Simulation and Characterization of Genetic Algorithm Implemented on MPPT for PV System under Partial Shading Condition

Shading is one of the most critical factors that produces a reduction in power in photovoltaic (PV) modules. The main causes of shading are related to cloud cover; local specificity; natural characteristics; building and other civil works; and the presence of the PV system itself. A reduction in overall radiation produces a consequent reduction in electric power. Another more problematic effect is associated with the partial shading of the PV modules. The shaded cell behaves as a load, dissipating energy and increasing its temperature. This effect can involve irreversible changes to the PV module, with a decrease in performance that can even cause the destruction of the shaded cell.The main aim of this work is the development of a testing procedure for the performance evaluation of commercial PV modules in the presence of partial shading on one cell. Tests were carried out using thermographic and electric measurements and by varying the shading levels according to IEC standards. Shading up to total darkening is achieved by means of a number of filters that reduce the direct solar irradiance.As a case study, a complete characterisation of a 180 Wp polycrystalline PV module was performed according to the proposed testing procedure, showing that high temperatures can be measured on the shaded PV module surface even if only 50 % of the surface of one cell of the PV module is darkened.

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Performance characterization of a PV system using wavelet transform and genetic algorithm

Renewable Energy and Power Quality Journal ◽

10.24084/repqj11.350 ◽

2013 ◽

pp. 495-500

Author(s):

P. Janik ◽

P. Kostyla ◽

J. Rezmer ◽

J. Szymanda ◽

T. Sikorski ◽

...

Keyword(s):

Genetic Algorithm ◽

Wavelet Transform ◽

Pv System ◽

Performance Characterization

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Automatic Detection and Characterization of Partial Shading in PV System

2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC) ◽

10.1109/pvsc.2018.8548279 ◽

2018 ◽

Cited By ~ 3

Author(s):

Levi Davies ◽

Ryan Thornton ◽

Paul Hudson ◽

Biswajit Ray

Keyword(s):

Automatic Detection ◽

Pv System ◽

Partial Shading

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A Novel Combined Particle Swarm Optimization and Genetic Algorithm MPPT Control Method for Multiple Photovoltaic Arrays at Partial Shading

Journal of Energy Resources Technology ◽

10.1115/1.4007940 ◽

2012 ◽

Vol 135 (1) ◽

Cited By ~ 18

Author(s):

Liqun Liu ◽

Chunxia Liu

Keyword(s):

Genetic Algorithm ◽

Particle Swarm Optimization ◽

Large Scale ◽

Control Method ◽

Particle Swarm ◽

Pv System ◽

Maximum Power Point ◽

Partial Shading ◽

Swarm Optimization ◽

Power Point

The output characteristics of multiple photovoltaic (PV) arrays at partial shading are characterized by multiple steps and peaks. This makes that the maximum power point tracking (MPPT) of a large scale PV system becomes a difficult task. The conventional MPPT control method was unable to track the maximum power point (MPP) under random partial shading conditions, making the output efficiency of the PV system is low. To overcome this difficulty, in this paper, an improved MPPT control method with better performance based on the genetic algorithm (GA) and adaptive particle swarm optimization (APSO) algorithm is proposed to solve the random partial shading problem. The proposed genetic algorithm adaptive particle swarm optimization (GAAPSO) method conveniently can be used in the real-time MPPT control strategy for large scale PV system, and the implementation of the collect circuit is easy to gain the global peak of multiple PV arrays, thereby resulting in lower cost, higher overall efficiency. The proposed GAAPSO method has been experimentally validated by using several illustrative examples. Simulations and experimental results demonstrate that the GAAPSO method provides effective, fast, and perfect tracking.

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Reconfigurable Distributed Power Electronics Technique for Solar PV Systems

Electronics ◽

10.3390/electronics10091121 ◽

2021 ◽

Vol 10 (9) ◽

pp. 1121

Author(s):

Kamran Ali Khan Niazi ◽

Yongheng Yang ◽

Tamas Kerekes ◽

Dezso Sera

Keyword(s):

Energy Yield ◽

Solar Pv ◽

Charge Redistribution ◽

Pv System ◽

Partial Shading ◽

Pv Systems ◽

Simulation Based ◽

In Series ◽

A Cell ◽

Power Balancing

A reconfiguration technique using a switched-capacitor (SC)-based voltage equalizer differential power processing (DPP) concept is proposed in this paper for photovoltaic (PV) systems at a cell/subpanel/panel-level. The proposed active diffusion charge redistribution (ADCR) architecture increases the energy yield during mismatch and adds a voltage boosting capability to the PV system under no mismatch by connected the available PV cells/panels in series. The technique performs a reconfiguration by measuring the PV cell/panel voltages and their irradiances. The power balancing is achieved by charge redistribution through SC under mismatch conditions, e.g., partial shading. Moreover, PV cells/panels remain in series under no mismatch. Overall, this paper analyzes, simulates, and evaluates the effectiveness of the proposed DPP architecture through a simulation-based model prepared in PSIM. Additionally, the effectiveness is also demonstrated by comparing it with existing conventional DPP and traditional bypass diode architecture.

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

Sustainability ◽

10.3390/su13052656 ◽

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.

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An Optimized PV Control System Based on the Emperor Penguin Optimizer

Energies ◽

10.3390/en14030751 ◽

2021 ◽

Vol 14 (3) ◽

pp. 751

Author(s):

Mariam A. Sameh ◽

Mostafa I. Marei ◽

M. A. Badr ◽

Mahmoud A. Attia

Keyword(s):

Duty Cycle ◽

Optimization Technique ◽

Pso Algorithm ◽

Boost Converter ◽

Emperor Penguin ◽

Pv System ◽

Partial Shading ◽

Pv Systems ◽

Point Tracking ◽

Grid Connected Inverter

During the day, photovoltaic (PV) systems are exposed to different sunlight conditions in addition to partial shading (PS). Accordingly, maximum power point tracking (MPPT) techniques have become essential for PV systems to secure harvesting the maximum possible power from the PV modules. In this paper, optimized control is performed through the application of relatively newly developed optimization algorithms to PV systems under Partial Shading (PS) conditions. The initial value of the duty cycle of the boost converter is optimized for maximizing the amount of power extracted from the PV arrays. The emperor penguin optimizer (EPO) is proposed not only to optimize the initial setting of duty cycle but to tune the gains of controllers used for the boost converter and the grid-connected inverter of the PV system. In addition, the performance of the proposed system based on the EPO algorithm is compared with another newly developed optimization technique based on the cuttlefish algorithm (CFA). Moreover, particle swarm optimization (PSO) algorithm is used as a reference algorithm to compare results with both EPO and CFA. PSO is chosen since it is an old, well-tested, and effective algorithm. For the evaluation of performance of the proposed PV system using the proposed algorithms under different PS conditions, results are recorded and introduced.

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

Energies ◽

10.3390/en14092521 ◽

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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