scholarly journals Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1962
Author(s):  
Muhammad Hamza Zafar ◽  
Thamraa Al-shahrani ◽  
Noman Mujeeb Khan ◽  
Adeel Feroz Mirza ◽  
Majad Mansoor ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Statistical Analysis ◽  
Optimization Algorithm ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Pv Systems ◽  
Power Point

The most cost-effective electrical energy is produced by photovoltaic (PV) systems, and with the smallest carbon footprint, making it a sustainable renewable energy. They provide an excellent alternative to the existing fossil fuel-based energy systems, while providing 4% of global electricity demand. PV system efficiency is significantly reduced by the intrinsic non-linear model, maximum power point (MPP), and partial shading (PS) effects. These two problems cause major power loss. To devise the maximum power point tracking (MPPT) control of the PV system, a novel group teaching optimization algorithm (GTOA) based controller is presented, which effectively deals with the PS and complex partial shading (CPS) conditions. Four case studies were employed that included fast-changing irradiance, PS, and CPS to test the robustness of the proposed MPPT technique. The performance of the GTOA was compared with the latest bio-inspired techniques, i.e., dragon fly optimization (DFO), cuckoo search (CS), particle swarm optimization (PSO), particle swarm optimization gravitational search (PSOGS), and conventional perturb and observe (P&O). The GTOA tracked global MPP with the highest 99.9% efficiency, while maintaining the magnitude of the oscillation <0.5 W at global maxima (GM). Moreover, 13–35% faster tracking times, and 54% settling times were achieved, compared to existing techniques. Statistical analysis was carried out to validate the robustness and effectiveness of the GTOA. Comprehensive analytical and statistical analysis solidified the superior performance of the proposed GTOA based MPPT technique.

scholarly journals Maximum Power Point Tracking Method for Photovoltaic System Based on Enhanced Particle Swarm Optimization Algorithm Under Partial Shading Condition

2020 ◽  
Vol 13 (6) ◽  
pp. 241-254
Author(s):  
Anas Kamil ◽  
◽  
Mahmoud Nasr ◽  
Shamam Alwash ◽  
◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Maximum Power ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Power Point

The maximum power point tracking (MPPT) is an essential key to ensure that the photovoltaic (PV) system is operated at the highest possible power generation. This paper presents an efficient MPPT method for the PV system based on an enhanced particle swarm optimization algorithm to track the location of the global maximum power point, whatever its location changes in the search space under all environmental conditions, including the partial shading on strings. In this paper, the formulation of the conventional particle swarm optimization algorithm is enhanced to decrease the searching time and the oscillation of the generated output power as well as the power losses in the online tracking process. This enhancement can be achieved by utilizing a special time-varying weighting coefficient and removing the effect of some other coefficients in the conventional particle swarm optimization algorithm (PSO) that cause winding of the particles during the online tracking process. Test results verified the accuracy of the proposed method to track the global maximum power point with considering the effect of partial shading condition. The proposed method was also compared with other MPPT methods to verify the superiority of the proposed work. The obtained results reveal that the proposed method is effective to improve the tracking efficiency and reduce the tracking time and the number of iterations for the different irradiances and load conditions. The maximum number of iterations was 11 iteration and the highest tracking time was 0.273s with tracking efficiency of about 99.98%.

scholarly journals Application of mutant particle swarm optimization for MPPT in photovoltaic system

2020 ◽  
Vol 19 (2) ◽  
pp. 600
Author(s):  
Thom Thi Hoang ◽  
Thi Huong Le
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Operating Efficiency ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Power Point

<span>The P –V characteristic of a photovoltaic system (PVs) is non-linear and de-pends entirely on the extreme environmental condition, thus a large amount PV energy is lost in the environment. To enhance the operating efficiency of the PVs, a maximum power point tracking (MPPT) controller is normally equipped in the system. This paper proposes a new mutant particle swarm optimization (MPSO) algorithm for tracking the maximum power point (MPP) in the PVs. The MPSO-based MPPT algorithm not only surmounts the steady-state oscillation (SSO) around the MPP, but also tracks accurately the optimum power under different varying environmental conditions. To demonstrate the effectiveness of the proposed method, MATLAB simulations are implemented in three challenging scenarios to the PV system, including changing irradiation, load variation and partial shading condition (PSC). Furthermore, the obtained results are compared to some of the con-ventional MPPT algorithms, such as incremental conductance (INC) and clas-sical particle swarm optimization (PSO) in order to show the superiority of the proposed approach in improving the efficiency of PVs. </span>

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 Accelerated Particle Swarm Optimization for Photovoltaic Maximum Power Point Tracking under Partial Shading Conditions

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 623 ◽  
Author(s):  
Muhannad Alshareef ◽  
Zhengyu Lin ◽  
Mingyao Ma ◽  
Wenping Cao
Keyword(s):  
Particle Swarm Optimization ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Accelerated Particle Swarm Optimization ◽  
Power Point

This paper presents an accelerated particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to track global maximum power point (MPP) of photovoltaic (PV) generation under partial shading conditions. Conventional PSO-based MPPT algorithms have common weaknesses of a long convergence time to reach the global MPP and oscillations during the searching. The proposed algorithm includes a standard PSO and a perturb-and-observe algorithm as the accelerator. It has been experimentally tested and compared with conventional MPPT algorithms. Experimental results show that the proposed MPPT method is effective in terms of high reliability, fast dynamic response, and high accuracy in tracking the global MPP.

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 Efficiency Improvement of Photovolataic by Using Maximum Power Point Tracking Based on Particle Swarm Optimization Algorithm Under Normal and Partial Shading

2018 ◽  
Vol 2 (2) ◽  
pp. 71
Author(s):  
Machmud Effendy ◽  
Khusnul Hidayat ◽  
Wahyu Dianto Pramana
Keyword(s):  
Particle Swarm Optimization ◽  
Maximum Power Point Tracking ◽  
Particle Swarm ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Swarm Optimization ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

Photovoltaic (PV) is a device which is capable to converts solar irradiance into Direct Current (DC) electricity energy. To increase the power result of PV, it needs a method to track the Maximum Power Point(MPP) which is usually called Maximum power Point Tracking(MPPT). So that, the power result increased with low cost. The purpose of this research is to conduct MPPT modeling by Particle Swarm Optimization (PSO). The proposed method is implemented in DC to DC converter. This research used SEPIC converter. The purpose of using SEPIC converter is in order the output of current and voltage have smallest ripple. The modelling system is conducted by using MATLAB 2016b software to find out performance of PSO and SEPIC converter. The evaluation of PSO and SEPIC converter performance has been done. The simulation result shows that the proposed system has been working very well. The PSO has good accurateness in tracking and capable to to track the power produced by PV with velocity around ±4,2 seconds when in conditions STC, ±9,2 seconds when in conditions partial shading, despite a fluctuating irradiance change. While in SEPIC converter is able to reach efficiency of ≥ 80%. 

Sign in / Sign up

Export Citation Format

Share Document