A GIS-Based Method for Identification of Wide area Rooftop Suitability for Minimum Size PV Systems Using LiDAR Data and Photogrammetry
| Autor: | Elena Koubli, Thomas R. Betts, Diane Palmer, Ian R. Cole, Ralph Gottschalg |
|---|---|
| Přispěvatelé: | Publica |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
LiDAR
wide-area solar yield lcsh:T Photovoltaic system 0211 other engineering and technologies 020101 civil engineering 02 engineering and technology 7. Clean energy lcsh:Technology solar 0201 civil engineering Identification (information) Photogrammetry Lidar Wide area building characteristics 021105 building & construction rooftop photovoltaics Environmental science Lidar data energy_fuel_technology Remote sensing |
| Zdroj: | Energies, Vol 11, Iss 12, p 3506 (2018) |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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