Methodology for estimating solar potential on multiple building rooftops for photovoltaic systems

Methodology for the assessment of PV capacity over a city region using low-resolution LiDAR data and application to the City of Leeds (UK)

“…Previously reported methods to calculate the potential PV capacity over a city region include image analysis of geometrically-corrected high-resolution aerial photography [4,5], statistical approaches based on correlations between building class, population, and roof profile [6][7][8], and roof profile reconstruction from light detection and ranging (LiDAR) point clouds [9][10][11][12][13][14][15][16][17][18][19][20].…”

“…An accurate assessment of the potential roof-mounted PV capacity in city regions is an essential component for establishing regional and national carbon reduction policies and informing investment decisions [3]. However, such assessments are not straightforward because of the range in size, orientation, pitch, and geometric complexity typically found in roof profiles.Previously reported methods to calculate the potential PV capacity over a city region include image analysis of geometrically-corrected high-resolution aerial photography [4,5], statistical approaches based on correlations between building class, population, and roof profile [6][7][8], and roof profile reconstruction from light detection and ranging (LiDAR) point clouds [9][10][11][12][13][14][15][16][17][18][19][20].Methods that utilise LiDAR data usually employ an error-minimising plane-fitting algorithm that divides each roof in to an arbitrary set of planes, which are referred to as roof segments. While such methods report high accuracy for large geometrically simple roofs, such as warehouses, they invariably require high-resolution LiDAR data to achieve accurate results for small buildings, such as residential properties, with inherently more complex roof profiles.…”

Estimating Rooftop Suitability for PV: A Review of Methods, Patents, and Validation Techniques

“…No results had been presented as of 2010, the date of Liddell's presentation. Kodysh et al (2013) use LiDAR data to calculate slope, aspect, and solar radiation values-determined by cloud cover and transmissivity data-for Knox County, Tennessee. Building footprints are extracted from a DEM and buffered by 25 meters to lessen the amount of data needing processing while still capturing shading influences from nearby buildings and trees.…”

Mapping suitability areas for concentrated solar power plants using remote sensing data

“…More recently, r.sun has been coupled with a canopy openness index derived from light detection and ranging (LiDAR) data to produce a subcanopy solar radiation model. 19 Recently, Kodysh et al 20 presented a methodology that advances previous efforts by estimating solar radiation potentials on multiple rooftops in an urban area for photovoltaic (PV) applications using DEM from LiDAR data and an upward looking hemispherical algorithm. Their methodology considers input parameters such as surface orientation, shadowing effect, elevation, and atmospheric conditions that influence solar intensity on the Earth's surface; it was implemented for some 212,000 buildings in Knox County, Tennessee, United States.…”