Solar access of residential rooftops in four California cities
Introduction
Tree-planting programs designed to shade and cool the south or west sides of buildings can inadvertently limit the solar access of rooftop solar-energy systems, including photovoltaic panels and thermal collectors. Several researchers have modeled the influence of shade on the solar access of buildings. Kaye et al. (1997) observed from the street the geometries of the roofs on and trees near 60 houses in an inner-city suburban region of Sydney, Australia. They then used ray-tracing software to predict the locations of on-hour shadows and estimate the average daily output of a nominally 1 kW rooftop photovoltaic array during winter months. Mardaljevic and Rylatt (2003) applied the Radiance lighting-simulation system to a three-dimensional model of San Francisco to generate a map of annual insolation on modeled urban surfaces, including walls and roofs. Compagnon (2004) also applied Radiance to three-dimensional building models to estimate urban solar availability, but presented results only for walls.
The CH2MHill Solar Automated Feature Extraction™ methodology (2008) uses stereo aerial imagery to build three-dimensional model of buildings, then geometrically computes each building’s solar access. This software does not consider trees because it is difficult to determine the heights of curved surfaces from stereo imagery.
Simpson (2002) and Akbari (2002) each modeled the influence of tree shading on residential energy use for heating and cooling. McPherson and Simpson (2003) determined tree-canopy coverage from aerial photographs of 21 California cities to determine the extent to which tree planting programs could reduce energy use in California communities. Akbari et al. (2003) and Rose et al. (2003) also estimated urban tree cover from high-resolution orthophotos. However, none of these studies quantified shading of rooftops.
This paper estimates the extent to which shading reduces the solar radiation incident on residential roofs in the four California cities of Sacramento, San Jose, Los Angeles and San Diego. This shading analysis can be used to better estimate power production and/or thermal collection by rooftop solar-energy equipment. It can also be considered when designing programs to plant shade trees.
Section snippets
Methodology
The locations and elevation profiles of buildings and trees are estimated by combining aerial photography with remote measurements of surface height. The fraction of each flat element of the roof’s surface, or “roofing plane,” that is shaded at a given hour of the year is determined by geometric computation of the extent to which trees and buildings obscure the path between the sun and the plane. This “shade fraction” gauges only the absence of direct sunlight. It does not distinguish between
Special characteristics of S-, SW- and W-facing planes
The following analysis pays special attention to the “S + SW + W” subset of roofing planes that face S, SW or W, because solar equipment is commonly installed on such planes for maximum solar access. For example, assuming a plane slope of 5:12, annual mean raw global solar irradiance in the four study regions is greatest for S-facing planes; values for SW-, SE-, W- and E-facing planes are 3–5%, 5–7%, 10–15% and 15–20% lower, respectively (Fig. 9). However, the raw global solar irradiances received
Conclusions
Tree growth increased annual total light-loss fractions for the S + SW + W-facing planes by about 50–70% over 30 years, from 0.07 to 0.08 in year zero to 0.11–0.14 in year 30. Annual extraparcel light-loss fractions very slightly increased from 0.01 in years zero to 0.01–0.02 in year 30. Trees and buildings in neighboring parcels were responsible for only about 10% of the annual light loss of these roofing planes (i.e., annual extraparcel shade fraction/annual total shade fraction ≈ 10%).
Shading
Acknowledgments
This work was supported by the California Energy Commission (CEC) through its Public Interest Energy Research Program (PIER) and by the Assistant Secretary for Energy Efficiency and Renewable Energy under Contract No. DE-AC02-05CH11231. We thank Bill Pennington of the California Energy Commission for helping to organize the study and for his guidance and support. For identifying trees, we thank Dan Pskowski, arborist, City of Sacramento; Ralph Mize, arborist, City of San Jose; David Lofgren,
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Present address: Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec, Canada.