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Forecasting and analysis of solar power output from integrated solar energy and IoT system

Solar-powered irrigation systems has attracted enormous attention considering because it is a green energy source and cost-effective green energy and power supply source for plantations and farms, especially those located in rural areas. Solar power generation systems may experience either insuffici...

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Main Authors: Hasyiya Karimah, Adli, Ku Azmie, Husin, Nurul Hasya, Mohd Hanafiah, Muhammad Akmal, Remli, Ernawan, Ferda, Wirawan, Panji Wisnu
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://umpir.ump.edu.my/id/eprint/42365/1/Forecasting%20and%20analysis%20of%20solar%20power%20output%20from%20integrated.pdf
http://umpir.ump.edu.my/id/eprint/42365/2/Forecasting%20and%20analysis%20of%20solar%20power%20output%20from%20integrated%20solar%20energy%20and%20IoT%20system_ABS.pdf
http://umpir.ump.edu.my/id/eprint/42365/
https://doi.org/10.1109/ICICoS53627.2021.9651831
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spelling my.ump.umpir.423652024-10-30T04:35:29Z http://umpir.ump.edu.my/id/eprint/42365/ Forecasting and analysis of solar power output from integrated solar energy and IoT system Hasyiya Karimah, Adli Ku Azmie, Husin Nurul Hasya, Mohd Hanafiah Muhammad Akmal, Remli Ernawan, Ferda Wirawan, Panji Wisnu QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Solar-powered irrigation systems has attracted enormous attention considering because it is a green energy source and cost-effective green energy and power supply source for plantations and farms, especially those located in rural areas. Solar power generation systems may experience either insufficient voltage or overvoltage of solar power generation usually occurs especially for the based on the specific country that has specific climate of the installation spot. East coast states of Malaysia face northeast monsoon every year and during this season, the outputs from solar power generation systems will fluctuate greatly that the solar power distribution throughout the year was never reported elsewhere. Thus, in this study, auto-tracking solar panel was installed in a mini farm equipped with Internet-of- Thing (IoT) system for 24/7 data monitoring. From the results, the highest amount of energy generated was found from between 12 pm until 2 pm with approximately 45.9% efficiency. Then, ARIMA (11, 2, 4) model was applied using Python tool to forecast the energy generation data obtained. This forecast found the Mean Absolute Percentage Error (MAPE) of around 32.0%, which of Mean Absolute Percentage Error (MAPE) implies that the prediction was is about 68.0% validity with Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MASE) figures of recorded with 1.70 and 0.32, respectively. Forecasting the output is important to ensure the availability of existing and back-up of electricity supply, besides to avoid over and underutilization of electricity. Institute of Electrical and Electronics Engineers Inc. 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42365/1/Forecasting%20and%20analysis%20of%20solar%20power%20output%20from%20integrated.pdf pdf en http://umpir.ump.edu.my/id/eprint/42365/2/Forecasting%20and%20analysis%20of%20solar%20power%20output%20from%20integrated%20solar%20energy%20and%20IoT%20system_ABS.pdf Hasyiya Karimah, Adli and Ku Azmie, Husin and Nurul Hasya, Mohd Hanafiah and Muhammad Akmal, Remli and Ernawan, Ferda and Wirawan, Panji Wisnu (2021) Forecasting and analysis of solar power output from integrated solar energy and IoT system. In: Proceedings - International Conference on Informatics and Computational Sciences. 5th International Conference on Informatics and Computational Sciences, ICICos 2021 , 24 - 25 November 2021 , Semarang. pp. 222-226., 2021-November. ISSN 2767-7087 ISBN 978-166543807-0 (Published) https://doi.org/10.1109/ICICoS53627.2021.9651831
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Hasyiya Karimah, Adli
Ku Azmie, Husin
Nurul Hasya, Mohd Hanafiah
Muhammad Akmal, Remli
Ernawan, Ferda
Wirawan, Panji Wisnu
Forecasting and analysis of solar power output from integrated solar energy and IoT system
description Solar-powered irrigation systems has attracted enormous attention considering because it is a green energy source and cost-effective green energy and power supply source for plantations and farms, especially those located in rural areas. Solar power generation systems may experience either insufficient voltage or overvoltage of solar power generation usually occurs especially for the based on the specific country that has specific climate of the installation spot. East coast states of Malaysia face northeast monsoon every year and during this season, the outputs from solar power generation systems will fluctuate greatly that the solar power distribution throughout the year was never reported elsewhere. Thus, in this study, auto-tracking solar panel was installed in a mini farm equipped with Internet-of- Thing (IoT) system for 24/7 data monitoring. From the results, the highest amount of energy generated was found from between 12 pm until 2 pm with approximately 45.9% efficiency. Then, ARIMA (11, 2, 4) model was applied using Python tool to forecast the energy generation data obtained. This forecast found the Mean Absolute Percentage Error (MAPE) of around 32.0%, which of Mean Absolute Percentage Error (MAPE) implies that the prediction was is about 68.0% validity with Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MASE) figures of recorded with 1.70 and 0.32, respectively. Forecasting the output is important to ensure the availability of existing and back-up of electricity supply, besides to avoid over and underutilization of electricity.
format Conference or Workshop Item
author Hasyiya Karimah, Adli
Ku Azmie, Husin
Nurul Hasya, Mohd Hanafiah
Muhammad Akmal, Remli
Ernawan, Ferda
Wirawan, Panji Wisnu
author_facet Hasyiya Karimah, Adli
Ku Azmie, Husin
Nurul Hasya, Mohd Hanafiah
Muhammad Akmal, Remli
Ernawan, Ferda
Wirawan, Panji Wisnu
author_sort Hasyiya Karimah, Adli
title Forecasting and analysis of solar power output from integrated solar energy and IoT system
title_short Forecasting and analysis of solar power output from integrated solar energy and IoT system
title_full Forecasting and analysis of solar power output from integrated solar energy and IoT system
title_fullStr Forecasting and analysis of solar power output from integrated solar energy and IoT system
title_full_unstemmed Forecasting and analysis of solar power output from integrated solar energy and IoT system
title_sort forecasting and analysis of solar power output from integrated solar energy and iot system
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2021
url http://umpir.ump.edu.my/id/eprint/42365/1/Forecasting%20and%20analysis%20of%20solar%20power%20output%20from%20integrated.pdf
http://umpir.ump.edu.my/id/eprint/42365/2/Forecasting%20and%20analysis%20of%20solar%20power%20output%20from%20integrated%20solar%20energy%20and%20IoT%20system_ABS.pdf
http://umpir.ump.edu.my/id/eprint/42365/
https://doi.org/10.1109/ICICoS53627.2021.9651831
_version_ 1822924724821295104
score 13.235318

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