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Journal articles on the topic 'Maximum Power Point Tracking System'

Author: Grafiati

Published: 4 June 2025

Last updated: 6 July 2025

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1

Ourici, Amel, and Bahi Abderaouf. "Maximum Power Point Tracking in A Photovoltaic System Based on Artificial Neurons." Indian Journal Of Science And Technology 16, no. 23 (2023): 1760–67. http://dx.doi.org/10.17485/ijst/v16i23.648.

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2

Fyali, Jibji-Bukar, and Anaya-Lara Olimpo. "Offline Photovoltaic Maximum Power Point Tracking." E3S Web of Conferences 64 (2018): 06007. http://dx.doi.org/10.1051/e3sconf/20186406007.

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As more renewable energy sources are connected to the electrical grid, it has become important that these sources participate in providing system support. It has become needful for grid-connected solar photovoltaics to participate in support functions like frequency support. However, photovoltaic systems need to implement a maximum power tracking algorithm to operate at maximum power and a method for de-loading photovoltaic systems is necessary for participation in frequency support. Some conventional maximum power tracking techniques are implemented in real time and will not adjust their output fast enough to provide system support while other may respond fast but are not very efficient in tracking the maximum power point of a photovoltaic system. This paper presents an offline method to estimate the maximum power voltage and current based on the characteristics of the photovoltaics module available in the datasheet and using the estimated values to operate the photovoltaics at maximum power. The performance of this technique is compared to the conventional technique. This paper also describes how the photovoltaic system can be de-loaded.

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Bhatnagar,, Nitesh. "Maximum Power Point Tracking for PV System." International Journal for Research in Applied Science and Engineering Technology 6, no. 4 (2018): 1395–401. http://dx.doi.org/10.22214/ijraset.2018.4235.

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Naick, Bhukya Krishna, Tarun Kumar Chatterjee, and Kalyan Chatterjee. "Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation." International Journal of Renewable Energy Development 6, no. 1 (2017): 65–74. http://dx.doi.org/10.14710/ijred.6.1.65-74.

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Photovoltaic (PV) system is one of the reliable alternative sources of energy and its contribution in energy sector is growing rapidly. The performance of PV system depends upon the solar insolation, which will be varying throughout the day, season and year. The biggest challenge is to obtain the maximum power from PV array at varying insolation levels. The maximum power point tracking (MPPT) controller, in association with tracking algorithm will act as a principal element in driving the PV system at maximum power point (MPP). In this paper, the simulation model has been developed and the results were compared for perturb and observe, incremental conductance, extremum seeking control and fuzzy logic controller based MPPT algorithms at different irradiation levels on a 10 KW PV array. The results obtained were analysed in terms of convergence rate and their efficiency to track the MPP.Article History: Received 3rd Oct 2016; Received in revised form 6th January 2017; Accepted 10th February 2017; Available onlineHow to Cite This Article: Naick, B. K., Chatterjee, T. K. & Chatterjee, K. (2017) Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation. Int Journal of Renewable Energy Development, 6(1), 65-74.http://dx.doi.org/10.14710/ijred.6.1.65-74

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Cabral Cavalcanti, Marcelo, Kleber Carneiro de Oliveira, Gustavo Medeiros de Souza Azevedo, and Francisco de Assis dos Santos Neves. "Comparative Study Of Maximum Power Point Tracking Techniques For Photovoltaic Systems." Eletrônica de Potência 12, no. 2 (2007): 163–71. http://dx.doi.org/10.18618/rep.2007.2.163171.

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6

Cercel, George, Cosmin Tigănaşu, and Ciprian Nemeş. "Photovoltaic Systems Maximum Power Point Tracking Algorithms." Bulletin of the Polytechnic Institute of Iași. Electrical Engineering, Power Engineering, Electronics Section 67, no. 2 (2021): 19–29. http://dx.doi.org/10.2478/bipie-2021-0008.

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Abstract The power delivered by a photovoltaic cell generator depends on the operating point at which this works. In order to maximize the energy supplied by the PV system, the generator should be adapted to the load so that the operating point will always correspond to the maximum power point. Usually, when a PV module is connected directly to a load, its operating point is rarely at the maximum power point. The operating principle of the maximum power point tracking is to place a converter between the load and the PV array, to adjust the output voltage and the current of the PV array so that the maximum available power is extracted. In most cases the optimal algorithm is chosen according to several criteria, such as: implementation complexity (autonomy of the systems, connected to the network), the type and number of sensors needed, the ability of the algorithm to detect local maximum points, cost, response time, type of implementation (analog, digital, mixed).

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7

Yawale, Mahesh M. "Maximum Power Point Tracking of Isolated Solar System." International Journal for Research in Applied Science and Engineering Technology 6, no. 4 (2018): 2278–82. http://dx.doi.org/10.22214/ijraset.2018.4389.

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8

Yatimi, Hanane, and Elhassan Aroudam. "Standalone Photovoltaic System with Maximum Power Point Tracking." International Journal of System Dynamics Applications 7, no. 3 (2018): 94–111. http://dx.doi.org/10.4018/ijsda.2018070105.

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In this article, on the basis of studying the mathematical model of a PV system, a maximum power point tracking (MPPT) technique with variable weather conditions is proposed. The main objective is to make a full utilization of the output power of a PV solar cell operating at the maximum power point (MPP). To achieve this goal, the incremental conductance (IC) MPPT technique is applied to an off-grid PV system under varying climatic conditions, in particular, solar irradiance and temperature that are locally measured in Northern Morocco. The output power behavior and the performance of the system using this technique have been analyzed through computer simulations to illustrate the validity of the designed method under the effect of real working conditions.

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9

Hua, Chih‐Chiang, Yi‐Hsiung Fang, and Cyuan‐Jyun Wong. "Improved solar system with maximum power point tracking." IET Renewable Power Generation 12, no. 7 (2018): 806–14. http://dx.doi.org/10.1049/iet-rpg.2017.0618.

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10

Gupta, Subhash, S. Kalika, and R. Cabigting Luisito. "Maximum Power Point Tracking for Solar PV System." Applied Mechanics and Materials 110-116 (October 2011): 2034–37. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.2034.

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Solar energy systems have emerged as a viable source of renewable energy over the past two or three decades, and are now widely used for a variety of industrial and domestic applications. This paper shows the potential system benefits of simple tracking solar system using a stepper motor and light sensor. This method is increasing power collection efficiency by developing a device that tracks the sun to keep the panel at a right angle to its rays. Such systems are based on a solar collector, designed to collect the sun’s energy and to convert it into either electrical power or thermal energy The output power produced by high-concentration solar thermal and photovoltaic systems is directly related to the amount of solar energy acquired by the system, and it is therefore necessary to track the sun’s position with a high degree of accuracy. The power developed in such applications depends fundamentally upon the amount of solar energy captured by the collector, and thus the problem of developing tracking schemes capable of following the trajectory of the sun throughout the course of the day on a year-round basis has received significant coverage in the literature. A solar tracking system is designed, implemented and experimentally tested. The design details and the experimental results are incorporated in this paper.

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11

Masood, Mirza. "An intelligent Maximum Power Point solar tracking system." Journal of Applied Engineering Science 17, no. 4 (2019): 457–62. http://dx.doi.org/10.5937/jaes17-20454.

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12

Chen, Wei Min, Shuang Chen, Nan Xie, and Hui Cai. "Researched on Maximum Power Point Tracking of PV Power System." Applied Mechanics and Materials 229-231 (November 2012): 1009–12. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1009.

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To the oscillation and misjudgment problem of the traditional perturbation and observation algorithm, a novel three-point comparison method was proposed. This method applied Constant Voltage Tracking (CVT) method and variable-step perturbation method to solve the problem between tracking accuracy and speed, and applied double-direction perturbation method to make sure the reliability of action to avoid the misjudgment when external conditions fast changing. Restraining the oscillation near the maximum power point effectively was another merit of this proposed method. Finally, the experimental results demonstrate effectiveness of proposed method with PV experimental platform.

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13

G. Molina, Marcelo, Domingo H. Pontoriero, and Pedro Enrique Mercado. "An Efficient Maximum-power-point-tracking Controller For Grid-connected Photovoltaic Energy Conversion System." Eletrônica de Potência 12, no. 2 (2007): 147–54. http://dx.doi.org/10.18618/rep.2007.2.147154.

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14

Chou, Yang, and Chen. "Maximum Power Point Tracking of Photovoltaic System Based on Reinforcement Learning." Sensors 19, no. 22 (2019): 5054. http://dx.doi.org/10.3390/s19225054.

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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.

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15

Andrasto, Tatyantoro, Yohanes Primadiyono, Syahroni Hidayat, Bernadus Sandyawan, Ahmad Rizqi Fauzi, and Mukhammad Khairul Azis. "Incremental Conductance Method in Maximum Power Point Tracking." IOP Conference Series: Earth and Environmental Science 1381, no. 1 (2024): 012023. http://dx.doi.org/10.1088/1755-1315/1381/1/012023.

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Abstract The power characteristic curve in photovoltaic system is non-linear fluctuating based on changes in solar irradiation and module surface temperature. MPPT is a system of tracking the maximum power point of solar panels at any change in irradiation and temperature. Incremental conductance is one of the maximum power tracking methods that can be applied to the MPPT with the input of solar panel voltage and solar panel current. DC-DC Converter is inseparable from the role of MPPT system. MPPT is integrated by implementing DC-DC Converter synchronous buck topology. The system is validated through computational simulations in simulink. Implementation of MPPT product design based on incremental conductance using Arduino Uno to be applied to a 50Wp single solar panel stand-alone. Measurement parameters are displayed on the LCD and data streamer as a monitoring system. The results of the study were conducted by comparing the two topologies of DC-DC converter on the MPPT system, from the comparison of the two topologies of DC-DC converter effect of Drain-Source resistance and forward voltage internal diode to the output power of solar panels showed that the MPPT system that implements the DC-DC converter synchronous buck is able to. Efficiency by implementing DC-DC converter synchronous buck reached 98.2% while the implementation using DC-DC Conveter buck topology reached 97.2% at 1000W/m2.

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16

Holtzhausen, David, and Yoon Soo Kim. "Electro-Mechanical Maximum Power Point Tracking of Photovoltaic System." Applied Mechanics and Materials 300-301 (February 2013): 371–77. http://dx.doi.org/10.4028/www.scientific.net/amm.300-301.371.

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This paper is concerned with optimisation of the power produced by a photovoltaic (PV) panel through designing, building and implementing maximum power point tracking (MPPT). In the literature, the MPPT has been normally approached either electronically (using a DC-to-DC converter) or mechanically (controlling the orientation of a PV panel). In this paper, these two approaches are combined to yield more power. To this end, for a given PV panel (available at the first author’s institution) which is already equipped with a mechanical tracking device, a Buck (DC-to-DC) converter is designed to improve the power saving which could be achieved by the mechanical tracking alone. Also, new electronic and mechanical MPPT methods are developed, and their combination, so-called electro-mechanical MPPT, is tested in a real environment to verify its usefulness.

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17

Forat, m. Taher QADOSH, and Prof. GÜL KURT Asst. "Maximum Power Point Tracking in PV System with Home Applications." Engineering and Technology Journal 9, no. 12 (2024): 5680–86. https://doi.org/10.5281/zenodo.14548467.

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The use of photovoltaic energy in modern transmission systems is increasingly preferred due to its environmentally friendly features. Modular photovoltaics show a nonlinear correlation between the generated power and the environmental conditions. This study presents a Maximum Power Point Tracker (MPPT) based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) to optimize solar power systems. The designed controller optimizes the output power of a DC-DC converter linked to a 250W solar array. The complete analysis of the model is done using MATLAB/SIMULINK, considering the key characteristics of the technical data. The controller behavior is evaluated under diverse weather conditions. The paper suggests that the controller is effective in tracking peak power of the panel.

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18

Azmi, Muhammad Hasbi, Ayman Nurshazwan Abdul Rashid, Siti Zaliha Mohammad Noor, Muhammad Murtadha Othman, Suleiman Musa, and Pusparini Dewi Abd Aziz. "Battery management system using Jaya maximum power point tracking technique." International Journal of Power Electronics and Drive Systems 16, no. 1 (2025): 622–32. https://doi.org/10.11591/ijpeds.v16.i1.pp622-632.

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This paper introduces the development of a battery management system (BMS) utilizing the Jaya-based maximum power point tracking (MPPT) technique. Previous studies have combined various MPPT techniques with switching methods, each having its pros and cons. Traditional MPPT methods are common but have limited performance. Therefore, artificial intelligence (AI)-based approaches are introduced to enhance and reduce the limitations faced. The Jaya technique is straightforward and easy to implement, making it an attractive choice for MPPT in photovoltaic systems. It is recognized for its effectiveness in eliminating the worst solutions and identifying the best solution with only a few control parameters required for operation. The proposed work aims to develop a BMS using a DC-DC buck converter and the Jaya MPPT technique. The objective is to find the MPP to achieve the desired performance level and ensure the effectiveness of maintaining battery quality, preventing overcharging or undercharging. The system is modeled in MATLAB/Simulink. The findings indicate that the Jaya MPPT demonstrates a tracking speed of less than 1 second to locate the maximum power point (MPP). Furthermore, the BMS is capable of monitoring changes in state of charge (SoC) to determine whether the system is in charging or discharging mode.

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19

Jia, Wen Ting, Xue Ye Wei, Jun Hong Zhang, and Yi Fei Meng. "Optimization of Photovoltaic Array Configurations in Photovoltaic System." Advanced Materials Research 1070-1072 (December 2014): 48–51. http://dx.doi.org/10.4028/www.scientific.net/amr.1070-1072.48.

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Closely related to the actual output power and the light intensity, the temperature of the photovoltaic cell panel and the load of the PV array or the like. In the case of the external environment is stable and load conditions change, the output power of the PV modules exist Maximum Power Point, in order to improve the self-tracking PV system energy conversion efficiency, maximum power point tracking method may ensure the system running at maximum power points. Photovoltaic power generation system, optimize allocation method of PV array are also discussed in this paper.

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20

Miss, Priyanka Gupta* Mr. Amit Agrawal Dr.Dharmendra Kumar Singh. "STUDY OF MAXIMUM POWER POINT TRACKING(MPPT) IN SOLAR PV ARRAY SYSTEM." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 5 (2016): 882–88. https://doi.org/10.5281/zenodo.52496.

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The problem being solved using maximum power point tracking MPPT techniques is to find the voltage VMPP or current IMPP at which a photovoltaic module should operate to obtain the maximum power output PMAX under a given temperature and illumination (solar irradiation). This paper gives an overview about some used techniques for power point tracking. The results which will be presented will also demonstrate the influence of temperature and solar irradiation (illumination) on the output power.  

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21

Chai, Yu, and Dong Mei Shang. "The Improvement of Maximum Power Point Tracker Algorithm in Photovoltaic Power System." Applied Mechanics and Materials 157-158 (February 2012): 377–80. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.377.

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Maximum power tracking is one of most important methods to improve efficiency of Photovoltaic power system. By simulating and analyzing the photovoltaic cell model，using Boost circuit to achieve maximum power tracking. Based on the analysis of the constant-voltage method, perturbation and observation method, then combining these two methods，I Put forward the constant-voltage method combined with perturbation and observation method, and has carried on the simulation.

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Mahobia, S. K. "STUDY OF PHOTOVOLTAIC ENERGY STORAGES SYSTEM USING OF MAXIMUM POWER POINT TRACKING." International Journal of Research -GRANTHAALAYAH 5, no. 2 (2017): 119–21. http://dx.doi.org/10.29121/granthaalayah.v5.i2.2017.1711.

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The uniform solar irradiation in the photovoltaic cells, power-voltage characteristics must be unique and the maximum powers are generated from PV cells. The MPPT Device are an essential part for photovoltaic power generation system. Maximum Power Point Tracking (MPPT) are used to optimize photovoltaic cells power.

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Dr., S. K. Mahobia. "STUDY OF PHOTOVOLTAIC ENERGY STORAGES SYSTEM USING OF MAXIMUM POWER POINT TRACKING." International Journal of Research -GRANTHAALAYAH 5, no. 2 (2017): 119–21. https://doi.org/10.5281/zenodo.345457.

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The uniform solar irradiation in the photovoltaic cells, power-voltage characteristics must be unique and the maximum powers are generated from PV cells. The MPPT Device are an essential part for photovoltaic power generation system. Maximum Power Point Tracking (MPPT) are used to optimize photovoltaic cells power.

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24

Ullah, Hafiz. "Microcontroller based maximum power point single axis Tracking System." Bangladesh Journal of Scientific and Industrial Research 47, no. 4 (2013): 427–32. http://dx.doi.org/10.3329/bjsir.v47i4.4689.

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Positioning a photovoltaic (PV) panel in the plane of maximum irradiation can increase the power output up to 57%. An automatic microcontroller based system for maximum power point tracking (MPPT) was designed and analyzed. The system was based on positioning the PV panel perpendicular to the solar irradiation. Photosensors were used to measure the difference of solar radiation intensity among three planes. The tracking system used an 8051 microcontroller to control a stepper motor which rotated the panel towards the plane with highest radiation intensity. The MPPT system was found to be 25.9% more effective in capturing solar power than a fixed panel with the same rating. This system would be useful to increase the power output of currently operating solar panels with minor modifications in mounting. Bangladesh J. Sci. Ind. Res. 47(4), 427-432, 2012 DOI: http://dx.doi.org/10.3329/bjsir.v47i4.4689

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Saldívar, Martha Belem, Laura Zimmermann Soto, Itzel Contreras Carmona, and Otniel Portillo Rodríguez. "Maximum Power Point Tracking Control for a Photovoltaic System." Memorias del Congreso Nacional de Control Automático 7, no. 1 (2024): 208–13. https://doi.org/10.58571/cnca.amca.2024.036.

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The use of renewable energy has experienced significant growth as part of efforts to reduce fossil fuel consumption. Mexico, due to its geographical location, holds significant potential for solar energy development. However, this valuable resource remains underutilized, largely due to the low efficiency of photovoltaic panels. To meet user demand for power, implementing a power converter and control algorithms is essential. This article focuses on the implications of not having a voltage converter and analyzes the performance of various controllers applied to the Maximum Power Point tracking problem. Specifically, it examines Proportional Integral Derivative control, first-order sliding mode control, and Super Twisting sliding mode control under abrupt and smooth changes in temperature and irradiance. The objective is to determine the most efficient and reliable control strategy for solving the stated problem.

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Huang, Bin-Juine, Wei-Zhe Ton, Chen-Chun Wu, et al. "Maximum-power-point tracking control of solar heating system." Solar Energy 86, no. 11 (2012): 3278–87. http://dx.doi.org/10.1016/j.solener.2012.08.019.

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27

Ihnatushenko, Oleh Yaroslavovych. "Testing Maximum Power Point Tracking Controller for PV System." Electronic and Acoustic Engineering 3, no. 4 (2020): 44–48. http://dx.doi.org/10.20535/2617-0965.2020.3.4.200721.

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Gousiya, Shaik, and Chintala Sai Veda Vyas. "Maximum Power Point Tracking Algorithms in Wind Energy System." International Journal of Advance Research and Innovation 8, no. 4 (2020): 93–99. http://dx.doi.org/10.51976/ijari.842015.

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It is vital to determine or extract the highest obtainable wind energy at any wind speed because of the natures unforeseeable wind limitations. Therefore, a smart controller that can monitor the extreme pitch irrespective of wind velocity. This article concentrates on several previous and present techniques for achieving maximum wind energy capacity. The maximum power point tracking (MMPT) solution is numerous, but the issues lends itself to their efficient selection and requires expert understanding about every method to choose an efficient MPP method, as such method alone presents some benefits and drawbacks. Different MPP techniques are discussed and compered in terms of convergence moment, effectiveness, training and implementation complexity and they are characterized based on continual wind speed as well as variable wind speed.

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Wu, Yu-Chi, Meng-Jen Chen, Sih-Hao Huang, Ming-Tsung Tsai, and Chia-Huang Li. "Maximum power point tracking on stand-alone solar power system: Three-point-weighting method incorporating mid-point tracking." International Journal of Electrical Power & Energy Systems 52 (November 2013): 14–24. http://dx.doi.org/10.1016/j.ijepes.2013.03.008.

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Frydrychowicz-Jastrzębska, Grażyna. "Maximum power point tracking in photovoltaic systems." ITM Web of Conferences 28 (2019): 01021. http://dx.doi.org/10.1051/itmconf/20192801021.

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The subject of the analysis was the optimisation of interoperation between the photovoltaic battery (PV) and DC motor, which drives a fan, with respect to the maximum efficiency of conversion of the electric energy into mechanical energy. Based on the block diagram, a mathematical model of this circuit was developed to ensure the mutual matching between the Maximum Power Point (MPP) of the battery and the receiver operation point. A computer simulation of the battery characteristics was conducted taking into account the changing MPP location on the characteristic vs. changes in solar radiation and temperature. The issue was considered for the optimal motor excitation coefficient, both changing and averaged in time. The energy conversion efficiency was determined for selected PV modules, as well as time.

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Muchen, Yuze, and Nadia Farah. "Maximum power point tracking for a photovoltaic power system using the DIRECT algorithm." i-manager's Journal on Power Systems Engineering 12, no. 2 (2024): 15. https://doi.org/10.26634/jps.12.2.21682.

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Photovoltaic (PV) power generation systems require effective maximum power point tracking (MPPT) algorithms to ensure optimal energy conversion efficiency. This research presents a novel MPPT algorithm based on the Dividing Rectangles (DIRECT) algorithm, which offers improved tracking performance under rapidly changing insolation and partial shading conditions. Compared to conventional techniques such as Perturb & Observe (P&O) and Incremental Conductance (INC), the proposed method effectively identifies and tracks the global maximum power point (GMPP) while minimizing steady-state oscillations. The effectiveness of the approach is validated through simulation and experimental results, demonstrating enhanced tracking speed and energy efficiency.

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Souissi, Ahmed, and Othman Hasnaoui. "A Maximum Power Point Tracking Method for a Photovoltaic Power System." International Journal on Engineering Applications (IREA) 8, no. 4 (2020): 133. http://dx.doi.org/10.15866/irea.v8i4.18494.

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Han, Lei, Xia Wang, and Guang Wei Wang. "Maximum Power Point Tracking for the Micro-Scale Photovoltaic Power System." Applied Mechanics and Materials 734 (February 2015): 771–74. http://dx.doi.org/10.4028/www.scientific.net/amm.734.771.

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In this paper, we give a comprehensive consideration on the maximum power point tracking (MPPT) algorithm for micro-scale solar energy harvesting system. Basing on the comparison analysis the MPPT algorithm of fractional open circuit voltage (FOCV) is certificated to be the simplest method among all the algorithms focus on small size photovoltaic devices. As a validation, an example is given to demonstrate the effectiveness of the proposed idea.

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Soetedjo, Aryuanto, Abraham Lomi, Yusuf Ismail Nakhoda, and Awan Uji Krismanto. "Modeling of Maximum Power Point Tracking Controller for Solar Power System." TELKOMNIKA (Telecommunication Computing Electronics and Control) 10, no. 3 (2012): 419. http://dx.doi.org/10.12928/telkomnika.v10i3.819.

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35

Kasa, N., T. Iida, and H. Iwamoto. "Maximum power point tracking with capacitor identifier for photovoltaic power system." IEE Proceedings - Electric Power Applications 147, no. 6 (2000): 497. http://dx.doi.org/10.1049/ip-epa:20000641.

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Ali, Mahmoud N., Karar Mahmoud, Matti Lehtonen, and Mohamed M. F. Darwish. "Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic." Sensors 21, no. 4 (2021): 1244. http://dx.doi.org/10.3390/s21041244.

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This paper addresses the improvement of tracking of the maximum power point upon the variations of the environmental conditions and hence improving photovoltaic efficiency. Rather than the traditional methods of maximum power point tracking, artificial intelligence is utilized to design a high-performance maximum power point tracking control system. In this paper, two artificial intelligence-based maximum power point tracking systems are proposed for grid-connected photovoltaic units. The first design is based on an optimized fuzzy logic control using genetic algorithm and particle swarm optimization for the maximum power point tracking system. In turn, the second design depends on the genetic algorithm-based artificial neural network. Each of the two artificial intelligence-based systems has its privileged response according to the solar radiation and temperature levels. Then, a novel combination of the two designs is introduced to maximize the efficiency of the maximum power point tracking system. The novelty of this paper is to employ the metaheuristic optimization technique with the well-known artificial intelligence techniques to provide a better tracking system to be used to harvest the maximum possible power from photovoltaic (PV) arrays. To affirm the efficiency of the proposed tracking systems, their simulation results are compared with some conventional tracking methods from the literature under different conditions. The findings emphasize their superiority in terms of tracking speed and output DC power, which also improve photovoltaic system efficiency.

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Yuan, Qi Ping, Yu Fei Liu, and Ting Ting Chi. "The Dual-Mode Maximum Power Point Tracking Control Method Based on Improved Variable Step Size." Advanced Materials Research 588-589 (November 2012): 1624–27. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1624.

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In the entire PV system, the maximum power point tracking (MPPT) has become an important part of the essential, the maximum power point tracking can improve the output power of photovoltaic power generation system as to improve the overall system power. Constant Voltage Tracking (CVT), Perturbation and Observation (P&O), incremental Conductivity, Short circuit control, Hysteresis comparing are the most commonly used methods. Due to a variety of methods have their advantages and disadvantages to each other, to improve efficiency, control accuracy, speed up the response, this paper, put up a program based on reforming the progress in dual-mode maximum power point tracking and this program can be faster and more accurate to find the maximum power point in the current environment, also reduce the oscillation near the maximum power point and improve the efficiency of solar photovoltaic grid-connected system.

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Luo, Ping, Xia Fu Lv, and Min Li. "Maximum Power Point Tracking Control for Photovoltaic Module." Advanced Materials Research 773 (September 2013): 175–80. http://dx.doi.org/10.4028/www.scientific.net/amr.773.175.

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Photovoltaic (PV) system is one kind of important renewable energy source because of its pollution-free and inexhaustible nature. The efficiency of the PV is an important factor that will determine the output power. A maximum power point tracking (MPPT) control was discussed and was simulated based on PSIM. The result of simulation showed that this method was efficiently and quickly.

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Du, Wei, Wei Han, and You Fei Tan. "Improved Golden Section Application in Maximum Power Point Tracking of Photovoltaic Power Generation." Advanced Materials Research 953-954 (June 2014): 52–56. http://dx.doi.org/10.4028/www.scientific.net/amr.953-954.52.

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In order to increase the output power of the photovoltaic system, the maximum power point tracking is needed. As the starting point of research in the output nonlinear characteristics, analysis of the advantages and disadvantages of the conventional algorithm and have the poor dynamic and steady-state performance of the maximum power point tracking(MPPT), the improvement method of golden section(IGSS) is applied to the photovoltaic power generation system. The results indicate that the method can quickly track the maximum power point of photovoltaic cells.

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Hu, Bo, and Zai Lin Piao. "On the Contrast and Research of Maximum Power Point Tracking Control in the Microgrids PV System." Advanced Materials Research 756-759 (September 2013): 361–64. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.361.

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In microgrids operation, photovoltaic power generation system need to quickly and accurately for maximum power point tracking (MPPT), namely MPPT technology, because of the diversity of the control method, its control effect is different, a realization of process is also great difference. And because the current maximum power point tracking method is not enough accurate and mature, which led to the photovoltaic system power loss, this paper expounds the advantages and disadvantages of all kinds of tracking control method, in light of the maximum power point tracking control theory, and sums up the mathematical model of optimization, seeking the optimal control method. The paper is to explore maximum power point tracking control method development mentality, to look forward the research direction of the microgrids PV system.

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Bahri, Hamza, and Adelghani Harrag. "Matlab/Stateflow P&O and ICMPPT Implementation for PEM Fuel Cell Power System." Progress in Solar Energy and Engineering Systems 5, no. 1 (2021): 1–7. http://dx.doi.org/10.18280/psees.050101.

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This paper outlines an innovative way in the assessment of proton exchange membrane fuel cell maximum power point tracking using Matlab/Stateflow implementation of variable step size version of perturb and observe and incremental conductance maximum power point tracking algorithms. In this study, the perturb and observe as well as the incremental conductance maximum power point tracking controllers have been completely implemented as Matlab/Stateflow models having as inputs: cell voltage, cell current and the variable step size; the model's output is the pulse width modulation ratio to drive the DC-DC boost converter for supplying the maximum power available from the 7kW proton exchange membrane fuel cell to a 50W resistive load. Simulation obtained results under different test scenarios prove the effectiveness of the proposed Matlab/Stateflow maximum power point tracking models that can provide accurate results and giving a strong tool to test and validate maximum power point tracking controllers.

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Srinivas, Paruchuri, and P. Swapna. "Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 9 (2022): 26–39. http://dx.doi.org/10.17762/ijritcc.v10i9.5748.

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Photovoltaic (PV) systems are the major nonconventional sources for power generation for present power strategy. The power of PV system has rapid increase because of its unpolluted, less noise and limited maintenance. But whole PV system has two main disadvantages drawbacks, that is, the power generation of it is quite low and the output power is nonlinear, which is influenced by climatic conditions, namely environmental temperature and the solar irradiation. The natural limiting factor is that PV potential in respect of temperature and irradiation has nonlinear output behavior. An automated power tracking method, for example, maximum power point tracking (MPPT), is necessarily applied to improve the power generation of PV systems. The MPPT methods undergo serious challenges when the PV system is under partial shade condition because PV shows several peaks in power. Hence, the exploration method might easily be misguided and might trapped to the local maxima. Therefore, a reasonable exploratory method must be constructed, which has to determine the global maxima for PV of shaded partially. The traditional approaches namely constant voltage tracking (CVT), perturb and observe (P&O), hill climbing (HC), Incremental Conductance (INC), and fractional open circuit voltage (FOCV) methods, indeed some of their improved types, are quite incompetent in tracking the global MPP (GMPP). Traditional techniques and soft computing-based bio-inspired and nature-inspired algorithms applied to MPPT were reviewed to explore the possibility for research while optimizing the PV system with global maximum output power under partially shading conditions. This paper is aimed to review, compare, and analyze almost all the techniques that implemented so far. Further this paper provides adequate details about algorithms that focuses to derive improved MPPT under non-uniform irradiation. Each algorithm got merits and demerits of its own with respect to the converging speed, computing time, complexity of coding, hardware suitability, stability and so on.

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Andrés, Julián Saavedra-Montes, Andrés Ramos-Paja Carlos, and Alejandro Ramírez-Gómez Carlos. "Model-based maximum power point tracking for wind generators." Revista Facultad de Ingeniería –redin-, no. 79 (June 16, 2016): 75–83. https://doi.org/10.17533/udea.redin.n79a08.

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A model-based maximum power point tracking solution for wind systems is presented in this paper. The strategy uses the Loss-free resistor concept and a generator model, which relates the load impedance required to produce the maximum power depending on the generator rotor speed. The strategy performance is validated through simulation and the emulation of a multi-machine wind generation system. With the proposed strategy, it is possible to extract the maximum power of each generator and, therefore, the maximum power of the generation system.

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Jamri, M. S., A. M. Kassim, and M. R. Hashim. "A Voltage Mode Control Maximum Power Point Tracking for Stand-Alone Photovoltaic System." Applied Mechanics and Materials 313-314 (March 2013): 503–7. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.503.

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The purpose of this paper is to discuss a modeling and control of stand- alone photovoltaic system using voltage mode control maximum power point tracking (MPPT) method. The PV module was modeled based on the parameters obtained from a commercial PV data sheet while voltage mode control was modeled using simulink block model. A DC-DC boost converter was chosen to step-up and regulates the input DC voltage of the PV module. The voltage mode control (VMC) maximum power point tracking model was simulated and compared with perturb and observe (P&O) maximum power point tracker in order to validate the performance of output results. Results showed that the voltage mode control maximum power point tracking model yields the similar performance as produced by the photovoltaic system controlled by perturb and observe maximum power point tracking algorithm. The simulation is made to analyze the voltage, current and power generated under the changing irradiant and temperature condition. As a conclusion, the voltage mode control technique is possible to implement which yields the similar performance as the results from conventional MPPT method.

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Lee, Hyeon-Seok, and Jae-Jung Yun. "Advanced MPPT Algorithm for Distributed Photovoltaic Systems." Energies 12, no. 18 (2019): 3576. http://dx.doi.org/10.3390/en12183576.

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The basic and adaptive maximum power point tracking algorithms have been studied for distributed photovoltaic systems to maximize the energy production of a photovoltaic (PV) module. However, the basic maximum power point tracking algorithms using a fixed step size, such as perturb and observe and incremental conductance, suffer from a trade-off between tracking accuracy and tracking speed. Although the adaptive maximum power point tracking algorithms using a variable step size improve the maximum power point tracking efficiency and dynamic response of the basic algorithms, these algorithms still have the oscillations at the maximum power point, because the variable step size is sensitive to external factors. Therefore, this paper proposes an enhanced maximum power point tracking algorithm that can have fast dynamic response, low oscillations, and high maximum power point tracking efficiency. To achieve these advantages, the proposed maximum power point tracking algorithm uses two methods that can apply the optimal step size to each operating range. In the operating range near the maximum power point, a small fixed step size is used to minimize the oscillations at the maximum power point. In contrast, in the operating range far from the maximum power point, a variable step size proportional to the slope of the power-voltage curve of PV module is used to achieve fast tracking speed under dynamic weather conditions. As a result, the proposed algorithm can achieve higher maximum power point tracking efficiency, faster dynamic response, and lower oscillations than the basic and adaptive algorithms. The theoretical analysis and performance of the proposed algorithm were verified by experimental results. In addition, the comparative experimental results of the proposed algorithm with the other maximum power point tracking algorithms show the superiority of the proposed algorithm.

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Xu, Xiaowei, Wei Zhou, Wenhua Xu, et al. "Application of the MPPT Control Algorithm Based on Hybrid Quantum Particle Swarm Optimization in a Photovoltaic Power Generation System." Processes 11, no. 5 (2023): 1456. http://dx.doi.org/10.3390/pr11051456.

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The Maximum Power Point Tracking method is a mainstream method for improving the operational efficiency of photovoltaic power generation, but it is difficult to adapt to the rapidly changing environment and lacks good steady-state and dynamic performance. To achieve fast and accurate tracking of the Maximum Power Point Tracking, the optimization of the contraction expansion coefficient of the Quantum Particle Swarm Optimization algorithm is studied, and then the Levy flight strategy is introduced to optimize the algorithm’s global convergence ability, thereby constructing the Hybrid Quantum Particle Swarm Optimization algorithm. Finally, the Hybrid Quantum Particle Swarm Optimization combined with the Maximum Power Point Tracking algorithm is obtained. The research results showed that the Hybrid Quantum Particle Swarm Optimization combined with the Maximum Power Point Tracking algorithm can always converge to the theoretical minimum value with a probability of more than 94% in the Roserock function and Rastigin function tests. The tracking error of the Hybrid Quantum Particle Swarm Optimization combined with the Maximum Power Point Tracking algorithm was less than 1% under lighting conditions. The convergence time of the Hybrid Quantum Particle Swarm Optimization combined with the Maximum Power Point Tracking algorithm in arbitrary shadow occlusion environments can reach a stable state within 0.1 s. In summary, the Hybrid Quantum Particle Swarm Optimization combined with the Maximum Power Point Tracking algorithm proposed in the study has excellent performance and very wide applicability. To a certain extent, it improves the total power generation capacity of the photovoltaic power generation system and the power generation efficiency of the photovoltaic array.

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Li, Feng Ting, and En Rang Zheng. "Research on Maximum Power Point Tracking Control System of Variable Speed Wind Turbine." Applied Mechanics and Materials 65 (June 2011): 389–93. http://dx.doi.org/10.4028/www.scientific.net/amm.65.389.

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This paper analyzes the operating characteristics of wind turbine and introduces the principle of maximum power point tracking control system of variable speed wind turbine. A improved maximum power tracking control strategy is proposed for large inertia wind power systems in order to achieve maximum wind power capture and increased utilization of wind energy when wind turbines is below the rated wind speed. A variable speed wind power generation system is modeled and simulated in the Simulink environment of the Matlab .The simulation results proves the correctness and feasibility of the tracking control strategy suggested in this paper.

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Tian, Zhi Guang, Lin Tian, Jian He, Zhen Hua Huang, Da Hai Zhang, and De Da Sun. "Maximum Power Point Tracking Based on SVR and GA." Applied Mechanics and Materials 687-691 (November 2014): 3231–34. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.3231.

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With the increasing application of Photovoltaic (PV) power system, it is important to make PV system always achieve its maximum power output, so maximum power point tracking (MPPT) technique develops. Based on Support Vector Regression (SVR) and Genetic Algorithm (GA), a novel MPPT method is proposed in this paper. The SVR model uses the solar radiation and temperature as two inputs, and uses the voltage at maximum power point (MPP) as output. Furthermore, GA is introduced to search the best parameters for SVR. Results validate the effectiveness of the proposed MPPT method.

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Raghappriya, M., K. M. Devadharshini, and S. Karrishma. "Fuzzy Logic Based Maximum Power Point Tracking of Photovoltaic System." Journal of Innovative Image Processing 4, no. 1 (2022): 49–60. http://dx.doi.org/10.36548/jiip.2022.1.006.

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A photovoltaic (PV) system converts light into electricity and has nonlinear characteristics between power and voltage. The PV system is affected by changes in environmental conditions and other factors. In PV system, the maximum power is obtained at the operating point. Many Maximum Power Point Tracking (MPPT) algorithms have been presented and explored in the literature, however many of them have drawbacks in terms of adaptability, efficiency, and accuracy. Traditional controllers are incapable of providing a better response due to the nonlinear nature of PV module current-voltage characteristics. The primary objective of this work is to design and implement a fuzzy logic control for obtaining MPPT for a photovoltaic system. Fuzzy logic control is a heuristic method to controller design that uses artificial intelligence to track maximum power. In this method, desirable results are achieved by defining the logical rule and specific range of membership functions. Simulink is used to develop and simulate a maximum power point tracking system that includes a photovoltaic voltaic module, a quadratic boost converter, and a fuzzy controller.

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Veligorskyi, Oleksandr, Oleksandr Husev, Viktor Shevchenko, et al. "A novel hysteresis power point optimizer for distributed solar power generation." Electrical, Control and Communication Engineering 14, no. 1 (2018): 12–22. http://dx.doi.org/10.2478/ecce-2018-0002.

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Abstract This paper proposes a new photovoltaic panel maximum-power-point optimizer based on a buck converter. It can be connected to the DC-link distributed energy harvesting system that should perform the true maximum-power-point tracking algorithm based on maintaining a constant DC link voltage. The algorithm is based on the sensorless hysteresis control and ensures high efficiency. Three different realizations of proposed hysteresis optimizers have been analyzed in the paper, including operation principle and adjustment of hysteresis intervals. An experimental study has been performed for a portable low-power photovoltaic system in case of different loads and irradiance levels. The efficiency of maximum power point tracking has been calculated analytically for different hysteresis intervals and validated by experiment, which proved a 97-98 % efficiency of tracking for different PV panel temperatures. The proposed solution is recommended to be used in small- and medium-sized power systems where the price of the conventional maximum power point tracking converter is very high and is comparable to the cost of the individual panel

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