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Norsk

Sai Sasidhar Punyam Rajendran

Sai Sasidhar Punyam Rajendran

PhD Candidate
Department of Manufacturing and Civil Engineering
Faculty of Engineering

sai.s.p.rajendran@ntnu.no
+4792566163 Beryll-bygget, 213, Gjøvik
About

About

A graduate at master's level from Otto von Guericke University Magdeburg with a GPA of 2.0. Currently pursuing PhD in the area of microgrids at Norwegian University of Science and Technology. I try to apply acquired knowledge from education and research for tackling real-world problems by leveraging strong organizational, designing, and programming skills. I have done extensive research in the renewable energy domain by developing optimization and simulation models that improved the system's performance.
 
Research Interest:
  • 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.

 

Competencies

  • Basics in Machine learning
  • Github version control
  • Latex
  • MatLab
  • Python
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