scholarly journals Simulations and dSPACE Real-Time Implementation of Photovoltaic Global Maximum Power Extraction under Partial Shading

2020 ◽  
Vol 12 (9) ◽  
pp. 3652
Author(s):  
Fahd A. Alturki ◽  
Abdullrahman A. Al-Shamma’a ◽  
Hassan M. H. Farh
Keyword(s):  
Cuckoo Search ◽  
Maximum Power ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Power Extraction ◽  
Maximum Power Point Tracker ◽  
Power Point ◽  
Global Peak

Under partial shading conditions (PSCs), solar photovoltaic (PV) energy systems generate multiple peaks; one global peak (GP) and several local peaks (LPs). Thus, tracking the GP of the PV systems under PSCs is necessary to enhance the system reliability and efficiency. Conventional maximum power point tracker (MPPT) algorithms are capable of tracking the unique peak under uniform conditions but they fail to track the GP under PSCs. To the best of our knowledge, this paper represents the first study that introduces a comprehensive comparison of three efficient maximum power point tracker (MPPT) algorithms that are used to extract the GP of the PV system under both uniform and PSCs. These MPPT techniques include two metaheuristic techniques, which are cuckoo search optimization (CSO) and particle swarm optimization (PSO) techniques in addition to one conventional MPPT; perturb and observe (P&O). Although the simulation and dSPACE-based experimental results demonstrated the superiority of CSO and PSO in tracking the GP, CSO requires less tracking time and thus provides a higher efficiency than the PSO. In addition, P&O can be used to follow the first peak, regardless if it is a local peak or global peak with notable oscillation.

scholarly journals A Simple Method for Detecting Partial Shading in PV Systems

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4938
Author(s):  
Waleed Al Abri ◽  
Rashid Al Abri ◽  
Hassan Yousef ◽  
Amer Al-Hinai
Keyword(s):  
Accurate Method ◽  
Maximum Power ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Simple Method ◽  
Partial Shading ◽  
Pv Systems ◽  
Power Point ◽  
Global Peak

Partial shading conditions (PSCs) can significantly reduce the output energy produced by photovoltaic (PV) systems. Moreover, when such conditions occur, conventional and advanced maximum power point tracking (MPPT) systems fail to operate the PV system at its peak because the bypassing diodes may cause the PV system to become trapped at a low power point when they are in conduction mode. The PV system can be operated at the global maximum power point (MPP) with the help of global peak searching tools. However, the frequent use of these tools will reduce the output of PV systems since they force the PV system to operate outside its power region while scanning the I-V curve in order to determine the global MPP. Thus, the global peak searching tools should be deployed only when a PSC occurs. In this paper, a simple and accurate method is proposed for detecting PSCs by means of monitoring the sign of voltage changes (positive or negative). The method predicts a PSC if the sign of successive voltage changes is the same for a certain number of successive changes. The proposed method was tested on two types of PV array configurations (series and series–parallel) with several shading patterns emulated on-site. The proposed method correctly and timely identified all emulated shading patterns. It can be used to trigger the global MPP searching techniques for improving the PV system’s output under PSCs; furthermore, it can be used to notify the PV system’s operator of the occurrence of PSCs.

scholarly journals Maximum power point tracking of partially shading PV system using cuckoo search algorithm

2019 ◽  
Vol 10 (2) ◽  
pp. 1081 ◽  
Author(s):  
Ahmed Ibrahim ◽  
Raef Aboelsaud ◽  
Sergey Obukhov
Keyword(s):  
High Efficiency ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Maximum Power ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Power Point

This paper presents a cuckoo search (CS) algorithm for determining the global maximum power point (GMPP) tracking of photovoltaic (PV) under partial shading conditions (PSC). The conventional methods are fail to track the GMPP under PSC, which decrease the reliability of the power system and increase the system losses. The performance of the CS algorithm is compared with perturb and observe (P&O) algorithm for different cases of operations of PV panels under PSC. The CS algorithm used in this work to control directly the duty cycle of the DC-DC converter without proportional integral derivative (PID) controller. The proposed CS model can track the GMPP very accurate with high efficiency in less time under different conditions as well as in PSC.

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.

scholarly journals Stochastic Fractal Search Optimization Algorithm Based Global MPPT for Triple-Junction Photovoltaic Solar System

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4971
Author(s):  
Hegazy Rezk ◽  
Ahmed Fathy
Keyword(s):  
Optimization Algorithm ◽  
Triple Junction ◽  
Maximum Power ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Power Point ◽  
Global Mppt ◽  
Stochastic Fractal Search

A significant growth in PV (photovoltaic) system installations have been observed during the last decade. The PV array has a nonlinear output characteristic because of weather intermittency. Partial shading is an environmental phenomenon that causes multiple peaks in the power curve and has a negative effect on the efficiency of the conventional maximum power point tracking (MPPT) methods. This tends to have a substantial effect on the overall performance of the PV system. Therefore, to enhance the performance of the PV system under shading conditions, the global MPPT technique is mandatory to force the PV system to operate close to the global maximum. In this paper, for the first time, a stochastic fractal search (SFS) optimization algorithm is applied to solve the dilemma of tracking the global power of PV system based triple-junction solar cells under shading conditions. SFS has been nominated because it can converge to the best solution at a fast rate. Moreover, balance between exploration and exploitation phases is one of its main advantages. Therefore, the SFS algorithm has been selected to extract the global maximum power point (MPP) under partial shading conditions. To prove the superiority of the proposed global MPPT–SFS based tracker, several shading scenarios have been considered. The idea of changing the shading scenario is to change the position of the global MPP. The obtained results are compared with common optimizers: Antlion Optimizer (ALO), Cuckoo Search (CS), Flower Pollination Algorithm (FPA), Firefly-Algorithm (FA), Invasive-Weed-Optimization (IWO), JAYA and Gravitational Search Algorithm (GSA). The results of comparison confirmed the effectiveness and robustness of the proposed global MPPT–SFS based tracker over ALO, CS, FPA, FA, IWO, JAYA, and GSA.

scholarly journals A Fast Converging Hybrid MPPT Algorithm Based on ABC and P&O Techniques for a Partially Shaded PV System

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2228
Author(s):  
Carlos Restrepo ◽  
Nicolas Yanẽz-Monsalvez ◽  
Catalina González-Castaño ◽  
Samir Kouro ◽  
Jose Rodriguez
Keyword(s):  
Sliding Mode ◽  
Computational Cost ◽  
Current Control ◽  
Maximum Power ◽  
Superior Performance ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Power Point

Among all the conventional maximum power point tracking (MPPT) techniques for a photovoltaic (PV) system that have been proposed, incremental conductance (INC) and perturb and observe (P&O) are the most popular because of their simplicity and ease of implementation. However, under partial shading conditions (PSCs), these MPPT algorithms fail to track the global maximum power point (GMPP) and instead converge into local maximum power points (LMPPs), resulting in considerable PV power loss. This paper presents a new hybrid MPPT technique combining the artificial bee colony (ABC) and P&O algorithms named ABC-P&O. The P&O technique is used to track the MPP under uniform irradiance, and only during irradiance variations is the ABC algorithm employed. The effectiveness of the proposed hybrid algorithm at tracking the GMPP, under both uniform and nonuniform irradiance conditions, was assessed by hardware-in-the-loop (HIL) tests employed by a dc–dc boost converter. Then, the ABC-P&O strategy was applied to obtain the voltage reference for the outer PI control loop, which provided the current reference to the discrete-time sliding-mode current control. The ABC-P&O algorithm has a reasonable computational cost, allowing the use of a commercial, low-priced digital signal controller (DSC) with outer voltage and inner current control loops. Many challenging tests validated that the proposed ABC-P&O technique converges fast to the GMPP with high efficiency and superior performance under different PSCs.

scholarly journals MPPT for a PV Grid-Connected System to Improve Efficiency under Partial Shading Conditions

2020 ◽  
Vol 12 (24) ◽  
pp. 10310 ◽  
Author(s):  
Abdulaziz Almutairi ◽  
Ahmed G. Abo-Khalil ◽  
Khairy Sayed ◽  
Naif Albagami
Keyword(s):  
Solar Cell ◽  
Local Maximum ◽  
Maximum Power ◽  
Convergence Time ◽  
Global Maximum ◽  
Cell Array ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Power Point

The disadvantage of photovoltaic (PV) power generation is that output power decreases due to the presence of clouds or shade. Moreover, it can only be used when the sun is shining. Consequently, there is a need for further active research into the maximum power point tracking (MPPT) technique, which can maximize the power of solar cells. When the solar cell array is partially shaded due to the influence of clouds or buildings, the solar cell characteristic has a number of local maximum power points (LMPPs). Conventional MPPT techniques do not follow the actual maximum power point, namely, the global maximum power point (GMPP), but stay in the LMPP. Therefore, an analysis of the occurrence of multiple LMPPs due to partial shading, as well as a study on the MPPT technique that can trace GMPP, is needed. In order to overcome this obstacle, the grey wolf optimization (GWO) method is proposed in order to track the global maximum power point and to maximize the energy extraction of the PV system. In addition, opposition-based learning is integrated with the GWO to accelerate the MPPT search process and to reduce convergence time. Simultaneously, the DC link voltage is controlled to reduce sudden variations in voltage in the event of transients of solar radiation and/or temperature. Experimental tests are presented to validate the effectiveness of the proposed MPPT method during uniform irradiance and partial shading conditions. The proposed method is compared with the perturbation and observation method.

scholarly journals Fractional Chaos Maps with Flower Pollination Algorithm for Partial Shading Mitigation of Photovoltaic Systems

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3548 ◽  
Author(s):  
Dalia Yousri ◽  
Thanikanti Sudhakar Babu ◽  
Dalia Allam ◽  
Vigna. K. Ramachandaramurthy ◽  
Eman Beshr ◽  
...  
Keyword(s):  
Dynamic Change ◽  
Optimization Technique ◽  
Maximum Power ◽  
Flower Pollination Algorithm ◽  
Global Maximum ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Flower Pollination ◽  
Power Point

Solar Photovoltaic (PV) systems have become prominent and have attained the attention of energy engineers, governments and researchers. To achieve the maximum benefit from the PV system in spite of its nonlinear characteristic and environmental conditions, finding a robust maximum power point tracking method is essential. Over two decades, various researchers proposed numerous MPPT methods, but they failed to evaluate their methods on consistency, reliability, and robustness over several numbers of runs. Most of the researchers examined one configuration and they did not to consider the dynamic change in the irradiation conditions. Therefore, in this manuscript, the authors introduced a novel optimization technique Fractional chaotic Flower Pollination Algorithm (FC-FPA), by merging fractional chaos maps with flower pollination algorithm (FPA). The proposed technique, help FPA in extracting the Global Maximum Power Point (GMPP) under different partial shading patterns including with different PV array configurations. The proposed FC-FPA technique is tested and evaluated over 5 different patterns of partial shading conditions. The first three patterns are tested over 4S configuration made with Shell S36 PV module. The other two patterns are applied to the 4S2P configuration of Shell SM55 PV panels. The performance of the proposed variant is investigated by tracking the GMPP for abruptly changing shade pattern. Exclusive statistical analysis is performed over several numbers of runs. Comparison with perturb and observe MPPT technique is established. These results confirm that, the proposed method shows fast convergence, zero oscillation and rapid response for the dynamic change in irradiation with consistent behavior.

Cuckoo Search Based Approach Towards Maximum Power Point Tracking for Solar Photovoltaic System Under Partial Shading

2019 ◽  
Vol 16 (8) ◽  
pp. 3338-3345 ◽  
Author(s):  
Paresh S. Nasikkar ◽  
Chandrakant D. Bhos
Keyword(s):  
Maximum Power Point Tracking ◽  
Cuckoo Search ◽  
Maximum Power ◽  
Global Maximum ◽  
Solar Pv ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Extracting the maximum power from as solar PV system is a critical task when high changes in light intensity or Partial Shading Condition (PSC) are experienced. The latter case is more difficult as it creates multiple maxima points on P–V curve. In this way, it is obligatory to thoroughly pick a precise Maximum Power Point Tracking (MPPT) method which recognizes adequately the Global Maximum Power Point (GMPP) and tracks it under partial shading. This paper first describes the modeling of PV module and PV characteristics under uniform irradiance as well as effect of PSC on PV characteristics. In the latter sections, a review of conventional and intelligent MPPT methods is done. To tackle the problem of MPPT under PSC, two metaheurisric algorithms namely Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are described briefly. A new optimization method called Cuckoo Search (CS) is implemented in MATLAB SIMULINK tool and tested under three different PSC patterns. A comparative analysis of different MPPT strategies is made after analyzing the results.

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