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.

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.

AN IMPROVED PERTURBATION AND OBSERVATION BASED MAXIMUM POWER POINT TRACKING METHOD FOR PHOTOVOLTAIC SYSTEMS

2016 ◽  
Vol 78 (6-2) ◽  
Author(s):  
Ammar Hussein Mutlag ◽  
Azah Mohamed ◽  
Hussain Shareef
Keyword(s):  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Fast Tracking ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Simulink Simulation ◽  
Current Voltage ◽  
Accurate Performance ◽  
Power Point

In photovoltaic (PV) system, maximum power tracking (MPPT) is crucial to improve the system performance. Irradiance and temperature are the two important parameters that affect MPPT. The conventional perturbation and observation (P&O) based MPPT algorithm does not accurately track the PV maximum power point. Therefore, this paper presents an improved P&O algorithm (Im-P&O) based on variable perturbation. The idea behind the Im-P&O algorithm is to produce variable step changes in the reference current/voltage for fast tracking of the PV maximum power point. The Im-P&O based MPPT is designed for the 25 SolarTIFSTF-120P6 PV panels, with a capacity of 3 kW peak. A complete PV system is modeled using the MATLAB/Simulink. Simulation results showed that the Im-P&O based MPPT achieved faster and accurate performance compared with the conventional P&O algorithm.

scholarly journals Análise Comparativa das Técnicas Clássicas de MPPT

2021 ◽  
Author(s):  
MIRéLI BINDER VENDRUSCOLO ◽  
ANTóNIO MANUEL SANTOS SPENCER ANDRADE
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Hill Climbing ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

As características elétricas de rendimento e potência de um painel fotovoltaico (PV) são influenciadas por dois fatores climáticos, que são: irradiância solar e temperatura. Por essa razão, os algoritmos de MPPT (Maximum Power Point Tracking) são essenciais para se obter a máxima potência produzida. Portanto, este trabalho apresenta uma avaliação comparativa das principais técnicas clássicas de MPPT, sendo elas: Perturba e Observa (P&O), Hill Climbing (HC) e Condutância Incremental (InC). Para fazer essas avaliações de MPPT foram utilizados conversores estáticos CC-CC, tais como: Boost, Buck e Buck-Boost. No entanto, o MPPT é aplicado na entrada e saída dos conversores, a fim de observar o melhor desempenho. Os resultados de simulação são avaliados utilizado o software PSIM.

scholarly journals Survey of Six Maximum Power Point Tracking Algorithms under Standard Test conditions

2021 ◽  
Vol 03 (01) ◽  
pp. 53-62
Author(s):  
Mohammed Salah Bouakkaz ◽  
◽  
Ahcene Boukadoum ◽  
Omar Boudebbouz ◽  
Issam Attoui ◽  
...  
Keyword(s):  
Short Circuit ◽  
Maximum Power Point Tracking ◽  
Open Circuit ◽  
Climatic Conditions ◽  
Maximum Power ◽  
Hill Climbing ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

In this work, a survey is carried out on six MPPT algorithms which include conventional and artificial intelligence based approaches. Maximum Power Point Tracking (MPPT) algorithms are used in PV systems to extract the maximum power in varying climatic conditions. The following most popular MPPT techniques are being reviewed and studied: Hill Climbing (HC), Perturb and Observe (P&O), Incremental Conductance (INC), Open-Circuit Voltage (OCV), Short Circuit Current (SCC), and Fuzzy Logic Control (FLC). The algorithms are evaluated, analyzed, and interpreted using a Matlab-Simulink environment to show the performance and limitations of each algorithm

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 A maximum power point tracking technique using modified hill climbing (MHC) method in DC microgrid application

2020 ◽  
Author(s):  
Zaenal Efendi ◽  
Epyk Sunarno ◽  
Farid Dwi Murdianto ◽  
Rachma Prilian Eviningsih ◽  
Lucky Pradigta Setiya Raharja ◽  
...  
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Hill Climbing ◽  
Maximum Power Point ◽  
Dc Microgrid ◽  
Tracking Technique ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

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.

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