Estimating the efficacy of solar photovoltaic panels in Lebanon using a digital surface model: A geospatial approach

Year 2024, Volume: 6 Issue: 1, 22 - 31, 15.06.2024

Jean Doumit

https://doi.org/10.53093/mephoj.1401603

Abstract

With the escalating need for alternative energy sources due to economic crises and fossil fuel shortages in Lebanon, solar photovoltaic (PV) panels have emerged as an attractive solution. This study examines the capacity and efficacy of rooftop-installed PV solar panels. Using geospatial technologies, including Digital Surface Models drone-based photogrammetry, the study assesses geometric and solar characteristics, seasonal solar radiation, solar duration, and power for 40 PV units installed in the study area. This research presents specific quantitative values for optimal orientations that result in high solar radiation across various seasons and identifies varying slopes influencing the performance of PV solar panels. Employing the Agglomerative Hierarchical Clustering (AHC) technique, PV units are systematically classified into clusters labeled as Moderate, High, Low, and Very Low solar power, offering quantitative metrics regarding the effectiveness of distinct panels. The high-efficiency Cluster exhibits an average solar power of 1868.114 kWh/m² during the summer season, whereas the Very Low Cluster, comprising panels with minimal solar power output, averages 150.578 kWh/m² in the same season. In conclusion, the most effective PV solar panels within the study area are those oriented between 195 and 225 degrees, with shallow inclination angles and larger surface areas contributing to enhanced performance in capturing solar radiation and generating power. These precise quantitative insights contribute to informed decision-making for optimizing the placement of PV panels to enhance energy generation. The study's recommendations are substantiated by specific numerical data, guiding future solar installations to maximize solar energy generation.

Keywords

Solar radiation, Solar duration, Solar photovoltaic, Photogrammetry, GIS

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