MODERN APPROACHES TO ASSESSING THE POTENTIAL OF PHOTOVOLTAIC SYSTEMS ON BUILDING ROOFTOPS USING GIS, LIDAR, AND MACHINE LEARNING

In the context of the global transition to renewable energy sources (RES), solar energy plays a key role in the energy strategies of many countries, including Uzbekistan. One promising direction is the installation of photovoltaic (PV) systems on building rooftops, which allows for the efficient use of urban areas for electricity generation. However, assessing the solar potential of rooftops is a complex task that requires considering multiple factors, such as roof geometry, shading, orientation, and tilt angle. This article provides an overview of modern methods for assessing the solar potential of rooftops using geographic information systems (GIS), LiDAR data, and machine learning.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-14
DOI
https://doi.org/10.5281/zenodo.15023706
Primary Topic
Engineering and Agricultural Innovations
Type
article
Field-Weighted Citation Impact
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article

MODERN APPROACHES TO ASSESSING THE POTENTIAL OF PHOTOVOLTAIC SYSTEMS ON BUILDING ROOFTOPS USING GIS, LIDAR, AND MACHINE LEARNING

Zenodo (CERN European Organization for Nuclear Research)
Engineering and Agricultural Innovations
article

MODERN APPROACHES TO ASSESSING THE POTENTIAL OF PHOTOVOLTAIC SYSTEMS ON BUILDING ROOFTOPS USING GIS, LIDAR, AND MACHINE LEARNING

article en

Abstract

In the context of the global transition to renewable energy sources (RES), solar energy plays a key role in the energy strategies of many countries, including Uzbekistan. One promising direction is the installation of photovoltaic (PV) systems on building rooftops, which allows for the efficient use of urban areas for electricity generation. However, assessing the solar potential of rooftops is a complex task that requires considering multiple factors, such as roof geometry, shading, orientation, and tilt angle. This article provides an overview of modern methods for assessing the solar potential of rooftops using geographic information systems (GIS), LiDAR data, and machine learning.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 53%
Engineering and Agricultural Innovations
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