posted on 2019-01-11, 12:25authored byDiane Palmer, Elena Koumpli, Ian R. Cole, Ralph Gottschalg, Tom BettsTom Betts
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. The paper starts by listing current methods used and stating their strengths and weaknesses. 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 aircraft-based Light Detection and Ranging (LiDAR) data, building footprint data, GIS (Geographical Information Systems) tools, and aerial photographs. It assesses each roof’s suitability for PV deployment. That is, the characteristics of each roof are examined for fitting of at least a minimum size solar power system. In this way the minimum potential solar yield for region or city may be obtained. Accuracy is determined 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 can generate data for various PV scenarios and future analyses.
Funding
This work has been executed as part of the research projects ‘Joint UK-India Clean Energy Centre
(JUICE)’ and ‘PV2025—Potential Costs and Benefits of Photovoltaic for UK Infrastructure and Society’ which are
funded by the RCUK’s Energy Programme (contract No: EP/P003605/ and contract No: 1EP/K02227X/1).
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
Energies
Volume
11
Issue
12
Pages
3506 - 3506
Citation
PALMER, D. ... et al., 2018. A GIS-based method for identification of wide area rooftop suitability for minimum size PV systems using LiDAR data and photogrammetry. Energies, 11(12): 3506.
This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/
Acceptance date
2018-12-06
Publication date
2018-12-15
Notes
This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/