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.

scholarly journals Predictive Control with Current-Based Maximum Power Point-Tracking for On-Grid Photovoltaic Applications

2021 ◽  
Vol 13 (6) ◽  
pp. 3037
Author(s):  
Carlos Muñoz ◽  
Marco Rivera ◽  
Ariel Villalón ◽  
Carlos R. Baier ◽  
Javier Muñoz ◽  
...  
Keyword(s):  
Predictive Control ◽  
Renewable Energy Sources ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Voltage Source ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Pi Controllers ◽  
Power Point

The high increase of renewable energy sources and the increment of distributed generation in the electrical grid has made them complex and of variable parameters, causing potential stability problems to the PI controllers. In this document, a control strategy for power injection to the electrical system from photovoltaic plants through a voltage source inverter two-level-type (VSI-2L) converter is proposed. The algorithm combines a current-based maximum power point-tracking (Current-Based MPPT) with model predictive control (MPC) strategy, allowing avoidance of the use of PI controllers and lowering of the dependence of high-capacitive value condensers. The sections of this paper describe the parts of the system, control algorithms, and simulated and experimental results that allow observation of the behavior of the proposed strategy.

Implementaasi Maximum Power Point Tracker (MPPT) dengan topologi sepic pada pembangkit listrik tenaga surya

JURNAL ELTEK ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. 1
Author(s):  
Oktriza Melfazen ◽  
M. Taqijuddin Alawiy ◽  
Denda Dewatama
Keyword(s):  
Power Plants ◽  
Solar Power ◽  
Maximum Power Point Tracking ◽  
Average Power ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Arduino Uno ◽  
Power Point

Terdapat rugi-rugi daya dalam proses menghasilkan daya pada Pembangkit Listrik Tenaga Surya (PLTS) konvensional. Sehingga energi yang dihasilkan tidak terserap secara maksimal. Sistem Pembangkit Listrik Tenaga Surya yang didesain dalam penelitian ini diharapkan dapat menghasilkan energi optimal dengan memanfaatkan kemampuan algoritma Maximum Power Point Tracking (MPPT) dengan metode Perturb and Obserb yang diaplikasikan pada topologi SEPIC. Pada penelitian ini, sistem  menggunakan panel surya berjenis amorphous 60W, sensor arus ACS712, sensor tegangan berupa pembagi tegangan dan rangkaian converter dengan topologi SEPIC yang dikontrol mikrokontroler Arduino UNO dengan sistem MPPT. Hasil penelitian yang didapat sebagai berikut: penempatan panel surya yang baik adalah menghadap atas (tegak lurus dengan permukaan bumi, sensor arus bekerja dengan eror rata-rata 1,92%, sensor tegangan mempunyai eror rata-rata 2,76%, dan topologi SEPIC dengan MPPT mempunyai hasil daya rata-rata 26,13 W.   There are power losses in the process of generating power in conventional Solar Power Plants (PLTS). So that the energy produced is not absorbed to the fullest. The Solar Power Sistem designed in this study is expected to produce optimal energy by utilizing the ability of the Maximum Power Point Tracking (MPPT) algorithm with the Perturb and Obserb method applied to the SEPIC topology. The sistem built in this study uses a 60W amorphous type solar panel, ACS712 current sensor, a voltage sensor in the form of a voltage divider and a converter circuit with a SEPIC topology controlled by an Arduino UNO microcontroller with an MPPT sistem.The results obtained as follows: a good placement of solar panels is facing upward (perpendicular to the surface of the earth, current sensors work with an average eror of 1.92%, voltage sensors have an average eror of 2.76%, and SEPIC topology with MPPT has an average power yield of 26.13 W.

Analysis, design and implementation of analog circuitry-based maximum power point tracking for photovoltaic boost DC/DC converter

2018 ◽  
Vol 41 (3) ◽  
pp. 668-686 ◽  
Author(s):  
Priyabrata Shaw ◽  
Priyabrat Garanayak
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Energy Concentration ◽  
Clock Frequency ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Analog Circuitry

Currently, research is being devoted towards the development of fast and precise maximum power point tracking (MPPT) methods for various photovoltaic (PV) applications. Due to rapidly varying solar irradiation and cell temperature, traditional MPPT algorithms are unable to track the optimum power from PV modules. In this paper, an analog circuitry-based fast and robust MPPT method utilizing a boost DC/DC converter is presented to improve the tracking capability. The mathematical model of a PV module and design expressions for converter elements are presented. To trace the desired maximum power point (MPP), a control law is derived by synthesizing the PV characteristic curves. The steady-state and transient responses of the PV-integrated boost converter are demonstrated under various conditions of source and load using the MATLAB/Simulink platform. Furthermore, a laboratory prototype is developed to validate the proposed control strategy in the real-time application. A satisfactory agreement has been exhibited among simulation and experimental results. The superiority of the proposed MPP tracker over different existing methods is investigated. Additionally, the proposed controller distributes the energy spectrum over a wider range of frequencies and simultaneously reduces the energy concentration at the clock frequency and its multiples, so that the effect of electromagnetic interference (EMI) is reduced for certain range of loads.

scholarly journals A Gradient Descent Approach for Maximum Power Point Tracking in Solar PV Systems Networks

2021 ◽  
Vol 9 (VI) ◽  
pp. 1739-1745
Author(s):  
Jyotsana Pandey
Keyword(s):  
Gradient Descent ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Percentage Error ◽  
Solar Pv ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

— The intermittent nature of solar irradiation makes it necessary to continuously track the irradiation and change the orientation of the solar panels so as to maximize the PV output. Since the nature of solar irradiation data is both extremely random and complex, hence classical statistical techniques render inaccuracies in the predicted values. Therefore, machine learning based approaches are needed for the estimation or forecasting of the PV output. The proposed approach employs the gradient descent-based approach for attaining the condition of maximum power point tracking (MPPT). The performance of the system has been evaluated in terms of the mean absolute percentage error and accuracy. It has been shown that the proposed system attains an accuracy of 96.31% with an MAPE of 3.69%.

scholarly journals Maximum Power Point Tracking of Photovoltaic System Based on Reinforcement Learning

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5054 ◽  
Author(s):  
Chou ◽  
Yang ◽  
Chen
Keyword(s):  
Reinforcement Learning ◽  
Learning Algorithm ◽  
Maximum Power Point Tracking ◽  
Average Power ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

The maximum power point tracking (MPPT) technique is often used in photovoltaic (PV) systems to extract the maximum power in various environmental conditions. The perturbation and observation (P&O) method is one of the most well-known MPPT methods; however, it may face problems of large oscillations around maximum power point (MPP) or low-tracking efficiency. In this paper, two reinforcement learning-based maximum power point tracking (RL MPPT) methods are proposed by the use of the Q-learning algorithm. One constructs the Q-table and the other adopts the Q-network. These two proposed methods do not require the information of an actual PV module in advance and can track the MPP through offline training in two phases, the learning phase and the tracking phase. From the experimental results, both the reinforcement learning-based Q-table maximum power point tracking (RL-QT MPPT) and the reinforcement learning-based Q-network maximum power point tracking (RL-QN MPPT) methods have smaller ripples and faster tracking speeds when compared with the P&O method. In addition, for these two proposed methods, the RL-QT MPPT method performs with smaller oscillation and the RL-QN MPPT method achieves higher average power.

scholarly journals Maximum Power Point Tracking Based on Sliding Mode Control

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Nimrod Vázquez ◽  
Yuz Azaf ◽  
Ilse Cervantes ◽  
Eslí Vázquez ◽  
Claudia Hernández
Keyword(s):  
Sliding Mode ◽  
Maximum Power Point Tracking ◽  
Good Choice ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Solar panels, which have become a good choice, are used to generate and supply electricity in commercial and residential applications. This generated power starts with the solar cells, which have a complex relationship between solar irradiation, temperature, and output power. For this reason a tracking of the maximum power point is required. Traditionally, this has been made by considering just current and voltage conditions at the photovoltaic panel; however, temperature also influences the process. In this paper the voltage, current, and temperature in the PV system are considered to be a part of a sliding surface for the proposed maximum power point tracking; this means a sliding mode controller is applied. Obtained results gave a good dynamic response, as a difference from traditional schemes, which are only based on computational algorithms. A traditional algorithm based on MPPT was added in order to assure a low steady state error.

scholarly journals Review of Online and Soft Computing Maximum Power Point Tracking Techniques under Non-Uniform Solar Irradiation Conditions

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3256 ◽  
Author(s):  
Amjad Ali ◽  
K. Almutairi ◽  
Muhammad Zeeshan Malik ◽  
Kashif Irshad ◽  
Vineet Tirth ◽  
...  
Keyword(s):  
Soft Computing ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Solar Irradiation ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Review Articles ◽  
Power Point

Significant growth in solar photovoltaic (PV) installation has been observed during the last decade in standalone and grid-connected power generation systems. However, the PV system has a non-linear output characteristic because of weather intermittency, which tends to a substantial loss in overall system output. Thus, to optimize the output of the PV system, maximum power point tracking (MPPT) techniques are used to track the global maximum power point (GMPP) and extract the maximum power from the PV system under different weather conditions with better precision. Since MPPT is an essential part of the PV system, to date, many MPPT methods have been developed by various researchers, each with unique features. A Google Scholar survey of the last five years (2015–2020) was performed to investigate the number of review articles published. It was found that overall, seventy-one review articles were published on different MPPT techniques; out of those, only four were on non-uniform solar irradiance, and seven review articles included shading conditions. Unfortunately, very few attempts were made in this regard. Therefore, a comprehensive review paper on this topic is needed, in which almost all the well-known MPPT techniques should be encapsulated in one document. This article focuses on online and soft-computing MPPT algorithm classifications under non-uniform irradiance conditions along with their mathematical expression, operating principles, and block diagram/flow charts. It will provide a direction for future research and development in the field of maximum power point tracking optimization.

Photovoltaic system optimization by new maximum power point tracking (MPPT) models based on analog components under harsh condition

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Minh Long Hoang
Keyword(s):  
Renewable Energy Sources ◽  
Maximum Power Point Tracking ◽  
System Optimization ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Abstract Photovoltaic (PV) energy has become a promising energy source because the demand for electrical energy from renewable energy sources is increasing worldwide in recent decades. Due to efficiency issues, the Maximum Power Point Tracking (MPPT) has been developed to optimize the solar panel’s performance. This paper presents an MPPT model, made up of the analog component, which overcomes traditional MPPT methods’ weakness via the Perturb and observes (P&O) technique. In this case, the PV system includes a PV array, a DC/DC boost converter, a battery, and a load. The proposed method was precisely built and simulated using the Powersim, MATLAB Simulink, and SimCoupler Module. The components of the analog MPPT system were designed practically in detail. The experiment was carried out by using European Efficiency Test 50530, and the results showed the proposed model has higher efficiency over the digital MPPT technique, about 99.99% as maximum. Moreover, MPPT methods were tested under steady-state, irradiation variation, and space conditions to verify the system’s potential capability with PV module Solbian 52L.

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