Comparison And Implementation Of Maximum Power Point Techniques Of A Pv Solar System (Using Perturb And Observe, Incremental Conductance, Modified Perturb, Fuzzy Logic And Artificial Neural Network)

Electrical Electronics Engineering | Industrial Physics | Engineering

The comparison and implementation of various maximum power point techniques for a PV solar system, including Perturb and Observe (P&O), Incremental Conductance (IncCond), Modified Perturb, Fuzzy Logic, and Artificial Neural Network (ANN), are essential for optimizing energy extraction from solar panels. P&O method involves continuously adjusting the operating point to track the maximum power, while IncCond method enhances P&O by considering changes in conductance. Modified Perturb approach refines P&O by mitigating oscillations around the maximum power point. Fuzzy Logic utilizes linguistic variables to adaptively adjust the operating point, offering robustness to changing environmental conditions. Lastly, ANN leverages machine learning to predict and optimize the maximum power point based on historical data. Implementing these techniques requires careful consideration of their respective advantages, such as efficiency, accuracy, and computational complexity, to determine the most suitable approach for specific solar system configurations and environmental factors.

ABSTRACT

The working behavior of a module / PV array is non-linear and highly dependent on working conditions. As a given condition, there is only one point at which the level of available power at its output is maximum. This point varies with time, enlightenment and temperature. To ensure optimum operation, the use of MPPT control allows us to extract the maximum power. This paper presents a comparative study of four widely-adopted MPPT algorithms, such as Perturb and Observe, Incremental Conductance, Measurements of the variation of the open circuit voltage or of the short-circuit current. Their performance is evaluated using, for all these techniques. In particular, this study compares the behaviors of each technique in presence of solar irradiation variations and temperature fluctuations. These MPPT techniques will be compared using the Matlab / Simulink tool.

CHAPTER ONE

1.0 INTRODUCTION

Solar energy is one of the most important renewable energy sources. As opposed to the conventional non renewable sources such as gasoline, coal, etc. solar energy is clean, inexhaustible and free. Unfortunately, PV generation systems have two major problems: the conversion efficiency in electric power generation is low and the amount of electric power generated by solar module changes continuously with weather conditions. Moreover, the solar cell V-I characteristic is nonlinear and changes with irradiation and temperature. In general, there is a point on the V-I or V-P curve only, called the Maximum Power Point (MPP), at which the entire PV system operates with maximum efficiency and produces its maximum output power. The location of the MPP is not known, but can be located, either through calculation models or by search algorithms. Maximum Power Point Tracking (MPPT) techniques are used to maintain the PV module’s operating point at its MPP.

Many MPPT techniques have been proposed in the literature; like Incremental conductance method, Perturb and Observe method, Artificial Neural Network method, the Fuzzy Logic method, etc..But, The tracking of MPP has not yet been done ,on the P-V or I-V Curve and conventional P&O has drawbacks such as low tracking speed do not track the exact maximum power point during sudden changes of irradiation and temperature. So in this paper Modify the perturb and observe, incremental conductance, modified perturb, fuzzy logic and artificial neural network methods using MATLAB Programming/Simulink Results.

1.2 AIM OF THE STUDY

In this study, different techniques of achieving maximium power of pv solar system are perturb and observe, incremental conductance, modified perturb, fuzzy logic and artificial neural network. The main aim of this work is to compare and implement these methods.

1.3 OBJECTIVE OF THE STUDY

At the end of this work, student involved will be able:

To define and discuss the different methods used in this work
To understand different MPPT algorithms commonly

To know the different among the techniques used

1.4 PURPOSE OF THE STUDY

The purpose of this paper is to study and compare five maximum power point tracking, (MPPT) algorithms in a photovoltaic simulation system. The Matlab/Simulink is used in this paper to establish a model of photovoltaic system with MPPT function. This system is developed by combining the models of established solar system.

1.5 SCOPE OF THE PROJECT

Maximum power point tracking (MPPT) is an essential part of the photovoltaic (PV) system to ensure that the power converters operate at the maximum power point (MPP) of the solar array. Various MPPT algorithms have been developed in [1]-[3]. In the P&O method, the voltage is being increased or decreased with a fixed step size in the direction of reaching the MPP. The process is repeated periodically until the MPP is reached. At steady state, the operating point oscillates around the MPP.

CHAPTER FIVE

5.1 CONCLUSION

The daily increase in the number of PV systems in different areas has resulted in extensive research for finding answers to energy and environmental problems. In this perspective, the MPPT methods play a very vital role to extract the maximum power available from PV system. This article offers an insight into various MPPT used in PV system. An effort has been made to point out the advantages and shortcomings of various MPPT methods. This paper provides acumen to select a MPPT technique depending upon various constraints. The tables provide a wide-range guide for the operational choice of a MPPT technique based on all major factors like cost, efficiency, complexity etc. It is remarkable to point out that there are very slight variances in performances among the best studied MPPTs. This review has also encompassed recent hybrid MPPT methods along with original methods. Further, this assessment is expected to be very useful for not only the MPPT end users but also for the engineers, researchers and commercial producers of PV systems.

In this work, we presented a comparison of 5 MPPT algorithms. In the comparison, we used several parameters including the complexity of the system, number of sensors, kind of circuitry (digital or analog), tuning, convergence speed, and the dependency of the parameters. The results are shown in the table to serve the users to choose the suitable system that suits their specific applications.

The existing methods Incremental, perturb and observe and proposed method modified perturb and observe methods are compared. Here, the results indicate that PV conversion system using modified perturb and observe method which has higher conversion efficiency and it tracks the exact maximum power point at less time with higher tracking speed than Incremental conductance, perturb and observe method. Therefore, the modified Perturb and Observe method was best preferred due to its higher tracking speed and high conversion efficiency.

In this study, a fuzzy logic MPPT controller is proposed to extract maximum possible power from a photovoltaic array. The algorithm works as a direct method of MPPT through a buck-boost converter placed in parallel with the PV array. The proposed system is simulated and constructed in both simulation and hardware and its functionality was proven. The obtained results from simulation and experimental setup confirm that the designed system is fast, robust and efficient. The results also show the capability of the proposed FL MPPT system to track the voltage which is respective to the maximum output power. It results in increasing the efficiency of the PV panel and reducing the bad effects of weather changing as much as possible.