IEEE 39 Bus System with PV & EV Charging - MATLAB Simulink Simulation: Research Methodology and Simulation Guide

Research problem and objective

A suitable research question is: how can the EV Charging & Grid Integration approach represented by “IEEE 39 Bus System with PV & EV Charging - MATLAB Simulink Simulation” be evaluated using MATLAB Simulink so that voltage deviation and frequency nadir are improved or maintained without creating unacceptable degradation in RoCoF?

The objective should be written before the final model is tuned so that the selected MATLAB Simulink parameters, test cases and plots remain aligned with the research question.

Model architecture and implementation plan

The IEEE 39 Bus System with PV & EV Charging - MATLAB Simulink Simulation workflow should keep the model modular enough to support baseline comparison, sensitivity testing and parameter revision. The main architecture elements are:

• PV array
• MPPT algorithm
• DC-DC converter
• DC-link capacitor
• Grid inverter or load
• Irradiance, voltage, current and power scopes

Recommended methodology

1. Set PV module and environmental parameters. Relate the step to the EV Charging & Grid Integration objective and record the relevant parameters.
2. Implement the MPPT algorithm and converter. Relate the step to the EV Charging & Grid Integration objective and record the relevant parameters.
3. Apply irradiance and temperature changes. Relate the step to the EV Charging & Grid Integration objective and record the relevant parameters.
4. Measure tracking convergence and DC-link response. Relate the step to the EV Charging & Grid Integration objective and record the relevant parameters.
5. Validate delivered power and controller robustness. Relate the step to the EV Charging & Grid Integration objective and record the relevant parameters.

Study cases for comparative research

A single nominal run is not enough for a defensible research conclusion. Suitable cases for this topic include:

• nominal charge/discharge operation
• step change in load or charging demand
• different initial SOC conditions
• power or current limit activation
• a stressed thermal or parameter-variation case

Outputs and quantitative validation

The recommended validation evidence includes voltage deviation, frequency nadir, RoCoF, settling time. A defensible result section should report both waveform or field behaviour and numerical metrics, with the baseline and proposed cases evaluated under the same conditions. The final discussion should also explain sensitivity to different initial SOC conditions, power or current limit activation.

• PV voltage and current
• PV power and MPP tracking
• Duty cycle / control signal
• DC-link voltage
• Grid/load active power

Useful validation metrics

Novelty directions for thesis or journal work

Any extension should respond to a specific limitation in the baseline method and be tested with the same operating conditions. Relevant directions include:

• adaptive, predictive or robust alternative to the baseline method
• sensitivity and uncertainty analysis
• multi-objective optimization with explicit constraints
• real-time, HIL or experimental validation where feasible

Applications and research relevance

• renewable-rich power systems
• microgrid planning and control
• low-inertia stability studies
• protection, operation and grid-support research

For PhD researchers and postgraduate scholars working internationally, this topic can be adapted to a university proposal, published reference paper or independently defined research gap. The model scope can be aligned with the required software version, parameter set, dataset, disturbance profile, geometry, controller structure and reporting format while preserving reproducibility and clear technical attribution.

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