top of page

Solar PV Powered EV Charging Station in MATLAB

Solar PV Powered EV Charging Station in MATLAB


Introduction

Electric vehicles (EVs) are a key component of the sustainable transport ecosystem. Integrating solar photovoltaic (PV) systems with EV charging stations enhances the sustainability of EV charging by utilizing renewable energy. Our goal today is to explore the MATLAB implementation of a solar PV-powered EV charging station, focusing on its block diagram and simulation.




Block Diagram

The block diagram of the solar-powered EV charging station includes:


PV Array: Captures solar energy.

DC-DC Converter: Steps up the voltage from the PV array.

Maximum Power Point Tracking (MPPT) Algorithm: Optimizes the power output from the PV array.

Stationary Storage Battery: Stores excess energy.

Bi-directional DC-DC Converter with DC Bus Voltage Controller: Manages power flow between the storage battery, the EV battery, and the DC bus.

Grid Integration: Connects the system to the grid for additional power supply or excess power export.

EV Battery: The battery of the electric vehicle being charged.


System Operation

Power Flow and Control

Solar Power Generation: The PV array generates power, which charges the stationary battery and, if an EV is connected, also charges the EV battery.

Battery Management

When PV generation is insufficient, the stationary battery supplies power to the EV battery.


If both the PV array and stationary battery are unable to supply enough power, the grid provides the necessary power.

If PV generation exceeds demand, excess power is exported to the grid.


Simulation Implementation

Our MATLAB simulation includes several key components:


Solar PV Array and Boost Converter: The PV array is connected to a boost converter, controlled by an Adaptive Neuro-Fuzzy Inference System (ANFIS) MPPT to maximize power output.

Stationary Battery with Bi-directional Converter: Manages energy storage and discharge to maintain the DC bus voltage around 500V.

EV Battery with Bi-directional Converter: Similar to the stationary battery setup, it ensures the EV battery is charged efficiently.

Grid Integration with Single-Phase Inverter: Uses a Phase-Locked Loop (PLL) for synchronization and neural networks for grid control.


Detailed Simulation Components


Solar PV System

ANFIS MPPT: This MPPT controller takes irradiance and temperature as inputs to determine the maximum power point voltage, which is compared with the actual PV voltage to control the boost converter.

Boost Converter: Steps up the voltage from the PV array, controlled by a PI controller and PWM generator.


Stationary and EV Batteries

Bi-directional DC-DC Converter: Controls the power flow to and from the batteries, maintaining a stable DC bus voltage.

Voltage Control: Ensures the DC bus voltage remains at 500V using a PI controller and PWM generator.


Grid Integration

Single-Phase Inverter: Manages power flow to and from the grid.

Neural Network-Based Control: Generates reference currents based on PV power and battery state of charge (SOC) to control the inverter.


Simulation Results

Case 1: High SOC (90%) for Stationary Battery, Low SOC (9%) for EV Battery

Initial Conditions: The PV array generates 2000W.

Operation:

The stationary battery discharges to supply the EV battery.

The EV battery charges efficiently, with SOC increasing from 9%.

Excess power is supplied to the grid when available.

Case 2: Moderate SOC (40%) for Stationary Battery, Low SOC (<10%) for EV Battery

Initial Conditions: The PV array generates 2000W, which fluctuates due to changing irradiance.

Operation:

The stationary battery and grid supply power to the EV battery.

SOC of the stationary battery decreases, indicating discharge.

The grid supplements power as needed based on PV generation.

Case 3: Low SOC (10%) for Both Batteries

Initial Conditions: Both batteries have low SOC.

Operation:

Both batteries charge, drawing power from the PV array and grid.

SOC of both batteries increases, indicating successful charging.

The grid supplies additional power due to low PV output.


Conclusion

The MATLAB simulation demonstrates the effective operation of a solar PV-powered EV charging station. By integrating advanced control systems such as ANFIS MPPT and neural network-based energy management, the system ensures efficient power distribution and utilization. This simulation provides valuable insights into the practical implementation and benefits of renewable energy integration with EV charging infrastructure.

0 views0 comments

Comments


bottom of page