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

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

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.

Idioma originalInglés
Título de la publicación alojada2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665434270
DOI
EstadoPublicada - 2021
Evento23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021 - Virtual, Ixtapa, México
Duración: 10 nov 202112 nov 2021

Serie de la publicación

Nombre2021 23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021

Conferencia

Conferencia23rd IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2021
País/TerritorioMéxico
CiudadVirtual, Ixtapa
Período10/11/2112/11/21

Nota bibliográfica

Publisher Copyright:
© 2021 IEEE.

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