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MATLAB Implementation of PO MPPT algorithm for Solar PV System

MATLAB Implementation of PO MPPT algorithm for Solar PV System

This video present about MATLAB Implementation of P&O MPPT algorithm for Solar PV System. In this work, perturb and observe maximum power point tracking controllers are utilized to extract the maximum power from the solar PV panel. The P&O algorithms operate by periodically perturbing i.e. incrementing or decrementing the array terminal voltage or current and comparing the PV output power with that of the previous perturbation cycle. If the PV array operating voltage changes and power increases dP/dV greater than 0, the control system moves the PV array operating point in that direction; otherwise, the operating point is moved in the opposite direction. In the next perturbation cycle, the algorithm continues in the same way. A common problem in PO algorithms is that the array terminal voltage is perturbed every MPPT cycle; therefore when the MPP is reached, the output power oscillates around the maximum, resulting in power loss in the PV system. Perturb & Observe is the simplest method and is widely used. In this technique we generally use two sensors, that is the voltage sensor, to sense the PV module voltage and current sensor to sense the PV current and hence the cost of implementation is less and hence easy to implement without any complexity. In certain situations like changing atmospheric conditions and change in irradiance the maximum power point shifts from its normal operating point on the PV curve. In the next iteration, it changes its direction and goes away from the maximum power point and results in multiple local maxima at the same point. So the maximum power point deviates from its original position.

Algorithm for Perturb and Observe Technique:

a. Read the value of current and voltage from the solar PV module.

b. Power is calculated from the measured voltage and current.

c. The value of voltage and power at kth instant are stored.

d. Then next values at k+1th instant are measured again and power is calculated from the measured values.

e. The power and voltage at k+1th instant are subtracted with the values from kth instant.

f. In the power voltage curve of the solar PV module, it is inferred that in the right-hand side curve where the voltage is almost constant and the slope of power voltage is negative dP/dV less than 0 whereas on the left-hand side, the slope is positive dP/dV greater than 0. Therefore the right side of the curve is for the lower duty cycle nearer to zero whereas the left side curve is for the higher duty cycle nearer to unity.

g. Depending on the sign of dP i.e. P k+1 – P k and dV i.e. V k+1 –V k after subtraction the algorithm decides whether to increase the duty cycle or to reduce the duty cycle.


Implementing the Perturb and Observe (P&O) MPPT Algorithm for Solar PV Systems in MATLAB

Introduction

In this article, we will discuss the implementation of the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) algorithm for a solar photovoltaic (PV) system using MATLAB. The P&O algorithm is commonly used to optimize the power output of solar PV panels by continuously adjusting the operating point to track the maximum power point (MPP) under varying environmental conditions.

Overview of the System:

We will start by assembling the model for the solar PV system using MATLAB. The system includes a solar PV panel and a boost converter placed between the load and the panel. The objective is to implement the P&O algorithm to efficiently extract maximum power from the solar panel.

PV Panel Details

For our implementation, we will consider a 250-watt solar PV panel with the following characteristics:

  • Maximum Power: 250 watts

  • Open Circuit Voltage: 37.3 volts

  • Voltage at MPP: 30.7 volts

  • Short Circuit Current: 6.66 amperes

  • Current at MPP: 0.915 amperes

Algorithm Implementation

  1. PV Panel Measurement: Voltage and current are measured from the solar PV panel, which serves as input for the P&O algorithm.

  2. Algorithm Initialization: The initial duty cycle is set to 0.42, with a maximum duty cycle of 0.8 and a minimum duty cycle of 0.08. Incremental duty cycle change is set to 0.0005.

  3. Power and Voltage Difference Calculation: The power and voltage differences between the current and previous instances are calculated.

  4. P&O Logic: Based on the calculated differences, the algorithm determines whether to increase or decrease the duty cycle to track the MPP.

  5. Duty Cycle Limit Check: The calculated duty cycle is compared with the maximum and minimum limits. If it exceeds these limits, the duty cycle is adjusted.

  6. Storing Previous Values: The current values of voltage, power, and duty cycle are stored as previous values for the next iteration.

Testing the Algorithm

We will test the P&O algorithm implementation under two scenarios:

  1. Variable Load: We'll keep irradiation and temperature constant and vary the load resistance from 5 ohms to 100 ohms. The algorithm should adjust the duty cycle to maximize power extraction.

  2. Variable Irradiation: The load resistance is fixed, and we'll vary the irradiation levels from 1000 W/m² to 400 W/m². The algorithm should adapt to changing irradiation levels and track the MPP.

Simulation and Results

Simulating the implemented model reveals that the P&O algorithm effectively tracks the MPP under varying load and irradiation conditions. The algorithm adjusts the duty cycle to extract maximum power from the solar PV panel.

Conclusion

he Perturb and Observe (P&O) algorithm is a widely used method for maximizing power extraction from solar PV panels. By implementing the algorithm in MATLAB, we demonstrated its ability to adapt to changing environmental conditions and efficiently optimize power output. This approach helps enhance the performance and efficiency of solar PV systems, making them more reliable and effective in generating renewable energy.


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