MODELLING AND SIMULATION OF ANFISBASED MPPT FOR PV SYSTEM WITH MODIFIED SEPIC CONVERTER

This paper proposes a capacitor switching logic for a multi input Single Ended Primary Inductance Converter (SEPIC) with efficient Maximum Power Point Tracking (MPPT) scheme for multiple non aligned solar panels. The proposed scheme is an improvement of time division multiplexing control of multi input converters for low power solar energy harvesters. In the proposed design, the capacitor switching logic gives the flexibility of selecting panels on demand providing additional advantage of isolation. For better accuracy an efficient algorithm has been implemented for determining MPPT. The MPPT is practically determined in each cycle when the corresponding capacitor is connected to converter. Using SEPIC converter at the output provides a constant 15V for charging the battery for solar panel voltage range from 8V to 25V. The design improvements will bring increased efficiency for medium power solar systems.

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.

This paper presents a performance analysis of grid connected SPV system for different maximum power point tracking (MPPT) algorithms. The detailed mathematical model of grid connected three-phase solar photovoltaic (SPV) system with parametric model of SPV cell, thermal modelling and switching loss calculation of switching devices are discussed. The performance evaluation has been carried out for perturb-and-observe (P&O) and incremental conductance (IC)-based MPPT algorithms for various outputs of the SPV array, in terms of energy injected to grid, switching losses, junction temperature and sink temperature, for switching in the DC-DC boost converter. The results validated the effectiveness of the MPPT algorithm in increasing SPV output energy, decrease in the switching losses, junction and sink temperature. The results show that IC method is slightly better to P&O method in energy injected to the grid with lower switching losses, junction and sink temperature.

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.

ABSTRACTThis paper presents the modelling, simulation and hardware implementation of the incremental conductance (INC) maximum power point tracking (MPPT) algorithm. The extraction of maximum power from the solar photovoltaic system was made by integrating the PV module with a DC–DC converter and utilising the MPPT algorithm. In this work, the INC MPPT algorithm is practically implemented on an Arduino Uno board to track the maximum power point (MPP) and also simulated in Matlab/Simulink under the same environmental conditions. The performance of the INC algorithm was also compared with the conventional Perturb and Observe (P&O) MPPT algorithm. The experimental and simulation results are provided for both MPPT techniques. Matlab/Simulink was used for simulation studies.

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

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.

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..

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.

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.

A comparative study between frequently used maximum power point tracking (MPPT) algorithms and a proposed Least Squares Support Vector Machine (LS-SVM) based MPPT algorithm under rapidly changing insolation condition (RCIC) is presented in this paper. The comparison shows that the proposed LS-SVM based MPPT algorithm offers some advantages over existing MPPT algorithms under RCIC, namely elimination of ripples in the output voltage of a PV solar system as well as improved tracking accuracy. The algorithms have been tested through simulation studies carried out on real data recorded by the Australia Bureau of Meteorology. The study compares the performances of LS-SVM, P&O and IncCond.

This Harnessing energy from the abundant and free sunlight is now a days a hot-topic among the research community. The availability of cheap solar modules has made it possible to harvest solar energy with better efficiency. The nature of solar modules is nonlinear and therefore the process of impedance matching is essential. The proper impedance matching ensures extraction of the maximum power from solar PV module. Several algorithms are reported in literatures that are used to operate the DC-DC converter around MPP. Maximum power point tracking (MPPT) algorithm acting an significant part in photovoltaic (PV) power generating system because it exploit the output power from a PV generating set for a various climatically conditions. This paper suggested a new modified work for MPPT of PV energy gathering system by using the optimized novel fuzzy logic controller (FLC). In the optimized FLC method, the membership functions tune automatically. In this paper MATLAB simulation effort shows with MPPT controller, a zero voltage and zero current dc to dc buck-boost Luo converter feeding a battery load is achieved. The results demonstrate that the suggested novel rule FLC MPPT in the photovoltaic generating system is valid.

A novel step-up/step-down DC-DC converter with improved voltage gain characteristics is suggested in this paper. The proposed converter combines flyback and single-ended primary inductance converter (SEPIC) converters. The voltage control loop design is simplified due to the use of only a single controlled switch. It has been discussed how switch duty cycle affects voltage gain. This relationship demonstrates that the proposed converter voltage gain is improved compared with flyback and SEPIC converters. However, compared to flyback and SEPIC converters, it has a higher voltage gain at any given duty cycle. The proposed converter operation is thoroughly discussed, the associated equations are derived, and its parameters are expertly designed. Moreover, it is designed to supply a DC load of 2.5 kW, 500 V, and 5 A. The proposed converter efficiency exceeds 84% under rated load conditions. Additionally, it is also presented as an adapter for electric vehicles. The waveforms associated with the simulation of the converter across the universal line voltage of 110-260 Vrms are shown. At both line voltages, the total harmonics distortions (THDs) of the line current are 17.12% and 27.26%, respectively. MATLAB/Simulink is utilized for validation in order to validate the topology for different applications.

For ensuring a greener and low carbon future; renewable energies sources such as solar energy stands out as a prominent solution for generating sustainable and clean electricity due to its accessibility, abundance and numerous benefits. The use of solar panel also called as photovoltaic systems has more importance in the world for their ability to convert sun irradiation into electricity while they have significant drawbacks like the nonlinearity of Pv panel. The efficiency and performance of Photovoltaic (PV) systems can be influnced by various factors, like climate fluctuations during the day. Therefore, it is so important to optimize the power capturing from PV panels. To optimize the energy created by photovoltaic modules, it is necessary to carefully select a DC-DC converter with MPPT control. This guarantees that the maximum power is extracted from the solar power plant and sent to the demand side in less time and with greater effectiveness. This paper introduces a super twisting sliding mode control technique for achieving maximum power point tracking (MPPT) in a photovoltaic (PV) system. The Single Ended Primary Inductor Converter (SEPIC) is proposed as a superior alternative to the conventional boost dc-dc converter, as it enables the extraction of the highest possible power from the photovoltaic panels array. Upon doing a thorough comparison of the suggested control with the P&O algorithm in various scenarios using the MATLAB/SIMULINK tool, it was found that the provided STC (Synchronous Tracking Control) for the SEPIC converter demonstrates greater efficiency and reduced oscillation around the Maximum Power Point (MPP).

This work deals with the design and a prototype implementation of a maximum power point tracker (MPPT) for a thermoelectric (TE) module aiming to improve energy conversion efficiency in battery charging. This system uses TE devices that directly convert heat energy from a water gas heater to electricity to charge a battery. The TE module exhibits a non-linear I-V characteristic and its maximum power point varies with the change of its surfaces temperatures. A SEPIC (single-ended primary inductance converter) DC-DC converter is applied and controlled by a microcontroller and to achieve the maximum power point tracking it is used the perturbation and observation (P&O) algorithm. The microcontroller will also control the charging process of lead-acid battery making an autonomous system that is used to feed the necessary electronics that controls an autonomous gas water heater system. The objectives of this work are to study the principle of TE power generation and to design and develop a TE battery charger that uses heat of a water gas heater system making an autonomous electrical system. The two different charging stages of a lead-acid battery lead us to a good interface board. Finally, experimental results performance of the first stage of charge using P&O MPPT algorithm are presented and compared with the results achieved with the direct connection of the TE module to the battery.