncertainty in the rise of charging stations. 
• Pioneered a state-of-the-art electric vehicle charging station (EVCS) simulation model based on the waiting time of EVs.
• Decreased the cost by 19.57% for the microgrids by proposing a combined planning model.
• Investigated the impact of charging station load on the capacity sizing of DERs.

Geographical assignments of storage systems to distribution substations

• Designed portfolio management of wind energy, PV, storage systems, and other renewable systems in Germany.
• Handled the storage systems dataset using SQL queries which decreased the computational time by 39.4%.
• Mapped renewable systems to substations using python programming.
• Redeployed the model to perform load flow studies for planning reserve capacities.