Evaluation of Optimum MPPT Controllers for PV Cells using Matlab Simulink Platform

Abstract

Nowadays, the Photovoltaic cell is one of the most essential parts in the electrical field to convert photo light to voltage and current, at the desired output voltage and frequency by using various control techniques The Solar panel can produce maximum power at a particular operating point called Maximum Power Point (MPP).To produce maximum power and to get maximum efficiency, the entire photovoltaic panel must operate at this particular point. Maximum power point of PV panel keeps on changing with changing environmental conditions such as solar irradiance and cell temperature. Thus to extract maximum available power from a PV module, MPPT algorithms are implemented. The output power of a photovoltaic (PV) module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement MPPT controllers to obtain the maximum power of a PV system regardless of variations in climatic conditions. This project reviews the most used MPPT algorithms, which are Perturb and observe (P&O), Incremental conductance method (ICM), and Fuzzy logic control (FLC).

Introduction

I. INTRODUCTION

Renewable energy also called non-conventional type of energy sources are the sources which are continuously replenished by natural processes. Solar energy, bio-energy (bio-fuels grown sustainably), wind energy and hydropower etc., are some of the examples of renewable energy sources .

Photovoltaic (PV) offers an environmentally friendly source of electricity since it is clean, pollution-free, and inexhaustible.

However, the output from a PV solar cell alone is not good enough to input into an electricity bank or the main grid because its output is not constant in terms of voltage.

This raises a need to design a controller which can calculate and extract the maximum power point (MPP) at any instant from the solar cells. Maximum Power Point Tracking, frequently referred to as MPPT is an electronic system that operates the Photovoltaic (PV) modules in a manner that allows the modules to produce all the power they are capable of at that time.

II. SOLAR ENERGY

Solar energy is a non-conventional type of energy. Solar energy has been harnessed by humans since ancient times using a variety of technologies. Solar powered electrical generation relies on photovoltaic system and heat engines. To harvest the solar energy, the most common way is to use photo voltaic panels which will receive photon energy from sun and convert to electrical energy. Solar technologies are broadly classified as either passive solar or active solar depending on the way they detain, convert and distribute solar energy.

Active solar techniques include the use of PV panels and solar thermal collectors to strap up the energy. Passive solar techniques include orienting a building to the sun, selecting materials with favourable thermal mass or light dispersing properties and design spaces that naturally circulate air. Solar energy has a vast area of application such as electricity generation for distribution, heating water, lighting building, crop drying etc.

The comparison between different photovoltaic cells can be done on the basis of their performance and characteristic curve. The parameters are always given in datasheet. The datasheet make available the notable parameter regarding the characteristics and performance of PV cells with respect to standard test condition. Standard test conditions are as follows:

Temperature (Tn) = 250C

Irradiance (Gn) = 400 W/m2.

III. PROBLEM STATEMENT

Photovoltaic (PV) systems have become an important source of power for a wide range of applications. Unfortunately, PV generation systems have two major problems: the conversion efficiency of electric power generation is very low (9-17%), especially under low irradiation conditions, and the amount of electric power generated by solar arrays changes continuously with weather conditions. Moreover, the solar cell V-I characteristic is nonlinear and varies with irradiation and temperature.

IV. PROJECT OBJECTIVES

The primary objective of this project is to design an MPPT controller for photovoltaic systems.

In addition, this project has various objectives, which comprise of:

1) To design the optimum controller by simulation for the maximum power point tracking.

2) To analyze simulation results of the maximum power point  tracking.

V. MAXIMUM POWER POINT TRACKING

Maximum power point plays an important role in photovoltaic system because they maximize the power output from a PV system for a given set of conditions, and therefore maximize the array efficiency. The different methods

used to track the maximum power point are:

(i) Perturb and Observe method

(ii) Incremental Conductance method

(iii) Parasitic Capacitance method

(iv) Constant Voltage method

(v) Intelligent Control methods (Fuzzy Logic, Artificial Neural Network and Genetic Algorithms etc).

A. Perturb and Observe Algorithm:

The Perturb and Observe ( P&O) algorithm is an extensively habituated system of Maximum Power Point Tracking( MPPT) used to control the power affair of a photovoltaic( PV) system. It's a simple and robust algorithm that's generally used in small-scale PV systems. The P&O algorithm works by continually conforming the operating voltage of the PV array and measuring the corresponding power affair. The algorithm starts by setting the voltage to an original value and also perturbing the voltage slightly in one direction. However, the algorithm continues to undo MPPT the voltage in that direction, If the power affair increases. However, if the power affair diminishes, the algorithm changes direction and starts perturbing the voltage in the contrary direction. This process continues until the maximum power point is reached.

The principle of P&O is to create a perturbation by decreasing or increasing the duty cycle of boost converter and then observing the direction of change of PV output. If at any instant k, the output PV power P(k) & voltage V(k) arengreater than the previous computed power P(k−1) & V(k-1), then the direction of perturbation is maintained, otherwise it is reversed.

Conclusion

This paper presents an evaluation comparision of optimum mppt controllers for pv cell using matlab simulink platform which represents the output power of a photovoltaic (PV) module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement MPPT controllers to obtain the maximum power of a PV system regardless of variations in climatic conditions which proves Fuzzy controller shows better performance with lower oscillation.

References

[1] J.A. Ramos, I. Zamora, J.J. Campayo. “Modeling of Photovoltaic Module”, International Conference on Renewable Energies and Power Quality (ICREPQ’10) Granada, Spain, 23-25 March 2010. [2] N. Pandiarajan and Ranganath Muthu, “Mathematical Modeling of Photovoltaic Module with Simulink”,International Conference on Electrical Energy Systems, 3-5 Jan 2011. [3] G. Venkateswarlu, P.Sangameswar Raju, “Simcape Model of Photovoltaic Cell”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 2, Issue 5, May 2013. [4] Athimulam Kalirasu and Subharensu Sekar Dash, “Simulation of Closed Loop Controlled Boost Converter for Solar Installation”, Serbian Journal of Electrical Engineering, Vol. 7, No. 1, May 2010.

Copyright

Copyright © 2024 Ongker Das, Dr. Alok Kumar Mohanty. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.