Solar IoT: Monitoring the Orientation and Electrical Parameters of the Solar Panel

In recent years, the use of solar energy from renewable energy sources has been increasing. Solar energy can be used directly for electricity and heat generation, as well as for small-scale use in smart cities such as traffic lights, city lighting, vehicle charging stations. The Internet of Things enables remote monitoring and control of solar energy systems, diagnosis of faults that may occur in the system and increasing system efficiency. The energy production of the system can be monitored depending on the time of day, and if solar tracking systems are applied, tracking angles can be monitored too. In this study, the electrical parameters of a solar panel such as voltage, current values, orientation of the solar panel and the light intensity in the outdoor environment were recorded in the cloud storage area by sensors. The data obtained from all sensors are evaluated and preprocessed by the microcontroller. These collected data are transferred to comparable graphs under two different light intensities. The proposed work is an example of an application that, if scaled up, can be used in monitoring larger-scale systems where solar panels can be grouped in series and parallel. The novel contribution of the study is to evaluate the basic electrical parameters and orientation of solar panels together and to monitor the faults (voltage, current, solar tracking system induced faults) caused by these characteristics.

Authors

Institutions

Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1109/ubmk63289.2024.10773539
Citations
1
Primary Topic
Solar Radiation and Photovoltaics
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Solar IoT: Monitoring the Orientation and Electrical Parameters of the Solar Panel

Oğuz Gora, Hakan Dalkılıç
1 citations
Solar Radiation and Photovoltaics
0.35
article

Solar IoT: Monitoring the Orientation and Electrical Parameters of the Solar Panel

Oğuz Gora, Hakan Dalkılıç
article en
1 citations

Abstract

In recent years, the use of solar energy from renewable energy sources has been increasing. Solar energy can be used directly for electricity and heat generation, as well as for small-scale use in smart cities such as traffic lights, city lighting, vehicle charging stations. The Internet of Things enables remote monitoring and control of solar energy systems, diagnosis of faults that may occur in the system and increasing system efficiency. The energy production of the system can be monitored depending on the time of day, and if solar tracking systems are applied, tracking angles can be monitored too. In this study, the electrical parameters of a solar panel such as voltage, current values, orientation of the solar panel and the light intensity in the outdoor environment were recorded in the cloud storage area by sensors. The data obtained from all sensors are evaluated and preprocessed by the microcontroller. These collected data are transferred to comparable graphs under two different light intensities. The proposed work is an example of an application that, if scaled up, can be used in monitoring larger-scale systems where solar panels can be grouped in series and parallel. The novel contribution of the study is to evaluate the basic electrical parameters and orientation of solar panels together and to monitor the faults (voltage, current, solar tracking system induced faults) caused by these characteristics.

Yaşar University (TR)
Affordable and clean energy
Openalex Percentile: Top 31%
Solar Radiation and Photovoltaics
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.