TY - GEN
T1 - Design and experimental validation of an IoT data-logger device for indirect measurement of solar irradiance based on a correlation model
AU - Alarcon-Maza, K.
AU - Herrera-Perez, V.
AU - Rodriguez-Flores, J.
AU - Pacheco-Cunduri, M.
AU - Hernandez-Ambato, J.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - PV data-logger
KW - correlational model
KW - solar cells
KW - solar irradiance estimation
UR - http://www.scopus.com/inward/record.url?scp=85166202759&partnerID=8YFLogxK
U2 - 10.1109/GreenTech56823.2023.10173825
DO - 10.1109/GreenTech56823.2023.10173825
M3 - Contribución a la conferencia
AN - SCOPUS:85166202759
T3 - 2023 IEEE Green Technologies Conference (GreenTech)
SP - 40
EP - 45
BT - 2023 IEEE Green Technologies Conference, GreenTech 2023
PB - IEEE Computer Society
T2 - 15th Annual IEEE Green Technologies Conference, GreenTech 2023
Y2 - 19 April 2023 through 21 April 2023
ER -
