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MATLAB Implementation of Power Management in PV Wind Battery DC Microgrid

Wind Power Generation and Boost Converter Design

The wind power generation system in the model is rated at 3,000 W. The goal is to maintain a DC bus voltage of around 400V. Since the wind generator output varies, a permanent magnet generator (PMG) is used, which is then rectified to DC using a diode rectifier. However, the rectified voltage is not sufficient, requiring a boost converter to elevate it to 400V.

The design of the boost converter involves calculating appropriate inductor (L) and capacitor (C) values. The key parameters considered include:

  • Wind generator rated power: 3,000 W

  • Input voltage: approximately 250V

  • Switching frequency: 5 kHz

  • Desired output voltage: 400V

Standard boost converter formulas are used to determine the required L and C values to ensure efficient operation with minimal ripple.



PV Panel Integration and Boost Converter Design

A solar PV panel rated at 200 W is also integrated into the microgrid. The PV panel’s input voltage typically hovers around 245–250V. Like the wind system, a boost converter is designed for the PV panel to raise its output to the stable 400V DC bus.

The boost converter design process again involves calculating L and C based on:

  • PV input voltage

  • Output voltage

  • Switching frequency

  • Acceptable ripple percentages

This ensures the PV system can contribute power effectively to the microgrid without causing voltage instability.

Bidirectional Converter for Battery Management

The microgrid also includes a battery system, consisting of batteries with a nominal voltage of around 20V, configured to achieve an effective voltage of approximately 240V. The battery is interfaced with the DC bus through a bidirectional converter, which primarily operates in boost mode to raise the battery voltage to 400V.

The bidirectional converter is designed based on parameters similar to the boost converter, with careful attention to the direction of current flow depending on whether the battery is charging or discharging.



MPPT Control Using Perturb and Observe (P&O) Method

To maximize the energy harvested from the PV panels, a Maximum Power Point Tracking (MPPT) algorithm based on the Perturb and Observe (P&O) method is implemented.

The MPPT process involves:

  • Measuring PV voltage and current

  • Calculating power and observing changes in power and voltage

  • Adjusting the duty cycle of the boost converter based on the change in power and voltage

  • Ensuring the duty cycle stays within predefined maximum and minimum limits

  • Continuously updating previous measurements to track the maximum power point

This method helps the PV system operate efficiently even under varying irradiance conditions.

MPPT Control Using Incremental Conductance (INC) Method

An alternative MPPT strategy used is the Incremental Conductance (INC) method. This approach improves accuracy under rapidly changing environmental conditions.

The INC method involves:

  • Calculating the rate of change of power with respect to voltage

  • Making finer adjustments to the duty cycle based on the relationship between current and voltage changes

  • Maintaining or adjusting the duty cycle to stay near the maximum power point

  • Updating parameters for real-time tracking

Both MPPT methods ensure that the PV system consistently delivers maximum available power to the microgrid.

DC Bus Voltage Control with PI Controller

Maintaining the DC bus voltage at 400V is critical for stable microgrid operation. A Proportional-Integral (PI) controller is used for voltage regulation.

The voltage control strategy involves:

  • Measuring the DC bus voltage

  • Comparing it with the reference voltage (400V)

  • Using a PI controller to adjust the duty cycle of the bidirectional converter

  • Generating appropriate pulses to control the IGBTs (Insulated Gate Bipolar Transistors)

This control loop ensures the DC bus voltage remains stable despite fluctuations in source power or load demands.

Simulation Results and Observations

The model simulation includes variations in solar irradiance — from 1,000 W/m² down to 10 W/m². The key observations are:

  • At high irradiance (1,000 W/m²), the PV generates about 2,000 W.

  • At medium irradiance (500 W/m²), PV generation drops to around 1,000 W.

  • At very low irradiance (10 W/m²), PV generation falls to zero.

These variations directly impact battery behavior:

  • When PV generation is high, the battery charges.

  • When PV generation drops, the battery discharges to maintain load power.

  • The battery switches dynamically between charging and discharging modes based on available power.

Meanwhile, the wind generator consistently produces around 2,700–2,800 W. However, since the load is 3,000 W, the battery frequently compensates for the shortfall.

Conclusion

This MATLAB model demonstrates effective power management in a PV-wind-battery DC microgrid. Through careful design of converters, implementation of MPPT algorithms, and robust voltage control strategies, the system maintains a stable DC bus voltage and reliably powers a constant DC load.

The battery plays a crucial role in balancing power fluctuations from renewable sources, ensuring continuous and stable operation of the microgrid even under varying environmental conditions.

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