| Title |
Solar Power Resource Assessment Using Light Detection and Ranging Data and Open Source Geographic Information System |
|
Authors |
Ellen Jane G. Gulben, Jeeng-Min Ling, Daxter William L. Gulben and Noel R. Estoperez |
|
Publication date |
2019/06 |
|
Conference |
2019 IEEE Milan PowerTech |
| Publisher |
IEEE |
| Abstract |
There is growing trend for distributed solar generation. To determine if it is a possible aid to a more sustainable power system, accurate assessment of solar potential on rooftops must be done. This study provides a fast and reliable method of solar power resource assessment using remote sensing technologies, Light Detection and Ranging (LiDAR) data and Geographic Information System (GIS). 1x1 m resolution Digital Elevation Model (DEM) is generated from point cloud data. An open-source software, System for Automated Geoscientific Analyses Geographic Information System (SAGA GIS), is used to effectively operate LiDAR point cloud and produce solar insolation maps. Monthly insolation maps of the tested area, Iligan City, and its building rooftops are created. Results show an average value 1,088.76 kWh/m 2 solar insolation and the total value of 3.61 TWh of energy is found in the building rooftop of the study area. Data validation indicates a 7.66% absolute relative error. |
| Index terms / Keywords |
Digital elevation models, energy resources, geographic information systems, remote sensing, solar energy. |
| DOI |
10.1109/PTC.2019.8810610 |
Mindanao State
University - Iligan Institute of Technology