PID Tuning for Solar PV System with MPPT in MATLAB: A Step-by-Step Guide

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1 day ago
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Tuning a PID controller in a solar photovoltaic (PV) system with Maximum Power Point Tracking (MPPT) is critical for maintaining optimal energy extraction under dynamic environmental and load conditions. In this blog post, we walk through the key design considerations, MPPT implementation, and the PID tuning process using MATLAB/Simulink.

Designing the Boost Converter for Solar PV

To begin, the solar PV panel characteristics are defined as follows:

Open Circuit Voltage (Voc): 70 V
Voltage at Maximum Power Point (Vmp): 60 V
Short Circuit Current (Isc): 5.1 A
Current at Maximum Power Point (Imp): 4.2 A

The system is configured to step up the voltage from 60 V to 120 V using a boost converter. Based on these parameters, the values for the inductor (L) and capacitor (C) are calculated using standard boost converter design equations, considering a switching frequency of 10 kHz. Load resistance (R) and duty cycle (D) are also determined.

Implementing Incremental Conductance (INR) MPPT Algorithm

The Incremental Conductance method is used for MPPT. The algorithm requires:

PV voltage and current measurements,
Initial, maximum, and minimum voltage reference values (e.g., Vmax ≈ 62 V, Vmin ≈ 55 V).

The algorithm continuously monitors the changes in voltage (ΔV), current (ΔI), and power (ΔP). Based on these changes:

If ΔV = 0 and ΔP = 0 → the system is at MPP.
If ΔP > 0 → increase voltage reference.
If ΔP < 0 → decrease voltage reference.

All reference and previous values are updated in each iteration until the system reaches and maintains maximum power extraction.

Using PID Controller for Voltage Regulation

The MPPT algorithm produces a reference voltage, which is then compared with the actual PV voltage. The error is fed into a PID controller that adjusts the duty cycle of the boost converter.

Initial PID gains (Kp and Ki) are set to default values. However, to improve system performance, PID tuning is necessary.

PID Tuning Using MATLAB Simulink

The Simulink PID Tuner is used for automated tuning:

Identify the Plant Model: Use the built-in "Identify New Plant" feature by applying a step input (e.g., from 0.2 to 0.6) and collecting I/O data.
Auto-Estimate Transfer Function: The software estimates the system’s transfer function based on the data. You can select one-pole or higher-order models.
Apply Gains: The tool calculates optimal PID parameters (Kp, Ki) and applies them to the controller block.
Simulate and Verify: After updating the PID values, simulate the system to verify stability, fast response, and minimal overshoot.

You can iterate this tuning process to refine the control parameters further.

System Testing Under Dynamic Conditions

Two test scenarios are simulated:

Variable Irradiance: The solar irradiance is changed every 2 seconds (e.g., 1.0 to 8.6 to 6.4 Sun levels).
Variable Load: The system load is altered every 3 seconds.

Results show that:

The PV system consistently operates near the maximum power point,
The PID controller adapts well to both irradiation and load changes,
Boost converter output remains stable and within the desired voltage range.

Conclusion

This demonstration highlights how properly tuning a PID controller—alongside a well-designed MPPT algorithm—enables a solar PV system to operate at peak efficiency, even under fluctuating environmental and load conditions. MATLAB/Simulink offers a powerful toolkit for system identification, controller design, and performance verification, making it ideal for research and real-time solar applications.