Intelligent predictive model of electrical power in photovoltaic systems through solar radiation and temperature on site

Luis Omar Lara Cerecedo, Nun Pitalua-Diaz, Jesus Fernando Hinojosa Palafox, Juan Anzurez Marin, Salvador Ramirez Zavala

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

Abstract

A Neuro-fuzzy ANFIS model is presented that allows predicting the generation of electrical power in a photovoltaic system considering the solar radiation and environmental temperature of the geographical area. This model enables fuzzy modeling to learn from the data set and, as a result, compute the most appropriate membership function parameters. It also makes use of neural networks' abilities to classify data and find patterns. The algorithm is developed using MATLAB® software and is trained with the acquired data weather station located in Hermosillo, Sonora City, and the electrical power output of the system at the site. The algorithm is evaluated using rigorous evaluation factors which shows how much the predicted value differs from the actual value, resulting in the following predicted values: RSME: 295.2686, NRMSE: 0.09496, RMSPE: 9.4306, MAE: 218.6996, and MAPE: 6.985, respectively.

Original languageEnglish
Title of host publication2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665434270
DOIs
StatePublished - 2021
Event23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021 - Virtual, Ixtapa, Mexico
Duration: 10 Nov 202112 Nov 2021

Publication series

Name2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021

Conference

Conference23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
Country/TerritoryMexico
CityVirtual, Ixtapa
Period10/11/2112/11/21

Bibliographical note

Funding Information:
Thanks to the University of Sonora for the facilities in the study of the photovoltaic system, as well to the support from CONACYT, Mexico, through graduate scholarship.

Publisher Copyright:
© 2021 IEEE.

Keywords

  • Estimation error
  • Fuzzy neural networks
  • Hybrid intelligent systems
  • Photovoltaic systems
  • Prediction algorithms
  • Solar power generation

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