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Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique

Design guidelines for solar panels regarding the environmental parameter’s influence over the solar panel power output are limited. This study proposes an output power percentage reduction model for predicting the effect of environmental parameters (ambient temperature, wind speed, relative humidity...

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Main Authors: Attia, Osam Hassan, Adam, Nor Mariah, As'arry, Azizan, Md Rezali, Khairil Anas, Hanoon, Ammar Nasiri
Format: Article
Language:English
Published: Medwell Publications 2019
Online Access:http://psasir.upm.edu.my/id/eprint/81144/1/PSO.pdf
http://psasir.upm.edu.my/id/eprint/81144/
http://docsdrive.com/pdfs/medwelljournals/jeasci/2019/1518-1531.pdf
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spelling my.upm.eprints.811442020-09-09T07:04:22Z http://psasir.upm.edu.my/id/eprint/81144/ Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique Attia, Osam Hassan Adam, Nor Mariah As'arry, Azizan Md Rezali, Khairil Anas Hanoon, Ammar Nasiri Design guidelines for solar panels regarding the environmental parameter’s influence over the solar panel power output are limited. This study proposes an output power percentage reduction model for predicting the effect of environmental parameters (ambient temperature, wind speed, relative humidity, dust accumulation and rain amount) using Particle Swarm Optimization (PSO). The PSO technique prevents an exhaustive traditional trial-and-error procedure for obtaining the set of the unknown coefficients of the proposed model. A total of 244 databases were collected from the literature and divided into two parts. The first set which comprises 194 data sets were used to build the proposed model while 50 datasets as the second set were used in the verification process. Three performance measures, namely mean absolute, mean absolute percentage and root mean square errors were used in the proposed model to ensure the accuracy of the study. The design procedure and accuracy of the proposed model are illustrated and analyzed via. simulation tests in MATLAB Software. The results show the applicability of the PSO technique to solve the solar energy problems. This technique can be adopted as an effective tool to explore the optimal solutions for the growth of the power reduction of solar panels with the different environmental parameters and provided a design guideline for solar panel site. Medwell Publications 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/81144/1/PSO.pdf Attia, Osam Hassan and Adam, Nor Mariah and As'arry, Azizan and Md Rezali, Khairil Anas and Hanoon, Ammar Nasiri (2019) Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique. Journal of Engineering and Applied Sciences, 14 (5). pp. 1518-1531. ISSN 1816-949X http://docsdrive.com/pdfs/medwelljournals/jeasci/2019/1518-1531.pdf 10.36478/jeasci.2019.1518.1531
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Design guidelines for solar panels regarding the environmental parameter’s influence over the solar panel power output are limited. This study proposes an output power percentage reduction model for predicting the effect of environmental parameters (ambient temperature, wind speed, relative humidity, dust accumulation and rain amount) using Particle Swarm Optimization (PSO). The PSO technique prevents an exhaustive traditional trial-and-error procedure for obtaining the set of the unknown coefficients of the proposed model. A total of 244 databases were collected from the literature and divided into two parts. The first set which comprises 194 data sets were used to build the proposed model while 50 datasets as the second set were used in the verification process. Three performance measures, namely mean absolute, mean absolute percentage and root mean square errors were used in the proposed model to ensure the accuracy of the study. The design procedure and accuracy of the proposed model are illustrated and analyzed via. simulation tests in MATLAB Software. The results show the applicability of the PSO technique to solve the solar energy problems. This technique can be adopted as an effective tool to explore the optimal solutions for the growth of the power reduction of solar panels with the different environmental parameters and provided a design guideline for solar panel site.
format Article
author Attia, Osam Hassan
Adam, Nor Mariah
As'arry, Azizan
Md Rezali, Khairil Anas
Hanoon, Ammar Nasiri
spellingShingle Attia, Osam Hassan
Adam, Nor Mariah
As'arry, Azizan
Md Rezali, Khairil Anas
Hanoon, Ammar Nasiri
Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique
author_facet Attia, Osam Hassan
Adam, Nor Mariah
As'arry, Azizan
Md Rezali, Khairil Anas
Hanoon, Ammar Nasiri
author_sort Attia, Osam Hassan
title Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique
title_short Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique
title_full Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique
title_fullStr Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique
title_full_unstemmed Development of a prediction model for output power reduction of PV solar panels based on environmental parameters using particle swarm optimization technique
title_sort development of a prediction model for output power reduction of pv solar panels based on environmental parameters using particle swarm optimization technique
publisher Medwell Publications
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/81144/1/PSO.pdf
http://psasir.upm.edu.my/id/eprint/81144/
http://docsdrive.com/pdfs/medwelljournals/jeasci/2019/1518-1531.pdf
_version_ 1677783009775845376
score 13.211869

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