A simulation of multiple peaks maximum power point tracking for photovoltaic system

Recent decades, renewable energy applications have shown significant increase due to the awareness from people regarding the negative impacts of fossil fuel burning to the environment. The availability of renewable energy source also has contributed to the increase in renewable energy applications....

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Main Author: Kamarzaman, Nur Atharah
Format: Thesis
Published: 2013
Subjects:
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author Kamarzaman, Nur Atharah
author_facet Kamarzaman, Nur Atharah
author_sort Kamarzaman, Nur Atharah
collection ePrints
description Recent decades, renewable energy applications have shown significant increase due to the awareness from people regarding the negative impacts of fossil fuel burning to the environment. The availability of renewable energy source also has contributed to the increase in renewable energy applications. Among the renewable energy sources available, photovoltaic (PV) is considered to be one of the best. This is mainly because it provides clean energy silently. However, there are some limitations to PV applications. Considering that it has a high initial cost to set up and it has very low conversion efficiency, it is vital to ensure that a PV system can operate at Maximum Power Point (MPP). Maximum Power Point Tracking (MPPT) controller such as Perturb and Observation (P&O), Incremental Conductance (Inc. Cond), and Hill Climbing (HC) are widely used due to simple implementation and shows a good performance in tracking MPP when solar irradiance is uniform. However, when partial shading occurs on the PV array, tracking to MPP becomes complicated as multiple peaks exist on the Power-Voltage (P-V) characteristic curve. Conventional methods cannot distinguish between local peaks and global peak, thus failed to track the true MPP. Several methods based on stochastic algorithm and artificial intelligence has been developed to track MPP under partial shading conditions. This project focuses on the performance of MPPT controller to extract maximum power from PV system under partial shading condition. The selected MPPT algorithms that have been implemented in the PV system includes Fuzzy Logic Controller and Particle Swarm Optimization. Results show that both the simulated MPPT controllers are capable of tracking the maximum power up to 90% of its efficiency.
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spelling utm.eprints-420562017-07-09T03:25:21Z http://eprints.utm.my/42056/ A simulation of multiple peaks maximum power point tracking for photovoltaic system Kamarzaman, Nur Atharah TK Electrical engineering. Electronics Nuclear engineering Recent decades, renewable energy applications have shown significant increase due to the awareness from people regarding the negative impacts of fossil fuel burning to the environment. The availability of renewable energy source also has contributed to the increase in renewable energy applications. Among the renewable energy sources available, photovoltaic (PV) is considered to be one of the best. This is mainly because it provides clean energy silently. However, there are some limitations to PV applications. Considering that it has a high initial cost to set up and it has very low conversion efficiency, it is vital to ensure that a PV system can operate at Maximum Power Point (MPP). Maximum Power Point Tracking (MPPT) controller such as Perturb and Observation (P&O), Incremental Conductance (Inc. Cond), and Hill Climbing (HC) are widely used due to simple implementation and shows a good performance in tracking MPP when solar irradiance is uniform. However, when partial shading occurs on the PV array, tracking to MPP becomes complicated as multiple peaks exist on the Power-Voltage (P-V) characteristic curve. Conventional methods cannot distinguish between local peaks and global peak, thus failed to track the true MPP. Several methods based on stochastic algorithm and artificial intelligence has been developed to track MPP under partial shading conditions. This project focuses on the performance of MPPT controller to extract maximum power from PV system under partial shading condition. The selected MPPT algorithms that have been implemented in the PV system includes Fuzzy Logic Controller and Particle Swarm Optimization. Results show that both the simulated MPPT controllers are capable of tracking the maximum power up to 90% of its efficiency. 2013 Thesis NonPeerReviewed Kamarzaman, Nur Atharah (2013) A simulation of multiple peaks maximum power point tracking for photovoltaic system. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:77695?queryType=vitalDismax&query=A+simulation+of+multiple+peaks+maximum+power+point+tracking
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Kamarzaman, Nur Atharah
A simulation of multiple peaks maximum power point tracking for photovoltaic system
title A simulation of multiple peaks maximum power point tracking for photovoltaic system
title_full A simulation of multiple peaks maximum power point tracking for photovoltaic system
title_fullStr A simulation of multiple peaks maximum power point tracking for photovoltaic system
title_full_unstemmed A simulation of multiple peaks maximum power point tracking for photovoltaic system
title_short A simulation of multiple peaks maximum power point tracking for photovoltaic system
title_sort simulation of multiple peaks maximum power point tracking for photovoltaic system
topic TK Electrical engineering. Electronics Nuclear engineering
work_keys_str_mv AT kamarzamannuratharah asimulationofmultiplepeaksmaximumpowerpointtrackingforphotovoltaicsystem
AT kamarzamannuratharah simulationofmultiplepeaksmaximumpowerpointtrackingforphotovoltaicsystem