Design and experimental validation of an IoT data-logger device for indirect measurement of solar irradiance based on a correlation model

K. Alarcon-Maza, V. Herrera-Perez, J. Rodriguez-Flores, M. Pacheco-Cunduri, J. Hernandez-Ambato

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

Abstract

The present work aimed to develop an autonomous instrument for indirectly measuring solar irradiance from silicon sensors. Through laboratory tests, using a precision digital solar power meter device (SM206-SOLAR), with an error range of ±10% per reading and ±0.38% W/m2 per °C, and photovoltaic trainer equipment (Lucas Nulle), a statistical correlation model was developed between the short-circuit current of the NPA5S-12H solar module and the measured artificial irradiance. A significant linear correlation was determined with a mean absolute percentage error (MAPE) of 6.97%, an average root-mean-square error (RMSE) of ±26 W/m2 per °C and a relative percentage root mean square error (rRMSE) of 10.76%. For real-time data collection purposes, a data-logger device with wireless communication functions based on a Wi-Fi link and IoT MQTT protocol was developed. Finally, a SQL server and web application were configured on a public Linux server to collect and present data in real-time.

Original languageEnglish
Title of host publication2023 IEEE Green Technologies Conference, GreenTech 2023
PublisherIEEE Computer Society
Pages40-45
Number of pages6
ISBN (Electronic)9781665492874
DOIs
StatePublished - 2023
Event15th Annual IEEE Green Technologies Conference, GreenTech 2023 - Denver, United States
Duration: 19 Apr 202321 Apr 2023

Publication series

Name2023 IEEE Green Technologies Conference (GreenTech)

Conference

Conference15th Annual IEEE Green Technologies Conference, GreenTech 2023
Country/TerritoryUnited States
CityDenver
Period19/04/2321/04/23

Keywords

  • PV data-logger
  • correlational model
  • solar cells
  • solar irradiance estimation

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