Comparative study of variable size perturbation and observation maximum power point trackers for PV systems

The perturbation and observation (P&O) maximum power point tracking (MPPT) algorithms are very common in PV systems. Implementations of P&O algorithms based on peak current control and on instantaneous sampled values have shown to provide very fast transients and small oscillations around the maximum power point (MPP). However, operation with fixed variation of the reference current results in a trade-off between speed of response and maximum power yield in the steady state. Variable variation of the reference current can be successfully done with Fuzzy logic but results in significant computation burden for common digital signal processors (DSP). Thus the minimum time step is relatively large what reduces the transient response of the scheme. This paper presents an alternative approach based on non-switching zones and compares by simulation the performance and discusses the implementation difficulties of 4 peak-current controlled P&O MPPT algorithms.

Due to the Randomness and fluctuation of the photovoltaic (PV) system, Maximum Power Point Tracking (MPPT) algorithm is employed to ensure the maximum power extraction from PV arrays, when it is connected to the grid. The previous studies have indicated that the MPPT algorithm is one of the main causes of interharmonics emission in PV systems. The MPPT algorithm parameters such as perturbation step size inevitably have a strong impact on the interharmonics in the current injected to the grid. In general, a smaller MPPT perturbation step size will reduce the interharmonics emission level, but it will result in poor tracking performance of the MPPT algorithm. Thus, there is a trade-off between the MPPT efficiency and the interharmonics emission in PV system. In this paper, an interharmonics suppression scheme with variable step size MPPT algorithm was proposed. In the suppression scheme, two voltage values near by the MPPT voltage and two tracking step size are preset. When the dc-link voltage of PV is between the two preset voltage values, it means that the PV power near its MPP and the smaller perturbation step size implemented in the MPPT algorithm. Otherwise, the bigger perturbation step size is employed. It can greatly reduce interharmonics emission level and maintain the MPPT efficiency. Simulations have been carried out to verify the effectiveness of the suppression scheme.

The perturbation and observation (P&O) maximum power point tracking (MPPT) algorithms are commonly used in photovoltaic (PV) systems due to their easy implementation and ability to track the maximum power point (MPP) of the solar array under widely varying atmospheric conditions viz. solar irradiation, panel temperature etc. P&O algorithm based on peak current control and the use of instantaneous sampled values to calculate the next perturbation direction have the potential for faster transients and smaller oscillations around the MPP. The use of fixed variation of the reference current results in a compromise sub-optimum solution. This paper discusses a fuzzy logic based P&O MPPT with peak current control with variable variation of the reference current for improved transient as well as steady-state performance. Simulation results show a 15 % gain in the transient response and decrease of the power loss in the steady state. Besides, both the P&O scheme with fixed variation for the reference current and the intelligent MPPT algorithm were able to identify the global MPP in a partially shaded PV module, however the performance of the intelligent MPPT algorithm was better

Recently, real-time simulation of renewable energy sources are indispensible for evaluating the performance of the maximum power point tracking (MPPT) controller, especially in the photovoltaic (PV) system in order to reduce cost in the testing phase. Nowadays, real time PV simulators are obtained by using analog and/or digital components. In this paper, a real-time simulation of a PV system with a boost converter was proposed using only the digital signal processor (DSP) processor with two DC voltage sources to emulate the temperature and irradiation in the PV system. AMATLAB/ Simulink environment was used to develop the real-time PV system with a boost converter into a C-program and build it into a DSP controller TMS320F28335. Besides, the performance of the real-time DSP-based PV was tested in different temperature and irradiation conditions to observe the P-V and V-I characteristics. Further, the performance of the PV with a boost converter was tested at different temperatures and irradiations using MPPT algorithms. This scheme was tested through simulation and the results were validated with that of standard conditions given in the PV data sheets. Implementation of this project helped to attract more researchers to study renewable energy applications without real sources. This might facilitate the study of PV systems in a real-time scenario and the evaluation of what should be expected for PV modules available in the market.

Photovoltaic (PV) systems are increasingly used as a sustainable energy source, but their efficiency is significantly affected by environmental factors such as shading and temperature variations. This study proposes a novel Maximum Power Point Tracking (MPPT) algorithm based on the fusion of Support Vector Regression (SVR) and Incremental Conductance (INC) techniques, designed to enhance the performance of PV systems under partial shading conditions. The SVR model is employed to predict the power output of the PV system based on voltage and current measurements, leveraging its capability to handle non-linear relationships with high accuracy. The INC method is then integrated with the SVR predictions to dynamically adjust the operating point of the PV array, ensuring rapid and precise tracking of the maximum power point (MPP). The algorithm was implemented in MATLAB, and comprehensive simulations were conducted to evaluate its performance. Simulation results demonstrate that the SVR-INC fusion algorithm significantly improves the accuracy and stability of MPPT under varying shading conditions. The algorithm effectively reduces the tracking time to the MPP and minimizes power losses caused by partial shading. Compared to traditional MPPT methods, the proposed algorithm shows enhanced robustness and faster convergence, making it highly suitable for practical applications in real-world PV systems. Furthermore, the integration of SVR with INC provides a robust framework for dealing with the complexities of $P V$ power generation. The algorithm’s ability to adapt to changing environmental conditions ensures that the PV system operates at its maximum efficiency. The study also discusses the optimization of SVR parameters and the importance of datadriven approaches in enhancing MPPT performance. In conclusion, the proposed SVR-INC fusion MPPT algorithm offers a promising solution for improving the efficiency and reliability of PV systems under partial shading. The findings highlight the potential of this approach for future advancements in PV technology, contributing to the development of more efficient and resilient solar energy systems..

Currently, Photovoltaic (PV) energy is the most important energy resource in electrical power applications around the world since it is inexhaustible, clean and pollution free. As the output power from the PV arrays changing with solar irradiance and temperature, so it is necessary to operate the photovoltaic (PV) system at the maximum power point (MPP) to increase the power extraction from the solar panel. For this effective operation and maximum power extraction from a PV system, Maximum power point tracking (MPPT) algorithm plays a vital role by operating the PV energy system near the MPP. In this work, amongst several existing well established MPPT algorithms, the open voltage (OV) based algorithm is chosen for simulation of a PV system using Matlab / Simscape. As maximum power point (MPP) can be attained with a certain amount of load from the PV power system, so load matching is an important concept of MPPT algorithms. Here, the performances of this open voltage (OV) based algorithm method is evaluated for different values of solar radiation and battery was used as load to see the charging performance for the algorithm.

This paper presents the analysis and operation of a grid connected photovoltaic (PV)energy conversion system with an Adaptive Neuro-Fuzzy Inference System (ANFIS)based maximum power point tracking (MPPT)algorithm. Particle swarm optimization is used to train the membership functions while the least squares algorithm is used to update the consequent parameters of the ANFIS with changing operating condition of PV solar system. The MPPT algorithm maximizes conversion efficiency by adjusting the duty cycle of the buck boost converter to change the output voltage of the solar panel and hence achieving the maximum panel output power for a given set of environmental conditions. The ANFIS is trained by using a hybrid algorithm implementing least squares estimator and particle swarm optimization with data obtained by operating the system using the Perturb and Observe (P&O)MPPT algorithm. The performance of the proposed ANFIS based MPPT algorithm is validated in simulation using MATLAB/Simulink at different operating conditions. It is proven that the designed ANFIS based MPPT scheme achieves a very fast response with little oscillations while transferring maximum power from solar panel to the grid line as compared to the conventional P&O based MPPT scheme.

The essence of switching from non conventional power generation system to conventional generation system has become inevitable due to emergence of constraints such as adverse environmental effects like global warming and depletion in conventional fuel like fossil fuels. The trend of power generation from renewable sources is gaining importance due to clean and inexhaustible properties. Amidst various natural resources, photovoltaic generation system is at priority. But, intermittent climatic variation affect the photovoltaic generation which headed to introduction of maximum power point tracking technique. This paper explicates mathematical modelling of photovoltaic system, implementation of Perturb and Observe maximum power point tracking technique for three phase grid connected photovoltaic generation system and comparison of current, voltage and power generated from photovoltaic system with and without perturb and observe maximum power point tracking technique.

A grid connected photovoltaic(PV) generation system with supercapacitor energy storage in a dc-coupled structure is proposed. The objective of this system is acquiring maximum power from PV arrays, keep the voltage of dc bus constant and supply the prescribed active and reactive power to power grid. An improved Perturbation and Observation (P&O) maximum power point tracking(MPPT) algorithm is applied to extract maximum power from PV arrays. The dc bus voltage is controlled via supercapacitor by charging and discharging. Constant active and reactive power control strategy is designed for the controller of DC/AC converter. Simulation results illustrate the performances obtained.

By detection of input signal, Maximum Power Point Tracking (MPPT) algorithms are used to maximize the potential output power. Since Perturbation and Observe (P&O) method was first applied in a Photovoltaic (PV) system, a myriad of MPPT algorithms has been proposed. With the pros and cons of various MPPT algorithms, a detailed analysis of several typical direct search and module-integrated MPPT algorithms is presented in this paper. Directions of future work for implementing new MPPT algorithms are also outlined.

Purpose Silicon photovoltaics technology has drawbacks of high cost and power conversion efficiency. In order to extract the maximum output power of the module, maximum power point (MPP) is used by implying the nonlinear behavior of I-V characteristics. Different techniques are used regarding maximum power point tracking (MPPT). The paper aims to review the techniques of MPPT used in PV systems and review the comparison between Perturb and Observe (P&O) method and incremental conductance (IC) method that are used to track the maximum power and gives a comparative review of all those techniques. Design/methodology/approach A study of MPPT techniques for photovoltaic (PV) systems is presented. Matlab Simulink is used to find the MPP using P&O simulation along with IC simulation at a steady temperature and irradiance. Findings MATLAB simulations are used to implement the P&O method and IC method, which includes a PV cell connected to an MPPT-controlled boost converter. The simulation results demonstrate the accuracy of the PV model as well as the functional value of the algorithms, which has improved tracking efficiency and dynamic characteristics. P&O solution gave 94% performance when configured. P&O controller has a better time response process. As compared to the P&O method of tracking, the incremental conductance response rate was significantly slower. Originality/value In PV systems, MPPT techniques are used to optimize the PV array output power by continuously tracking the MPP under a variety of operating conditions, including cell temperature and irradiation level.

The subject of variable step size maximum power point tracking (MPPT) algorithms has been addressed in the literature. However, most of the addressed algorithms tune the variable step size according to two variables: the photovoltaic (PV) array voltage (<TEX>$V_{PV}$</TEX>) and the PV array current (<TEX>$I_{PV}$</TEX>). Therefore, both the PV array current and voltage have to be measured. Recently, maximum power point trackers that arc based on a single variable (<TEX>$I_{PV}$</TEX> or <TEX>$V_{PV}$</TEX>) have received a great deal of attention due to their simplicity and ease of implementation, when compared to other tracking techniques. In this paper, two methods have been proposed to design a variable step size MPPT algorithm using only a single current sensor for stand-alone battery storage PV systems. These methods utilize only the relationship between the PV array measured current and the converter duty cycle (D) to automatically adapt the step change in the duty cycle to reach the maximum power point (MPP) of the PV array. Detailed analyses and flowcharts of the proposed methods are included. Moreover, a comparison has been made between the proposed methods to investigate their performance in the transient and steady states. Finally, experimental results with field programmable gate arrays (FPGAs) are presented to verify the performance of the proposed methods.

This paper presents a comparive analysis between four Maximum Power Point Tracking (MPPT) algorithms in centralized grid-tied Photovoltaic (PV) systems. The algorithms are used to control the duty cycle of a DC-DC converter in order to boost the output voltage of the PV generator and guarantee the operation of the solar panels in the Maximum Power Point (MPP). Three of the analyzed algorithms correspond to the classical Perturb and Observe (P&O) method, the Incremental Conductance (IC) technique and the Constant Voltage (CV) method. The fourth analyzed algorithm is a modification of the classical P&O method and it has been designed to improve the tracking of the MPP under voltage disturbances at the DC-side capacitor (interface between the DC-DC and the DC-AC stage). The performance of the MPPT techniques is compared through simulations in PSIM under two conditions: sudden changes of irradiance and a distortion of second order in the voltage at the DC-side capacitor. The comparative analysis is made according to some criterias such as the number of sensors, the rise time and the efficiency.

An on-line MPPT algorithm for rapidly changing illuminations of solar arrays

Photovoltaic (PV) modules subject to partial shading (PS) or inhomogeneous irradiation drastically decrease the PV string power output. An algorithm composed of maximum voltage point tracking (MVPT) and maximum power point (MPP) tracking (MPPT) is presented to restore part of the power loss caused by PS. The MVPT can simultaneously drive the operating point of series PV modules toward their respective MPPs and guarantee power peak uniqueness. The MVPT is performed by means of a controllable current transformer (CCT) disposed at the terminal of each PV module permitting a compatible current in the series path of a PV string. The CCT output current can be regulated using a dependent current source according to the MPPT algorithm. An appropriate CCT current determined by the MPPT algorithm can avert undue CCT activation and consequently reduces the switching and copper losses of the converter circuit. Experimental results validate that the proposed strategy can balance the PV modules' output current subject to PS and facilitate convergence to the theoretical global MPP.