Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM

PV solar is the conversion of light into electricity using semiconducting materials. Currently, there are two types of PV module that install at the rooftop FKE which are mono and thin film and this PV system has already been operating for seven years. Performance ratio for that PV systems is the ra...

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Main Author:	Johari, Nurhanani
Format:	Thesis
Language:	English English
Published:	2020
Subjects:	T Technology (General)
Online Access:	http://eprints.utem.edu.my/id/eprint/25565/1/Quantitative%20Evaluation%20of%20Output%20Power%20Degradation%20Rate%20for%20PV%20System%20in%20FKE%20UTeM.pdf http://eprints.utem.edu.my/id/eprint/25565/2/Quantitative%20Evaluation%20of%20Output%20Power%20Degradation%20Rate%20for%20PV%20System%20in%20FKE%20UTeM.pdf
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spelling	my-utem-ep.255652022-01-06T12:57:54Z Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM 2020 Johari, Nurhanani T Technology (General) TK Electrical engineering. Electronics Nuclear engineering PV solar is the conversion of light into electricity using semiconducting materials. Currently, there are two types of PV module that install at the rooftop FKE which are mono and thin film and this PV system has already been operating for seven years. Performance ratio for that PV systems is the rating between the actual data power output from PV solar divide by theoretical calculation power output. There are three method that are used to predict the future performance ratio which are Linear Regression (LR), Auto Regressive Integrated Moving Average (ARIMA) and Support Vector Machine (SVM). The lowest RMSE from the performance ratio in 2016 is selected and is compared with the actual data of PV output in year 2019. Result from the simulation show that ARIMA method is suitable for Mono system while SVM is suitable for Thin-film. Lastly, linear equation is obtained from the prediction data in 2016 and 2019 to be used in determining the future value of performance ratio. 2020 Thesis http://eprints.utem.edu.my/id/eprint/25565/ http://eprints.utem.edu.my/id/eprint/25565/1/Quantitative%20Evaluation%20of%20Output%20Power%20Degradation%20Rate%20for%20PV%20System%20in%20FKE%20UTeM.pdf text en public http://eprints.utem.edu.my/id/eprint/25565/2/Quantitative%20Evaluation%20of%20Output%20Power%20Degradation%20Rate%20for%20PV%20System%20in%20FKE%20UTeM.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=117867 mphil masters Universiti Teknikal Malaysia Melaka Faculty Of Mechanical Engineering Baharin, Kyairul Azmi 1. H. K. Lim, M. F. Sepikit, and M. Maskum, “Photo voltaic Solar Energy Technology Overview for Malaysia Scenario ” pp. 300–305, 2003. 2. N. H. Zaini, M. Z. A. Kadir, M. Izadi, N. I. Ahmad, M. A. M. Radzi, and N. Azis, “The Effect of Temperature on a Mono-crystalline Solar PV Panel,” pp. 249–253, 2015. 3. K. Rahimi, V. Tech, U. N. C. Charlotte, and N. Carolina, “Effects of Photovoltaic Systems on Power Quality,” pp. 1–6, 2016. 4. C. Science, B. Dubey, and D. Tiwari, “Effect of temperature variations over photovoltaic modules efficiency of different technologies at,” 2016. 5. H. A. Kazem, “Effect of Humidity on Photovoltaic Performance Based on Experimental Study,” no. December 2015, 2016. 6. H. A. Kazem et al., “Effect of Humidity on the PV Performance in Oman,” no. July 2016, pp. 1–5, 2012. 7. P. Stephen and P. G. Scholar, “Linear Regression For Pattern Recognition.” 8. S. P. Menon, “Prediction of Temperature using Linear Regression,” 2017. 9. S. Atique, S. Noureen, V. Roy, and S. Bayne, “Forecasting of total daily solar energy generation using ARIMA : A case study,” no. January, 2019. 10. L. W. Chong, R. W. Ng, Y. W. Wong, and R. K. Rajkumar, “One-Hour Ahead Prediction of Solar Irradiance Using Support Vector Machines,” 2018 Int. Electr. Eng. Congr., pp. 1–4, 2018. 11. K. Y. Bae, H. S. Jang, and S. Member, “Hourly Solar Irradiance Prediction Based on Support Vector Machine and Its Error Analysis,” vol. 8950, no. c, pp. 1–11, 2016. 12. W. Math, “Linear Regression.” [Online]. Available: https://www.mathworks.com/help/matlab/data_analysis/linear-regression.html. [Accessed: 17-Jan-2020]. 13. W. Math, “Understanding Support Vector Machine Regression.” [Online]. Available: https://www.mathworks.com/help/stats/understanding-support-vector-machineregression.html. [Accessed: 17-Jan-2020]
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Baharin, Kyairul Azmi
topic	T Technology (General) T Technology (General)
spellingShingle	T Technology (General) T Technology (General) Johari, Nurhanani Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM
description	PV solar is the conversion of light into electricity using semiconducting materials. Currently, there are two types of PV module that install at the rooftop FKE which are mono and thin film and this PV system has already been operating for seven years. Performance ratio for that PV systems is the rating between the actual data power output from PV solar divide by theoretical calculation power output. There are three method that are used to predict the future performance ratio which are Linear Regression (LR), Auto Regressive Integrated Moving Average (ARIMA) and Support Vector Machine (SVM). The lowest RMSE from the performance ratio in 2016 is selected and is compared with the actual data of PV output in year 2019. Result from the simulation show that ARIMA method is suitable for Mono system while SVM is suitable for Thin-film. Lastly, linear equation is obtained from the prediction data in 2016 and 2019 to be used in determining the future value of performance ratio.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Johari, Nurhanani
author_facet	Johari, Nurhanani
author_sort	Johari, Nurhanani
title	Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM
title_short	Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM
title_full	Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM
title_fullStr	Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM
title_full_unstemmed	Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM
title_sort	quantitative evaluation of output power degradation rate for pv system in fke utem
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty Of Mechanical Engineering
publishDate	2020
url	http://eprints.utem.edu.my/id/eprint/25565/1/Quantitative%20Evaluation%20of%20Output%20Power%20Degradation%20Rate%20for%20PV%20System%20in%20FKE%20UTeM.pdf http://eprints.utem.edu.my/id/eprint/25565/2/Quantitative%20Evaluation%20of%20Output%20Power%20Degradation%20Rate%20for%20PV%20System%20in%20FKE%20UTeM.pdf
_version_	1747834140274720768

Quantitative Evaluation of Output Power Degradation Rate for PV System in FKE UTeM

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