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:
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.
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.
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.
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:
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.
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.
Battery Operation:
Bidirectional converter ensures charging and discharging based on the power balance.
PI controller maintains DC bus voltage, supporting stability in the microgrid.
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:
Power Generation:
PV and wind systems operate at maximum power points.
Battery operations demonstrate dynamic charging and discharging patterns.
DC Bus Voltage Control:
PI controller effectively maintains the DC bus voltage at the desired level.
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.