Investigating rooftop solar energy potential in coastal area with unmanned aerial vehicle technology

Bengkulu has abundant direct sunlight all year round. Nonetheless, this region faces limited energy availability. Based on its potential, there is an immense opportunity for the development of electrical energy systems based on solar energy. In the coastal area, the operation of this energy system is still too limited and vulnerable. In order to fix energy requirements, a rooftop solar photovoltaic (PV) system can be implemented. The utilization of the rooftop requires preliminary studies related to solar mapping to identify the economic potential of the rooftop solar energy system. In this study, Unmanned Aerial Vehicle (UAV / Drone) technology has been adopted to map the potential of rooftop solar PV system. The drone is used to collect aerial photographic data on the rooftop, which is then processed to acquire a two-dimensional map. This map is used to obtain rooftop parameters such as area, tilt angle, and orientation of the roof. These rooftop parameters are favorable to estimate the potential of solar energy that can be generated. Based on these parameters, an estimate is made to assess the maximum solar energy that can be generated if the building rooftop is installed with a number of solar panels. To calibrate the calculated parameters of the rooftop, we compare the calculation results with the direct measurements. It has been proven that the drone technology can give promising results on high-resolution mapping of solar potential area. In addition, direct normal irradiance measurements are also performed in the case study area by using previously developed equipment.

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Publication Details

Journal
Journal of Energy Systems
Published
2025-03-15
DOI
https://doi.org/10.30521/jes.1416277
Citations
1
Primary Topic
Solar Radiation and Photovoltaics
Type
article
Field-Weighted Citation Impact
2.48
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article

Investigating rooftop solar energy potential in coastal area with unmanned aerial vehicle technology

Elfi Yuliza, Riska Ekawita, Ismail Fahmy Almadi
1 citations
Journal of Energy Systems
Solar Radiation and Photovoltaics
2.48
article

Investigating rooftop solar energy potential in coastal area with unmanned aerial vehicle technology

Elfi Yuliza, Riska Ekawita, Ismail Fahmy Almadi
article en
1 citations

Abstract

Bengkulu has abundant direct sunlight all year round. Nonetheless, this region faces limited energy availability. Based on its potential, there is an immense opportunity for the development of electrical energy systems based on solar energy. In the coastal area, the operation of this energy system is still too limited and vulnerable. In order to fix energy requirements, a rooftop solar photovoltaic (PV) system can be implemented. The utilization of the rooftop requires preliminary studies related to solar mapping to identify the economic potential of the rooftop solar energy system. In this study, Unmanned Aerial Vehicle (UAV / Drone) technology has been adopted to map the potential of rooftop solar PV system. The drone is used to collect aerial photographic data on the rooftop, which is then processed to acquire a two-dimensional map. This map is used to obtain rooftop parameters such as area, tilt angle, and orientation of the roof. These rooftop parameters are favorable to estimate the potential of solar energy that can be generated. Based on these parameters, an estimate is made to assess the maximum solar energy that can be generated if the building rooftop is installed with a number of solar panels. To calibrate the calculated parameters of the rooftop, we compare the calculation results with the direct measurements. It has been proven that the drone technology can give promising results on high-resolution mapping of solar potential area. In addition, direct normal irradiance measurements are also performed in the case study area by using previously developed equipment.

Journal of Energy SystemsVol. 9(1)
Mulawarman University (ID), University of Bengkulu (ID)
Openalex Percentile: Top 11%
Solar Radiation and Photovoltaics
2.48
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