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

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 deman...

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Main Authors: Muhammad Hamza Zafar, Thamraa Al-shahrani, Noman Mujeeb Khan, Adeel Feroz Mirza, Majad Mansoor, Muhammad Usman Qadir, Muhammad Imran Khan, Rizwan Ali Naqvi
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/9/11/1962
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spelling doaj-6d8dc89de5a249f9b59db5c1996344732020-11-25T04:01:32ZengMDPI AGElectronics2079-92922020-11-0191962196210.3390/electronics9111962Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial ShadingMuhammad Hamza Zafar0Thamraa Al-shahrani1Noman Mujeeb Khan2Adeel Feroz Mirza3Majad Mansoor4Muhammad Usman Qadir5Muhammad Imran Khan6Rizwan Ali Naqvi7Department of Electrical, Capital University of Science and Technology, Islamabad 44000, PakistanDepartment of Physics, College of Science, Princess Nourah Bint Abdulrahman University, Riyadh 11671, Saudi ArabiaDepartment of Electrical, Capital University of Science and Technology, Islamabad 44000, PakistanDepartment of Automation, University of Science and Technology of China, Hefei 230027, ChinaDepartment of Automation, University of Science and Technology of China, Hefei 230027, ChinaDepartment of Electrical, University of Lahore, Islamabad Campus, Islamabad 46000, PakistanHefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei 230027, ChinaDepartment of Unmanned Vehicle Engineering, Sejong University, Seoul 05006, KoreaThe 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.https://www.mdpi.com/2079-9292/9/11/1962group teaching optimization algorithm (GTOA)maximum power point tracking (MPP)global maxima (GM)complex partial shading (CPS)
collection DOAJ
language English
format Article
sources DOAJ
author Muhammad Hamza Zafar
Thamraa Al-shahrani
Noman Mujeeb Khan
Adeel Feroz Mirza
Majad Mansoor
Muhammad Usman Qadir
Muhammad Imran Khan
Rizwan Ali Naqvi
spellingShingle Muhammad Hamza Zafar
Thamraa Al-shahrani
Noman Mujeeb Khan
Adeel Feroz Mirza
Majad Mansoor
Muhammad Usman Qadir
Muhammad Imran Khan
Rizwan Ali Naqvi
Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading
Electronics
group teaching optimization algorithm (GTOA)
maximum power point tracking (MPP)
global maxima (GM)
complex partial shading (CPS)
author_facet Muhammad Hamza Zafar
Thamraa Al-shahrani
Noman Mujeeb Khan
Adeel Feroz Mirza
Majad Mansoor
Muhammad Usman Qadir
Muhammad Imran Khan
Rizwan Ali Naqvi
author_sort Muhammad Hamza Zafar
title Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading
title_short Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading
title_full Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading
title_fullStr Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading
title_full_unstemmed Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading
title_sort group teaching optimization algorithm based mppt control of pv systems under partial shading and complex partial shading
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2020-11-01
description 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.
topic group teaching optimization algorithm (GTOA)
maximum power point tracking (MPP)
global maxima (GM)
complex partial shading (CPS)
url https://www.mdpi.com/2079-9292/9/11/1962
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