Modeling of photovoltaic array using random forests technique

Ibrahim A. Ibrahim, Azah Mohamed, Tamer Khatib

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

7 Citations (Scopus)


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 languageEnglish
Title of host publication2015 IEEE Conference on Energy Conversion (CENCON)
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
ISBN (Electronic)9781479985982, 9781479985975
Publication statusPublished - 2015
Externally publishedYes
Event2015 IEEE Conference on Energy Conversion - Berjaya Waterfront Hotel, Johor Bahru, Malaysia
Duration: 19 Oct 201520 Oct 2015
Conference number: CFP15CEO-ART


Conference2015 IEEE Conference on Energy Conversion
Abbreviated titleCENCON 2015
CityJohor Bahru
Internet address


  • modeling of PV systems
  • random forests
  • performance evaluation


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