Assessment of potential for photovoltaic roof installations by extraction of roof tilt from light detection and ranging data and aggregation to census geography. Issue 4 (1st April 2016)

• Record Type: Journal Article
• Authors: Palmer, Diane; Cole, Ian; Betts, Thomas; Gottschalg, Ralph
• Is Part Of: IET renewable power generation. Volume 10:Issue 4(2016)
• Page Start: 467
• Page End: 473
• Publication Date: 2016-04-01
• Subjects: building integrated photovoltaics -- solar cell arrays -- sunlight; photovoltaic roof installations -- roof tilt extraction -- light detection -- census geography -- electricity network operators -- rooftop PV systems -- aircraft‐based light detection -- roof tilt variation -- roof plane azimuth angles; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2015.0388
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : 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 and 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 study demonstrates the automated extraction of building roof plane characteristics from existing wide‐area, aircraft‐based 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°. 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.