scholarly journals Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2770
Author(s):  
Mukul Chankaya ◽  
Ikhlaq Hussain ◽  
Aijaz Ahmad ◽  
Hasmat Malik ◽  
Fausto Pedro García Márquez
Keyword(s):  
Maximum Power ◽  
Solar Irradiation ◽  
Gaussian Kernel ◽  
Mean Square ◽  
Maximum Power Point ◽  
Dynamic Conditions ◽  
Multi Objective ◽  
Kernel Width ◽  
Dc Bus ◽  
Power Point

This article presents the control of a three-phase three-wire (3P-3W) dual-stage grid-tied PV-battery storage system using a multi-objective grass-hopper optimization (MOGHO) algorithm. The voltage source converter (VSC) control of the presented system is implemented with adaptive kernel width sixth-order maximum correntropy criteria (AKWSOMCC) and maximum power point tracking (MPPT) control is accomplished using the variable step-size incremental conductance (VSS-InC) technique. The proposed VSC control offers lower mean square error and better accuracy, convergence rate and speed as compared to peer adaptive algorithms, i.e., least mean square (LMS), least mean fourth (LMF), maximum correntropy criteria (MCC), etc. The adaptive Gaussian kernel width is a function of the error signal, which changes to accommodate and filter Gaussian and non-Gaussian noise signals in each iteration. The VSS-InC based MPPT is provided with a MOGHO based modulation factor for better and faster tracking of the maximum power point during changing solar irradiation. Similarly, an optimized gain conventional PI controller regulates the DC bus to improve the power quality, and DC link stability during dynamic conditions. The optimized DC-link generates an accurate loss component of current, which further improves the VSC capability of fundamental load current component extraction. The VSC is designed to perform multi-functional operations, i.e., harmonics elimination, reactive power compensation, load balancing and power balancing at point of common coupling during diverse dynamic conditions. The MOSHO based VSS-InC, and DC bus performance is compared to particle swarm optimization (PSO) and genetic algorithm (GA). The proposed system operates satisfactorily as per IEEE519 standards in the MATLAB simulation environment.

Comparison between Seven MPPT Techniques Implemented in a Buck Converter

2019 ◽  
Vol 12 (6) ◽  
pp. 476-486
Author(s):  
Lahcen El Mentaly ◽  
Abdellah Amghar ◽  
Hassan Sahsah
Keyword(s):  
Value Added ◽  
Buck Converter ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Solar Panels ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Pv Panel ◽  
Low Efficiency ◽  
Power Point

Background: The solar field on our planet is inexhaustible, which favors the use of photovoltaic electricity which generates no nuisance: no greenhouse gases, no waste. Methods: It is a high value-added energy that is produced directly at the place of consumption through photovoltaic (PV) solar panels. Notwithstanding these advantages, the maximum power depends strongly on solar irradiation and temperature, which means that a Maximum Power Point Tracking (MPPT) controller must be inserted between the PV panel and the load in order to follow the Maximum Power Point (MPP) continuously and in real time. In this work, MPP’s behavior was simulated at different temperatures and solar irradiations using seven techniques which identify the MPP by different methods. Results: The novelty of this work is that the seven MPPT methods were compared according to a very selective criterion which is the MPPT efficiency as well as a purely digital duty cycle control without using the PI controller. The simulation under the PSIM software shows that the FLC, TP, FSCC, TG, HC and IC methods have almost the same efficiency of 99%, whereas the FOCV method had a low efficiency of 96%. Conclusion: This makes it possible to conclude that the best methods are FLC, HC and IC because they use fewer sensors compared to the rest.

scholarly journals A Novel DSP-Based MPPT Control Design for Photovoltaic Systems Using Neural Network Compensator

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3260
Author(s):  
Ming-Fa Tsai ◽  
Chung-Shi Tseng ◽  
Kuo-Tung Hung ◽  
Shih-Hua Lin
Keyword(s):  
Neural Network ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Irradiation Cell ◽  
Power Point ◽  
Neural Network Compensator

In this study, based on the slope of power versus voltage, a novel maximum-power-point tracking algorithm using a neural network compensator was proposed and implemented on a TI TMS320F28335 digital signal processing chip, which can easily process the input signals conversion and the complex floating-point computation on the neural network of the proposed control scheme. Because the output power of the photovoltaic system is a function of the solar irradiation, cell temperature, and characteristics of the photovoltaic array, the analytic solution for obtaining the maximum power is difficult to obtain due to its complexity, nonlinearity, and uncertainties of parameters. The innovation of this work is to obtain the maximum power of the photovoltaic system using a neural network with the idea of transferring the maximum-power-point tracking problem into a proportional-integral current control problem despite the variation in solar irradiation, cell temperature, and the electrical load characteristics. The current controller parameters are determined via a genetic algorithm for finding the controller parameters by the minimization of a complicatedly nonlinear performance index function. The experimental result shows the output power of the photovoltaic system, which consists of the series connection of two 155-W TYN-155S5 modules, is 267.42 W at certain solar irradiation and ambient temperature. From the simulation and experimental results, the validity of the proposed controller was verified.

scholarly journals Modified Maximum Power Point Tracking Algorithm under Time-Varying Solar Irradiation

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6722
Author(s):  
Mehmet Ali Yildirim ◽  
Marzena Nowak-Ocłoń
Keyword(s):  
Renewable Energy Sources ◽  
Maximum Power Point Tracking ◽  
Average Power ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Time Varying ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Solar photovoltaic (PV) energy is one of the most viable renewable energy sources, considered less polluting than fossil energy. However, the average power conversion efficiency of PV systems is between 15% and 20%, and they must operate with high efficiency. Photovoltaic cells have non-linear voltage–current characteristics that are dependent on environmental factors such as solar irradiation and temperature, and have low efficiency. Therefore, it becomes crucial to harvest the maximum power from PV panels. This paper aims to study and analyze the most common and well-known maximum power point tracking (MPPT) algorithms, perturb and observe (P&O) and incremental conductance (IncCond). These algorithms were found to be easy to implement, low-cost techniques suitable for large- and medium-sized photovoltaic applications. The algorithms were tested and compared dynamically using MATLAB/Simulink software. In order to overcome the low performance of the P&O and IncCond methods under time-varying and fast-changing solar irradiation, several modifications are proposed. Results show an improvement in the tracking and overall system efficiencies and a shortened response time compared with original techniques. In addition, the proposed algorithms minimize the oscillations around the maximum power point (MPP), and the power converges faster.

Improvement of the Temperature Parametric (TP) Method for Fast Tracking of Maximum Power Point in Photovoltaic Modules

2019 ◽  
Vol 20 (5) ◽  
Author(s):  
Lahcen El Mentaly ◽  
Abdellah Amghar ◽  
Hassan Sahsah
Keyword(s):  
Maximum Power ◽  
Hill Climbing ◽  
Solar Irradiation ◽  
Operating Voltage ◽  
Maximum Power Point ◽  
New Approach ◽  
Fast Tracking ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Abstract In this work we have presented a generalization of the Temperature Parametric (TP) Method which is based on the detection of the maximum power point by the prediction of the corresponding optimal voltage. This operating voltage is determined by the continuous measurement of the ambient temperature and solar irradiation. This new approach is based on a 3D linear regression model linking these quantities and which allows to our method to realize the maximum power point tracking in real time. The simulation shows that this new technique has a better MPPT efficiency compared to Hill Climbing technique.

Research on MPPT of PV Systems Based on BP Neural Network

2012 ◽  
Vol 466-467 ◽  
pp. 930-934
Author(s):  
Wen Ying Chen ◽  
Yong Jun Lin ◽  
Wei Liang Liu ◽  
Shuang Sai Liu
Keyword(s):  
Control Structure ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Maximum Power Point ◽  
Hardware Platform ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Perturb And Observe ◽  
Power Point

In order to obtain more output power of photovoltaic (PV) array, which depends on solar irradiation and ambient temperature, maximum power point tracking (MPPT) techniques are employed. Among all the MPPT strategies, the Perturb and Observe (P&O) algorithm is more attractive due to the simple control structure. Nevertheless, steady-state oscillations always appear due to the perturbation. In this paper, a new MPPT method based on BP Neural Networks and P&O is proposed for searching maximum power point (MPP) fast and exactly, and its effectiveness is validated by experimental results using hardware platform based on microcomputer.

Research of MPPT Using Support Vector Machine for PV System

2013 ◽  
Vol 441 ◽  
pp. 268-271
Author(s):  
De Da Sun ◽  
Da Hai Zhang ◽  
Yang Liu
Keyword(s):  
Support Vector Machine ◽  
Power Systems ◽  
High Efficiency ◽  
Environmental Changes ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Support Vector ◽  
Pv System ◽  
Maximum Power Point ◽  
Power Point

Photovoltaic (PV) power systems are widely used today, so its useful to study how to make the PV maximum power output. In this paper a novel approach based on Support Vector Machine (SVM) for maximum power point tracking (MPPT) of PV systems is presented. The output power characteristics of PV cells vary with solar irradiation and temperature, so the controllers inputs is the level of solar radiation and ambient temperature of the PV module, and the voltage at maximum power point (MPP) is the output. Results show that the proposed MPPT controller based on SVM is sensitive to environmental changes and has high efficiency and less Mean Square Error (MSE).

scholarly journals Real-Time Experimental Assessment of a New MPPT Algorithm Based on the Direct Detection of the Short-Circuit Current for a PV System

2021 ◽  
Vol 19 ◽  
pp. 598-603 ◽  
Author(s):  
C.B. Nzoundja Fapi ◽  
◽  
P. Wira ◽  
M. Kamta ◽  
Keyword(s):  
Fuzzy Logic Controller ◽  
Direct Detection ◽  
Short Circuit ◽  
Short Circuit Current ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Pv System ◽  
Maximum Power Point ◽  
Pv Panel ◽  
Power Point

To substantially increase the efficiency of photovoltaic (PV) systems, it is important that the Maximum Power Point Tracking (MPPT) system has an output close to 100%.This process is handled by MPPT algorithms such as Fractional Open-Circuit Voltage (FOCV), Perturb and Observe (P&O), Fractional Short-Circuit Current (FSCC), Incremental Conductance (INC), Fuzzy Logic Controller (FLC) and Neural Network (NN) controllers. The FSCC algorithm is simple to be implemented and uses only one current sensor. This method is based on the unique existence of the linear approximation between the Maximum Power Point (MPP) current and the short-circuit current in standard conditions. The speed of this MPPT optimization technic is fast, however this algorithm needs to short-circuit the PV panel each time in order to obtain the short circuit current. This process leads to energy losses and high oscillations. In order to improve the FSCC algorithm, we propose a method based on the direct detection of the shortcircuit current by simply reading the output current of the PV panel. This value allows directly calculating the short circuit current by incrementing or decrementing the solar irradiation. Experimental results show time response attenuation, little oscillations, power losses reduction and better MPPT accuracy of the enhanced algorithm compared to the conventional FSCC method.

An Advanced MPPT Based on Artificial Bee Colony Algorithm for MPPT Photovoltaic System under Partial Shading Condition

2017 ◽  
Vol 8 (2) ◽  
pp. 647 ◽  
Author(s):  
Salmi Hassan ◽  
Badri Abdelmajid ◽  
Zegrari Mourad ◽  
Sahel Aicha ◽  
Baghdad Abdenaceur
Keyword(s):  
Local Maximum ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Pv Array ◽  
Point Tracking ◽  
Power Point

<p>Maximum power point tracking (MPPT) algorithms are employed in photovoltaic (PV) systems to make full utilization of PV array output power, which have a complex relationship between ambient temperature and solar irradiation. The power-voltage characteristic of PV array operating under partial shading conditions (PSC) exhibits multiple local maximum power points (LMPP). In this paper, an advanced algorithm has been presented to track the global maximum power point (GMPP) of PV. Compared with the Perturb and Observe (P&amp;O) techniques, the algorithm proposed the advantages of determining the location of GMPP whether partial shading is present.</p>

Improvement of EMC in MPPT Control of Photovoltaic System Using Auto-Tuning Adaptive Velocity Estimator

2015 ◽  
Vol 27 (5) ◽  
pp. 489-495
Author(s):  
Tsuyoshi Ohba ◽  
◽  
Risa Matsuda ◽  
Haruo Suemitsu ◽  
Takami Matsuo
Keyword(s):  
Time Derivative ◽  
Maximum Power ◽  
Adaptive Observer ◽  
Solar Irradiation ◽  
Frequency Noise ◽  
Maximum Power Point ◽  
Photovoltaic Array ◽  
Conductance Method ◽  
Auto Tuning ◽  
Power Point

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270005/04.jpg"" width=""300"" /> Proposed modified-IC method</div> Output by a photovoltaic array is nonlinear and changes with solar irradiation and cell temperature. Maximum Power Point Tracking (MPPT) is needed to maximize the energy produced. Most MPPT techniques include the time derivative of current and voltage. These electrical signals are disturbed by high-frequency noise such as from the power device switching. Lowpass filters are used to reduce circuit noise, but estimation error occurs when the maximum power point is calculated. We therefore apply an adaptive observer to estimate the time derivative of noisy signals. Specifically, we propose an auto-tuning velocity estimator with a forgetting factor based on the adaptive observer. We also improve the incremental conductance method by using an auto-tuning velocity estimator. </span>

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