Genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation

Photovoltaic (PV) arrays which are the main part of PV generators consist of PV modules and PV modules are composed of PV cells. Such a modular nature is a blessing when it provides flexibility in system sizing but is a curse when it combines with inequality of PV modules and causes the so-called m...

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Main Author: Kohneh, Samad Shirzadi Deh
Format: Thesis
Language:English
Published: 2015
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Online Access:http://psasir.upm.edu.my/id/eprint/57537/1/FK%202015%2054RR.pdf
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spelling my-upm-ir.575372017-10-10T04:47:54Z Genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation 2015-05 Kohneh, Samad Shirzadi Deh Photovoltaic (PV) arrays which are the main part of PV generators consist of PV modules and PV modules are composed of PV cells. Such a modular nature is a blessing when it provides flexibility in system sizing but is a curse when it combines with inequality of PV modules and causes the so-called mismatch power loss. Recent investigations have reported this type of mismatch losses from 1% to 10%. The conventional techniques to minimize mismatch losses are distributed maximum power point tracking (MPPT), array reconfiguration and module sorting technique. Module sorting techniques which sort modules in arrays by one characteristic parameter are superior among all conventional solutions. This study proposes a new method for arranging modules in arrays using a genetic algorithm (GA) to find the arrangement with lowest mismatch losses and highest output power. Some data sets of modules are generated through a stochastic process and organized in different arrays. These data sets are used to carry out several simulations in MATLAB. These simulations cover calculation of mismatch losses at standard test circumstance (STC) and also energy yield under the GA based arrangement as well as the sorting techniques. Results prove that the proposed arrangement of modules in arrays reduces mismatch losses and subsequently improves the energy yield more effectively than what conventional sorting techniques do. The GA based arrangement is also validated with other data sets of modules that are collected from 3 practical arrays. Results of participation of these practical data sets also support the superiority of the GA based arrangement over Morting techniques. Comparison between best sorting technique and the GA based arrangement turned out that the GA based arrangement recovers daily energy ranging from 50 Wh to 320 Wh and monthly energy ranging from 1010 Wh to 6240 Wh depending on the array size. Similar comparison for the practical arrays shows an annual recoverable energy ranging from 6.35 kWh to 11.8 kWh and up to 278 kWh for an array with defective modules. Photovoltaic power generation Electrical engineering 2015-05 Thesis http://psasir.upm.edu.my/id/eprint/57537/ http://psasir.upm.edu.my/id/eprint/57537/1/FK%202015%2054RR.pdf application/pdf en public masters Universiti Putra Malaysia Photovoltaic power generation Electrical engineering
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
topic Photovoltaic power generation
Electrical engineering

spellingShingle Photovoltaic power generation
Electrical engineering

Kohneh, Samad Shirzadi Deh
Genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation
description Photovoltaic (PV) arrays which are the main part of PV generators consist of PV modules and PV modules are composed of PV cells. Such a modular nature is a blessing when it provides flexibility in system sizing but is a curse when it combines with inequality of PV modules and causes the so-called mismatch power loss. Recent investigations have reported this type of mismatch losses from 1% to 10%. The conventional techniques to minimize mismatch losses are distributed maximum power point tracking (MPPT), array reconfiguration and module sorting technique. Module sorting techniques which sort modules in arrays by one characteristic parameter are superior among all conventional solutions. This study proposes a new method for arranging modules in arrays using a genetic algorithm (GA) to find the arrangement with lowest mismatch losses and highest output power. Some data sets of modules are generated through a stochastic process and organized in different arrays. These data sets are used to carry out several simulations in MATLAB. These simulations cover calculation of mismatch losses at standard test circumstance (STC) and also energy yield under the GA based arrangement as well as the sorting techniques. Results prove that the proposed arrangement of modules in arrays reduces mismatch losses and subsequently improves the energy yield more effectively than what conventional sorting techniques do. The GA based arrangement is also validated with other data sets of modules that are collected from 3 practical arrays. Results of participation of these practical data sets also support the superiority of the GA based arrangement over Morting techniques. Comparison between best sorting technique and the GA based arrangement turned out that the GA based arrangement recovers daily energy ranging from 50 Wh to 320 Wh and monthly energy ranging from 1010 Wh to 6240 Wh depending on the array size. Similar comparison for the practical arrays shows an annual recoverable energy ranging from 6.35 kWh to 11.8 kWh and up to 278 kWh for an array with defective modules.
format Thesis
qualification_level Master's degree
author Kohneh, Samad Shirzadi Deh
author_facet Kohneh, Samad Shirzadi Deh
author_sort Kohneh, Samad Shirzadi Deh
title Genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation
title_short Genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation
title_full Genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation
title_fullStr Genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation
title_full_unstemmed Genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation
title_sort genetic algorithm-based arrangement of photovoltaic modules in arrays for mismatch loss mitigation
granting_institution Universiti Putra Malaysia
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/57537/1/FK%202015%2054RR.pdf
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