EV Charging Station Load Modelling in MATLAB: Impact on Distribution Networks

EV Charging Station Load Modelling in MATLAB: Impact on Distribution Networks is most useful as a research topic when the simulation is treated as an experiment rather than a demonstration. The central objective is aggregated EV-charging demand and its effect on a distribution feeder. A strong study fixes the plant and test conditions, defines a baseline, changes one research factor at a time and reports numerical evidence alongside plots.

For doctoral and postgraduate work, the model should make every assumption visible: rated values, data sources, solver settings, controller sampling, initial conditions, boundary conditions and disturbance definitions. This makes the results easier to defend in a thesis, reproduce later and convert into a publication-oriented comparison.

1. Choose a distribution feeder and validate base-case load flow.
2. Create EV arrival, dwell-time, battery SOC and charger-power distributions.
3. Aggregate uncontrolled, time-of-use and smart-charging scenarios.
4. Run time-series power flow across representative days.
5. Measure feeder voltage, transformer loading and losses.
6. Add PV/BESS/V2G coordination as an extension.

Use numerical metrics that map directly to the research objective. Recommended outputs for this topic include:

• minimum bus voltage
• transformer peak loading
• feeder losses
• peak demand
• hosting capacity
• charging completion rate

To turn this topic into a stronger research contribution, start with one baseline and one proposed method, then extend the validation using probabilistic charging, price-responsive charging, V2G support. The final results section should explain why the proposed method changes the engineering behaviour, not only whether the output curve looks smoother. Include failure cases or operating limits when they reveal the boundary of the method.

• probabilistic charging
• price-responsive charging
• V2G support
• charger siting optimisation