Preprint Article Version 1 This version is not peer-reviewed

A GIS-Based Method for Identification of Wide area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry

Version 1 : Received: 19 November 2018 / Approved: 21 November 2018 / Online: 21 November 2018 (06:59:32 CET)

A peer-reviewed article of this Preprint also exists.

Palmer, D.; Koumpli, E.; Cole, I.; Gottschalg, R.; Betts, T. A GIS-Based Method for Identification of Wide Area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry. Energies 2018, 11, 3506. Palmer, D.; Koumpli, E.; Cole, I.; Gottschalg, R.; Betts, T. A GIS-Based Method for Identification of Wide Area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry. Energies 2018, 11, 3506.

Journal reference: Energies 2018, 11, 3506
DOI: 10.3390/en11123506

Abstract

A new method for wide-area urban roof assessment of suitability for solar photovoltaics is introduced and validated. Knowledge of roof geometry and physical features is essential for evaluation of the impact of multiple rooftop solar photovoltaic (PV) system installations on local electricity networks. This paper begins by reviewing and testing a range of existing techniques for identifying roof characteristics. It was found that no current method is capable of delivering accurate results with publicly available input data. Hence a different approach is developed, based on slope and aspect using LIDAR data, building footprint data, GIS tools and aerial photographs. It assesses each roof’s suitability for PV installation. That is, its properties should allow the installation of at least a minimum size photovoltaic system. In this way the minimum potential solar yield for region or city may be obtained. The accuracy of the new method is then established, by ground-truthing against a database of 886 household systems. This is the largest validation of a rooftop assessment method to date. The method is flexible with few prior assumptions. It is based on separate consideration of buildings and can therefore generate data for various PV scenarios and future analyses.

Subject Areas

solar; LiDAR; rooftop photovoltaics; building characteristics; wide-area solar yield

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