top of page
Search

# Grid Connected PV System with Neural Network MPPT

Grid Connected PV System with Neural Network MPPT

## Explanation of the Simulation Model

This model is developed for a grid-connected PV system with ANN MPPT. The model consists of:

• Main Grid: 154 MW, 34 kW.

• Transformer: 34 kW to Volt transformer.

• AC Load:

• Load 1: 500 kW

• Load 2: 30 kW

• Both loads have a rating of 400V line-to-line RMS and 50 Hz.

### Solar PV Array

The PV array in this model includes:

• Panel Power: 414 watts per panel

• Open Circuit Voltage: 85.3V

• Voltage at Maximum Power Point: 72.9V

• Short Circuit Current: 6.09A

• Current at Maximum Power Point: 5.69A

• Temperature Coefficients:

• Voltage: -0.229%/Â°C

• Current: 0.03%/Â°C

A total of 41 kW PV panels are used, arranged in series and parallel to match the grid requirements.

## ANN MPPT Implementation

### Data Collection and Training

For the neural network MPPT, we need to measure the irradiation and temperature. Based on these measurements, the reference voltage is generated.

1. Data Collection:

• Short Circuit Current: 6.09A

• Current at Maximum Power Point: 5.69A

• Open Circuit Voltage: 85.3V

• Voltage at Maximum Power Point: 72.9V

• Temperature Coefficients:

• Voltage: -0.229%/Â°C

• Current: 0.03%/Â°C

1. Input and Output Data:

• Input: Irradiation and temperature

• Output: Reference voltage (Maximum Power Voltage)

1. Training the Neural Network:

• Collected 1000 samples with varying temperature (15-35Â°C) and irradiation (0-1000 W/mÂ²).

• Used the standard solar PV equations to generate input data for the neural network.

### Neural Network Training

• Input Data: Irradiation and temperature

• Target Data: Reference voltage

• The neural network is trained to match the input data with the output reference voltage. The model's accuracy is validated with an R-value close to 1, indicating a good fit.

## Simulation of the Grid Connected PV System

### Constant Irradiation and Temperature

1. Initial Setup:

• Irradiation: 1000 W/mÂ²

• Temperature: 25Â°C

1. Simulation Results:

• Maximum Power from PV: ~41 kW

• Load 1 Power: ~30 kW

• Load 2 Power: ~10 kW

• Grid Power: Remaining power supplied to the grid or received from the grid.

### Changing Load Conditions

1. New Load Setup:

• Load 1: 20 kW

• Load 2: 10 kW

• Total Load: 30 kW

1. Simulation Results:

• PV Power: ~40 kW

• Excess power (10 kW) supplied to the grid.

### Varying Irradiation

1. Changing Irradiation:

• Initial Irradiation: 1000 W/mÂ²

• Reduced to: 500 W/mÂ² at 0.3 seconds

1. Simulation Results:

• PV Power drops from ~40.65 kW to ~20.2 kW.

• Grid compensates for the reduced power to meet the load requirements.

## Explanation of Inverter Control

1. Inverter Control Logic:

• Measures irradiation and temperature to provide the reference voltage.

• DC link voltage is regulated based on this reference voltage.

• Real power from the PV is sent to the grid while ensuring reactive power (IQ reference) is zero.

1. Control Voltage:

• Generated in the form of VD and VQ.

• Converted to ABC form for modulation.

• Sinusoidal three-phase voltages are generated and multiplied with magnitude to control the inverter.

## Conclusion

Using ANN MPPT, we effectively extract maximum power from the solar PV system. The system adjusts to varying irradiation conditions and load requirements, ensuring efficient power management between the PV system and the grid.

10 views0 comments

bottom of page