About the position
PhD project: Optimisation of Renewable Energy Sources (RES) and Energy Storage Systems (ESS) in a Microgrid
Due to global warming, climate change, and the increased need for sustainability, the current power grid needs to be transformed by integrating more renewable energies.
However, unlike traditional fossil-fuel-based power sources, renewable energy sources (RES) fluctuate with weather, are variable and are non-dispatchable.
One possible solution is using large-scale energy storage systems (ESS), which will store and dispatch energy when necessary, thus reducing this variability.
Microgrids, which are small formulations of the main grid grids with smaller RESs and ESS sizes, are becoming popular for integrating more renewable energies.
Microgrids can operate independently or be connected to the main power grid.
Designing and sizing an optimal microgrid involves many engineering constraints and parameters like voltage fluctuation, frequency deviations, system reliability, cost, and solving nonlinear power flow equations, which presents a complex optimisation problem.
This PhD project aims to find the best solution to this optimisation problem.
The objective is to identify and apply an efficient and robust optimisation algorithm to handle all the uncertainties related to the RES and tackle the engineering constraints and solve nonlinear power flow equations fast enough for better convergence.
The deliverables/outcomes can be summarised as follows: A suitable optimisation algorithm for microgrid sizing and design An optimisation algorithm for microgrids that takes both the energy balancing and system transients into account for optimisation Most cost-effective sizing and design of the energy storage system.
Location, weather, and load variations do not affect the optimisation speed and convergence level.
What you’ll bring
- Optimization, Electrical Power Engineering
- Smart Grid with Renewable Energy, Python Programming
- BSC./BTech/MTech/MSc in Electrical Power Engineering
At a glance
- Position type
- PhD
- Institution
- BITS Pilani / RMIT
- Department
- Not stated
- Research group
- Not stated
- Location
- India and Australia
- Supervisor / contact person
- Pratyush Chakraborty, Dr Manoj Datta, Senior Lecturer, HITESH DATT MATHUR, Dr Manoj Datta
- Funding
- Funding not stated
- Duration
- Not stated
- Expected start
- Not stated
- Vacancy reference
- BITSRMIT100059
Research focus
- Discipline
- Not stated
- Research area
- Energy storage
- Methods
- Not stated
- Software
- Python
Dates to know
- Listed on FOSS Positions
- 17 Sep 2026
- Original advertisement date
- Not stated in the source
- Application deadline
- Deadline not stated
- Priority review date
- Not stated
- Last checked
- 17 Sep 2026
- Last updated
- 17 Sep 2026
How to apply
Due to global warming, climate change, and the increased need for sustainability, the current power grid needs to be transformed by integrating more renewable energies. However, unlike traditional fossil-fuel-based power sources, renewable energy sources (RES) fluctuate with weather, are variable and are non-dispatchable. This variability and stochastic nature of RESs is a significant challenge for power grid integration. One possible solution is using large-scale energy storage systems (ESS), which will store and dispatch energy when necessary, thus reducing this variability. However, they still need to be cost-friendly. Microgrids, which are small formulations of the main grid grids with smaller RESs and ESS sizes, are becoming popular for integrating more renewable energies. Microgrids can operate independently or be connected to the main power grid. Designing and sizing an optimal microgrid involves many engineering constraints and parameters like voltage fluctuation, frequency deviations, system reliability, cost, and solving nonlinear power flow equations, which presents a complex optimisation problem. This PhD project aims to find the best solution to this optimisation problem. The objective is to identify and apply an efficient and robust optimisation algorithm to handle all the uncertainties related to the RES and tackle the engineering constraints and solve nonlinear power flow equations fast enough for better convergence.
Contact: pchakraborty@hyderabad.bits-pilani.ac.inmanoj.datta@rmit.edu.aumathurhd@pilani.bits-pilani.ac.inContact: pchakraborty@hyderabad.bits-pilani.ac.inContact: manoj.datta@rmit.edu.auContact: 9694096451Contact: mathurhd@pilani.bits-pilani.ac.in
Original sources
https://bitspilaniedu.com/rmit/bitsrmitphdwebsite/ResearchProjectDetail.aspx?progCode=123 ↗
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