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Assessment of potential for photovoltaic roof installations by extraction of roof tilt from LiDAR data and aggregation to census geography

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posted on 18.01.2016 by Diane Palmer, Ian R. Cole, Tom Betts, Ralph Gottschalg
Large-scale adoption of solar photovoltaics (PV) in the built environment requires automation of roof suitability surveying over large geographical areas. Furthermore, as local PV installation density increases, electricity network operators require clearer information on the overall impact the large number of different rooftop PV systems will have on the stability of the local network. Knowledge of roof features (tilt angle, azimuth angle, area) and localised in-plane irradiance data is essential to meet both of these requirements. Such information is currently not available (except by individual roof surveying by PV consultants) and has to be generated. This paper demonstrates the automated extraction of building roof plane characteristics from existing wide-area, aircraft-based LiDAR (Light Detection and Ranging) data. These characteristics are then aggregated statistically and scaled-up to produce a UK-wide map of average roof tilt variation. Validation of roof tilt with site measurements taken by four different methods demonstrates a mean absolute error of 3 degrees. For major roof plane azimuth angles, banded into compass octants, accurate detection was achieved in 100% of cases, validated by inspection of aerial photography. This is sufficient for calculating in-plane irradiance for a more detailed automated assessment.

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  • Mechanical, Electrical and Manufacturing Engineering

Published in

IET Renewable Power Generation

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Special Issue

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? - ? (19)

Citation

PALMER, D. ... et al, 2016. Assessment of potential for photovoltaic roof installations by extraction of roof tilt from LiDAR data and aggregation to census geography. IET Renewable Power Generation, 10 (4), pp. 467-473

Publisher

Institution of Engineering and Technology (IET)

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VoR (Version of Record)

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This work is made available according to the conditions of the Creative Commons Attribution 3.0 (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

Publication date

2016

Notes

This is an Open Access article published by IET and made available under the terms of the Creative Commons Attribution Licence, (http://creativecommons.org/licenses/by/3.0/).

ISSN

1752-1424

Language

en

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