A Review on Photo Voltaic MPPT Algorithms

A photovoltaic generator exhibits nonlinear voltage-current characteristics and its maximum power point varies with solar radiation and cell temperature. A Dc/Dc power converter is used to match the photovoltaic system to the load and to operate the PV (photo voltaic) cell array at maximum power point. Maximum Power Point Tracking (MPPT) is a process which tracks one maximum power point from PV array input, varying the ratio between the voltage and current delivered to get the most power it can. There are different techniques proposed with lot of algorithms are being used in the MPPT controller to extract the maximum power. It is very difficult for the photo voltaic designers, researchers and academic experts to select a particular MPPT technique for a particular application which requires the background knowledge and comparative features of various MPPT algorithms. This paper will be avaluable source for those who work in the photo voltaic generation, so its objective is to review the main MPPT algorithms in practice and analyzes the merits and demerits with various factors

Current-Sensorless Control Strategy for the MPPT of a PV Cell:An Energy-Based Approach

A novel energy-based modelling and control strategy is developed and implemented to solve the maximum power point tracking problem when a photovoltaic cell array is connected to consumption loads. A mathematical model that contains key characteristic parameters of an energy converter stage connected to a photovoltaic cell array is proposed and recast using the port-Hamiltonian framework. The system consists of input-output power port pairs and storage and dissipating elements. Then, a current-sensorless control loop for a maximum power point tracking is designed, acting over the energy converter stage and following an interconnection and damping assignment passivity-based strategy. The performance of the proposed strategy is compared to a (classical) sliding mode control law. Our energy-based strategy is implemented in a hardware platform with a sampling rate of 122 Hz, resulting in lower dynamic power consumption compared to other maximum power point tracking control strategies. Numerical simulations and experimental results validate the performance of the proposed energy-based modelling and the novel control law approach

An improved search ability of particle swarm optimization algorithm for tracking maximum power point under shading conditions

Introduction. Extracting maximum possible power from solar energy is a hot topic of the day as other sources have become costly and lead to pollution. Problem. Dependency on sunlight for power generation makes it unfeasible to extract maximum power. Environmental conditions like shading, partial shading and weak shading are the major aspect due to which the output of photovoltaic systems is greatly affected. Partial shading is the most known issue. Goal. There have been many proposed techniques and algorithms to extract maximum output from solar resources by use of photovoltaic arrays but every technique has had some shortcomings that couldn’t serve the complete purpose. Methodology. Nature inspired algorithms have proven to be good to search global maximum in a partially shaded multipeak curve which includes particle swarm optimization, artificial bee colony algorithm, and flower pollination algorithm. Methods. Particle swarm optimization algorithm is best among these in finding global peaks with less oscillation around maximum power point, less complexity, and easy to implement nature. Particle swarm optimization algorithm has the disadvantage of having a long computational time and converging speed, particularly under strong shading conditions. Originality. In this paper, an improved opposition based particle swarm optimization algorithm is proposed to track the global maximum power point of a solar photovoltaic module. Simulation studies have been carried out in MATLAB/Simulink R2018a. Practical value. Simulation studies have proved that opposition based particle swarm optimization algorithm is more efficient, less complex, more robust, and more flexible and has better convergence speed than particle swarm optimization algorithm, perturb and observe algorithm, hill climbing algorithm, and incremental conductance algorithm.Вступ. Отримання максимально можливої потужності із сонячної енергії є надзвичайно актуальним наразі, оскільки інші джерела енергії стали коштовними та призводять до забруднення. Проблема. Залежність від сонячного світла для вироблення електроенергії унеможливлює отримання максимальної потужності. Умови навколишнього середовища, такі як затінення, часткове затінення і слабке затінення, є основним аспектом, від якого сильно залежить потужність фотоелектричних систем. Часткове затінення – найвідоміша проблема. Мета. Було запропоновано багато методів та алгоритмів для отримання максимальної віддачі від сонячних ресурсів за допомогою фотоелектричних батарей, але кожен метод мав деякі недоліки, які не могли служити досягненню повної мети. Методологія. Алгоритми, натхненні природою, виявилися хорошими для пошуку глобального максимуму на частково затіненій кривій з багатьма піками, включаючи оптимізацію рою частинок, алгоритм штучної бджолиної колонії та алгоритм запилення квітів. Методи. Алгоритм оптимізації рою частинок найкраще підходить для пошуку глобальних піків з меншими коливаннями навколо точки максимальної потужності, меншою складністю та простотою реалізації. Алгоритм оптимізації рою частинок має недолік, що полягає у тривалому часі обчислень та швидкості збіжності, особливо в умовах сильного затінення. Оригінальність. У цій статті пропонується покращений алгоритм оптимізації рою частинок на основі протилежності для відстеження глобальної точки максимальної потужності сонячного фотоелектричного модуля. Розрахункові моделювання проводились у MATLAB/Simulink R2018a. Практична цінність. Дослідження за допомогою моделювання довели, що алгоритм оптимізації рою частинок на основі протилежності є більш ефективним, менш складним, надійнішим і гнучкішим і має кращу швидкість збіжності, ніж алгоритм оптимізації рою частинок, алгоритм збурення та спостереження, алгоритм сходження на пагорб та алгоритм інкрементальної провідності

MPPT control of PV array based on PSO and adaptive controller

In general, photovoltaic (PV) array is not able to generate maximum power automatically, because some partial shading caused by trees, clouds, or buildings. Irradiation imperfections received by the PV array are overcome by applying maximum power point tracking (MPPT) to the output of the PV array. In order to overcome these partial shading problems, this system is employing particle swarm optimization (PSO) as MPPT method. It optimizes the output power of the solar PV array by Zeta converter. Output voltage of MPPT has high rate such that it needs stepdown device to regulate certain voltage. Constant voltage will be the input voltage of buck converter and controlled using adaptive PID. Adaptive control based on model reference adaptive control (MRAC) has design that almost same as the conventional PID structure and it has better performance in several conditions. The proposed system is expected to have stable output and able to perfectly emulate the response of the reference model. From the simulation results, it appears that PSO have high tracking accuracy and high tracking speed to reach maximum power of PV array. In the output voltage regulation, adaptive control does not have a stable error status and consistently follows the set point value

Design and implementation of a dual-input single-output photovoltaic converter

In many solar inverters, a dc/dc converter is mainly located between the solar arrays and the inverter. This study presents an enhanced maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems that drives solar array voltages to track a reference value and decreases fluctuations and oscillations in PV voltage. Different from the previously presented methods, a novel MPPT method is proposed that ensures tracking accuracy by considering output voltage in addition to input voltage and currents. The proposed method detects dI/dV variations, compares the output voltage with the desired reference to shift operation mode and refreshes step size. The digital filtering, enhanced PI, and perturb-and-observe (P&O) tracking features of the proposed MPPT method make it robust to mitigate source fluctuations and sensitivity to partial shading based oscillations. In order to validate the success of the proposed method, a test rig has been installed with dual boost converters. The performance improvements have been verified by both simulation and experimental results that are compared to InCon and P&O MPPT methods. It is also confirmed by experimental results that the proposed MPPT method provides robust control capability in terms of tracking the reference voltage and rejecting the effects of various shading situations on solar arrays

A Robust Maximum Power Point Tracking Control Method for a PEM Fuel Cell Power System

Taking into account the limited capability of proton exchange membrane fuel cells (PEMFCs) to produce energy, it is mandatory to provide solutions, in which an efficient power produced by PEMFCs can be attained. The maximum power point tracker (MPPT) plays a considerable role in the performance improvement of the PEMFCs. Conventional MPPT algorithms showed good performances due to their simplicity and easy implementation. However, oscillations around the maximum power point and inefficiency in the case of rapid change in operating conditions are their main drawbacks. To this end, a new MPPT scheme based on a current reference estimator is presented. The main goal of this work is to keep the PEMFCs functioning at an efficient power point. This goal is achieved using the backstepping technique, which drives the DC-DC boost converter inserted between the PEMFC and the load. The stability of the proposed algorithm is demonstrated by means of Lyapunov analysis. To verify the ability of the proposed method, an extensive simulation test is executed in a Matlab-Simulink (TM) environment. Compared with the well-known proportional-integral (PI) controller, results indicate that the proposed backstepping technique offers rapid and adequate converging to the operating power point.The authors are very grateful to the UPV/EHU for its support through the projects PPGA18/04 and to the Basque Government for its support through the project ETORTEK KK-2017/00033. The authors would also like to thank the Tunisian Government for its support through the research unit UR11ES82