PV Wind Battery Based DC Microgrid PO MPPT in MATLAB

PV Wind Battery Based DC Microgrid PO MPPT in MATLAB

Introduction:

We delve into a simulation model featuring an integrated PV (Photovoltaic), wind, and battery-based DC microgrid. This model illustrates the dynamic behavior of a sustainable energy system, combining power generation from solar and wind sources with energy storage capabilities. Let's delve into the components and operational aspects of this simulation.

Simulation Model Components:

1. Wind Power Generation:

• Features a Permanent Magnet Synchronous Generator (PMSG) coupled with a wind turbine model.

• Utilizes a Universal Bridge and Boost Converter to convert the generated AC power to DC.

• Boost converter is controlled by a Perturb and Observe Maximum Power Point Tracking (P&O MPPT) algorithm to optimize wind power extraction.

• Three inputs, including wind speed, generated speed, and pitch angle, influence the wind turbine model.

1. Photovoltaic Power Generation:

• Consists of an array of solar panels connected in series and parallel.

• A Boost Converter is employed to step up the voltage from the PV panels.

• Similar to wind power, a P&O MPPT algorithm is applied for maximum power extraction.

1. Battery Energy Storage System:

• A bidirectional converter connects the battery to the DC bus.

• Voltage control of the converter is facilitated by a Proportional-Integral (PI) controller, maintaining the DC bus voltage at a set level.

• The battery ensures power balance and continuity in supply during fluctuations in renewable energy generation.

1. DC Microgrid:

• The DC bus serves as the common platform for integrating power from wind, PV, and battery sources.

• Load demand is met by the collective contribution of wind, PV, and battery systems.

Simulation Dynamics:

1. Wind Power Operation:

• Wind turbine model dynamically adjusts to wind speed variations.

• P&O MPPT algorithm optimizes the boost converter for maximum power extraction.

• The generated power is injected into the DC microgrid.

1. PV Power Operation:

• Solar panels respond to varying irradiation levels.

• P&O MPPT algorithm adjusts the boost converter for optimal power conversion.

• Extracted power contributes to the DC microgrid.

1. Battery Operation:

• Bidirectional converter ensures charging and discharging based on the power balance.

• PI controller maintains DC bus voltage, supporting stability in the microgrid.

1. System Response to Changing Conditions:

• Simulation accounts for changes in wind speed and irradiation levels.

• Results showcase the adaptability of the microgrid to varying environmental conditions.

Simulation Results:

1. Power Generation:

• PV and wind systems operate at maximum power points.

• Battery operations demonstrate dynamic charging and discharging patterns.

1. DC Bus Voltage Control:

• PI controller effectively maintains the DC bus voltage at the desired level.

1. Load Supply:

• Load demand is met through the collective contribution of wind, PV, and battery systems.

Conclusion:

This simulation model exemplifies the efficacy of an integrated PV, wind, and battery-based DC microgrid. The combination of renewable energy sources and energy storage enhances grid stability and resilience.