Modeling of photovoltaic array using random forests technique

Ibrahim A. Ibrahim; Azah Mohamed; Tamer Khatib

doi:10.1109/CENCON.2015.7409575

Modeling of photovoltaic array using random forests technique

Ibrahim A. Ibrahim, Azah Mohamed, Tamer Khatib

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

7 Citations (Scopus)

Abstract

This paper presents a novel technique for modeling of photovoltaic (PV) array using random forests (RFs). Metrological variables such as solar radiation and ambient temperature as well as actual output current of a 3 kWp PV grid-connected system installed at Universiti Kebangsaan Malaysia have been utilized. These data are used to train and validate the proposed RFs model. Three statistical error values, namely, root mean square error (RMSE), mean bias error (MBE), and mean absolute percentage error (MAPE), are used to evaluate the developed model. The results show that the proposed RFs model accurately predicts the output current of the PV system. The RMSE, MAPE, and MBE values of the RFs model are 2.7482%, 8.7151%, and -2.5772%, respectively.

Original language	English
Title of host publication	2015 IEEE Conference on Energy Conversion (CENCON)
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	390-393
Number of pages	4
ISBN (Electronic)	9781479985982, 9781479985975
DOIs	https://doi.org/10.1109/CENCON.2015.7409575
Publication status	Published - 2015
Externally published	Yes
Event	2015 IEEE Conference on Energy Conversion - Berjaya Waterfront Hotel, Johor Bahru, Malaysia Duration: 19 Oct 2015 → 20 Oct 2015 Conference number: CFP15CEO-ART https://ieeemy.org/mysection/?p=2154

Conference

Conference	2015 IEEE Conference on Energy Conversion
Abbreviated title	CENCON 2015
Country/Territory	Malaysia
City	Johor Bahru
Period	19/10/15 → 20/10/15
Internet address	https://ieeemy.org/mysection/?p=2154

Keywords

modeling of PV systems
random forests
performance evaluation

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10.1109/CENCON.2015.7409575

Cite this

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title = "Modeling of photovoltaic array using random forests technique",

abstract = "This paper presents a novel technique for modeling of photovoltaic (PV) array using random forests (RFs). Metrological variables such as solar radiation and ambient temperature as well as actual output current of a 3 kWp PV grid-connected system installed at Universiti Kebangsaan Malaysia have been utilized. These data are used to train and validate the proposed RFs model. Three statistical error values, namely, root mean square error (RMSE), mean bias error (MBE), and mean absolute percentage error (MAPE), are used to evaluate the developed model. The results show that the proposed RFs model accurately predicts the output current of the PV system. The RMSE, MAPE, and MBE values of the RFs model are 2.7482%, 8.7151%, and -2.5772%, respectively.",

keywords = "modeling of PV systems, random forests, performance evaluation",

author = "Ibrahim, {Ibrahim A.} and Azah Mohamed and Tamer Khatib",

year = "2015",

doi = "10.1109/CENCON.2015.7409575",

language = "English",

pages = "390--393",

booktitle = "2015 IEEE Conference on Energy Conversion (CENCON)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2015 IEEE Conference on Energy Conversion, CENCON 2015 ; Conference date: 19-10-2015 Through 20-10-2015",

url = "https://ieeemy.org/mysection/?p=2154",

}

Modeling of photovoltaic array using random forests technique. / Ibrahim, Ibrahim A.; Mohamed, Azah; Khatib, Tamer.
2015 IEEE Conference on Energy Conversion (CENCON). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 390-393.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Modeling of photovoltaic array using random forests technique

AU - Ibrahim, Ibrahim A.

AU - Mohamed, Azah

AU - Khatib, Tamer

N1 - Conference code: CFP15CEO-ART

PY - 2015

Y1 - 2015

N2 - This paper presents a novel technique for modeling of photovoltaic (PV) array using random forests (RFs). Metrological variables such as solar radiation and ambient temperature as well as actual output current of a 3 kWp PV grid-connected system installed at Universiti Kebangsaan Malaysia have been utilized. These data are used to train and validate the proposed RFs model. Three statistical error values, namely, root mean square error (RMSE), mean bias error (MBE), and mean absolute percentage error (MAPE), are used to evaluate the developed model. The results show that the proposed RFs model accurately predicts the output current of the PV system. The RMSE, MAPE, and MBE values of the RFs model are 2.7482%, 8.7151%, and -2.5772%, respectively.

AB - This paper presents a novel technique for modeling of photovoltaic (PV) array using random forests (RFs). Metrological variables such as solar radiation and ambient temperature as well as actual output current of a 3 kWp PV grid-connected system installed at Universiti Kebangsaan Malaysia have been utilized. These data are used to train and validate the proposed RFs model. Three statistical error values, namely, root mean square error (RMSE), mean bias error (MBE), and mean absolute percentage error (MAPE), are used to evaluate the developed model. The results show that the proposed RFs model accurately predicts the output current of the PV system. The RMSE, MAPE, and MBE values of the RFs model are 2.7482%, 8.7151%, and -2.5772%, respectively.

KW - modeling of PV systems

KW - random forests

KW - performance evaluation

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U2 - 10.1109/CENCON.2015.7409575

DO - 10.1109/CENCON.2015.7409575

M3 - Conference proceeding contribution

SP - 390

EP - 393

BT - 2015 IEEE Conference on Energy Conversion (CENCON)

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - 2015 IEEE Conference on Energy Conversion

Y2 - 19 October 2015 through 20 October 2015

ER -

Modeling of photovoltaic array using random forests technique

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Keywords

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