scholarly journals A Novel Photovoltaic Module Quick Regulate MPPT Algorithm for Uniform Irradiation and Partial Shading Conditions

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2213
Author(s):  
Hwa-Dong Liu ◽  
Shiue-Der Lu ◽  
Yu-Lin Lee ◽  
Chang-Hua Lin
Keyword(s):  
Open Circuit ◽  
Hill Climbing ◽  
Photovoltaic Module ◽  
Partial Shading ◽  
Irradiance Level ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Key Factor ◽  
Power Point ◽  
The Hill

This study proposed a new photovoltaic module quick regulate (PVM-QR) maximum power point tracking (MPPT) algorithm, which can eliminate the disturbance problem of the hill-climbing (HC) algorithm, especially under low irradiance level and partial shading conditions (PSC). This proposed algorithm has the advantage that it only uses the detection photovoltaic module (PVM) impedance and the open-circuit voltage to simply and quickly calculate the PVM temperature, the irradiance level, and then the key factor parameter u. To achieve the MPPT quickly and accurately, this proposed algorithm is developed for the prediction of the best MPPT duty cycle based on the irradiance level, parameter u, and load. This study verified the proposed MPPT by the measurement results, where the HC algorithm MPPT has 95% efficiency at 0.55 kW/m2 but diverges at 0.2 kW/m2 under uniform irradiation conditions (UIC), and the proposed MPPT algorithm has an improved efficiency (99%) under the same conditions. Moreover, the proposed MPPT algorithm has 99% efficiency under PSC, while the HC algorithm MPPT’s efficiency is 66%. This study implemented a simple-design circuit with the proposed MPPT algorithm for UIC and PSC, where the actual experiment results can also verify that the proposed algorithm performs better than the HC algorithm.

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 Necessity Analysis of Bypass Diode for AC Module under Partial Shading Condition

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4778
Author(s):  
Huixue Ren ◽  
Peide Han
Keyword(s):  
Hot Spot ◽  
Local Maximum ◽  
Maximum Power ◽  
Photovoltaic Module ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Bypass Diode ◽  
Power Point

To protect a photovoltaic module from the hot spot effect more efficiently, an AC (alternating current) module that contains a module-level MPPT (maximum power point tracking) has been put forward. In this paper, operation states of shadowed solar cells and relevant bypass diodes were studied through MATLAB/Simulink tools, and a commercial PV module was used to reveal the temperature change when working at different LMPP (local maximum power point). Experiment results show that bypass diode can reduce power loss for the AC module to some extent but has a limited effect on protecting the AC module from the hot spot effect. Instead, it is more likely to form a local hot spot when the bypass diode turns on, and the worst shading condition for the AC module with bypass diode is about 46.5% during work states.

Development of Artificial Neural Network Based MPPT for Photovoltaic System during Shading Condition

2013 ◽  
Vol 448-453 ◽  
pp. 1573-1578 ◽  
Author(s):  
Mahamad Abd Kadir ◽  
Saon Sharifah
Keyword(s):  
Neural Network ◽  
Variable Temperature ◽  
Photovoltaic System ◽  
Photovoltaic Module ◽  
Elman Network ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Network Controller ◽  
Power Point

This paper presents Feedforward Neural network (FFNN) and Elman network controllers to control the maximum power point tracking (MPPT) of photovoltaic (PV). MPPT is a method used to extract the maximum available power from photovoltaic module by designs them to operate efficiently. Thus, cell temperatures and solar irradiances are two critical variable factors to determine PV output powers. The performances of the controller is analyzed in four conditions which are i) constant irradiation and temperature, ii) constant irradiation and variable temperature, iii) constant temperature and variable irradiation and iv) variable temperature and irradiation. The proposed systems are simulated by using MATLAB-SIMULINK. Based on the results, FFNN controller has shown the better performance compare to the Elman network controller during partial shading conditions.

scholarly journals Maximum Power Point Tracking of PV Systems under Partial Shading Conditions Based on Opposition-Based Learning Firefly Algorithm

2021 ◽  
Vol 13 (5) ◽  
pp. 2656
Author(s):  
Ahmed G. Abo-Khalil ◽  
Walied Alharbi ◽  
Abdel-Rahman Al-Qawasmi ◽  
Mohammad Alobaid ◽  
Ibrahim M. Alarifi
Keyword(s):  
Firefly Algorithm ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Opposition Based Learning ◽  
Power Point Tracking ◽  
Convergence Process ◽  
Power Point

This work presents an alternative to the conventional photovoltaic maximum power point tracking (MPPT) methods, by using an opposition-based learning firefly algorithm (OFA) that improves the performance of the Photovoltaic (PV) system both in the uniform irradiance changes and in partial shading conditions. The firefly algorithm is based on fireflies’ search for food, according to which individuals emit progressively more intense glows as they approach the objective, attracting the other fireflies. Therefore, the simulation of this behavior can be conducted by solving the objective function that is directly proportional to the distance from the desired result. To implement this algorithm in case of partial shading conditions, it was necessary to adjust the Firefly Algorithm (FA) parameters to fit the MPPT application. These parameters have been extensively tested, converging satisfactorily and guaranteeing to extract the global maximum power point (GMPP) in the cases of normal and partial shading conditions analyzed. The precise adjustment of the coefficients was made possible by visualizing the movement of the particles during the convergence process, while opposition-based learning (OBL) was used with FA to accelerate the convergence process by allowing the particle to move in the opposite direction. The proposed algorithm was simulated in the closest possible way to authentic operating conditions, and variable irradiance and partial shading conditions were implemented experimentally for a 60 [W] PV system. A two-stage PV grid-connected system was designed and deployed to validate the proposed algorithm. In addition, a comparison between the performance of the Perturbation and Observation (P&O) method and the proposed method was carried out to prove the effectiveness of this method over the conventional methods in tracking the GMPP.

scholarly journals A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2521
Author(s):  
Alfredo Gil-Velasco ◽  
Carlos Aguilar-Castillo
Keyword(s):  
Maximum Power ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Pv Systems ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point ◽  
Computational Resources

There are multiples conditions that lead to partial shading conditions (PSC) in photovoltaic systems (PV). Under these conditions, the harvested energy decreases in the PV system. The maximum power point tracking (MPPT) controller aims to harvest the greatest amount of energy even under partial shading conditions. The simplest available MPPT algorithms fail on PSC, whereas the complex ones are effective but require high computational resources and experience in this type of systems. This paper presents a new MPPT algorithm that is simple but effective in tracking the global maximum power point even in PSC. The simulation and experimental results show excellent performance of the proposed algorithm. Additionally, a comparison with a previously proposed algorithm is presented. The comparison shows that the proposal in this paper is faster in tracking the maximum power point than complex algorithms.

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