A hierarchical methodology for the mesoscale assessment of building integrated roof solar energy systems

Jo, Jin Ho; Otanicar, Todd

doi:10.1016/j.renene.2011.03.038

Cited by 61 publications

(37 citation statements)

References 10 publications

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“…East-and west-facing roofs also had potential, but a north-facing roof did not have potential. The result is similar to previous studies, such as those conducted by Jo et al [25] and Ordonez et al [26]. The electricity that can be generated in each year was calculated from the watt-peak rating of the module, sunlight hours per day, and the number of rain-free days in a year.…”

Section: Resultssupporting

confidence: 85%

“…Izquierdo et al [24] studied the influence of hourly shadows on monthly values via geometrical calculations with digital terrain models; the results show that the shadowing coefficient varies from 0.33 to 0.52, depending on the municipality type (as a function of population and building densities) in Spain. Jo et al [25] utilized Google SketchUp for shadow analysis, a 3D computer modeling program able to cast shadows based on the longitude and latitude of the site. The result of the study (which included 932 buildings) was that about 30% of the total rooftop area of unshaded, predominately flat, roofs were suitable for PV applications.…”

Section: Introductionmentioning

confidence: 99%

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Identifying Potential Area and Financial Prospects of Rooftop Solar Photovoltaics (PV)

Ninsawat

Hossain

2016

Sustainability

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Abstract:In an urban area, the roof is the only available surface that can be utilized for installing solar photovoltaics (PV), and the active surface area depends on the type of roof. Shadows on a solar panel can be caused by nearby tall buildings, construction materials such as water tanks, or the roof configuration itself. The azimuth angle of the sun varies, based on the season and the time of day. Therefore, the simulation of shadow for one or two days or using the rule of thumb may not be sufficient to evaluate shadow effects on solar panels throughout the year. In this paper, a methodology for estimating the solar potential of solar PV on rooftops is presented, which is particularly applicable to urban areas. The objective of this method is to assess how roof type and shadow play a role in potentiality and financial benefit. The method starts with roof type extraction from high-resolution satellite imagery, using Object Base Image Analysis (OBIA), the generation of a 3D structure from height data and roof type, the simulation of shadow throughout the year, and the identification of potential and financial prospects. Based on the results obtained, the system seems to be adequate for calculating the financial benefits of solar PV to a very fine scale. The payback period varied from 7-13 years depending on the roof type, direction, and shadow impact. Based on the potentiality, a homeowner can make a profit of up to 200%. This method could help homeowners to identify potential roof area and economic interest.

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Section: Resultssupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Identifying Potential Area and Financial Prospects of Rooftop Solar Photovoltaics (PV)

Ninsawat

Hossain

2016

Sustainability

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“…The researchers do not discuss how many rooftops are ground-truthed for accuracy. The Chandler, Arizona, study (Jo and Otanicar 2011) includes a visual ground inspection of 150 of the 932 analyzed buildings to validate rooftop obstructions and area estimates with the satellite imagery used in the analysis.…”

Section: Validation Of Resultsmentioning

confidence: 99%

“…The Chandler study (Jo and Otanicar 2011) assesses imagery for brightness value to determine the potential areas of shadow and obstructions on commercial and government rooftops in a 4-square mile area of the city. The lengths of shadows are estimated in detail using Google SketchUp by casting simulated shadows on a 3-D building model.…”

Section: Gis-based Methodsmentioning

confidence: 99%

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

Melius

Margolis

Ong

2013

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“…Bergamasco and Asinari (2011) proposed a method to compute the available roof surface for integrated solar (PV) installations through the analysis of shadow zones, space, brightness and suitability for PV installation. Jo and Otanicar (2011) analysed the patterns of shadow cast and their effects on the rooftop in order to estimate the available rooftop area for PV installation. A number of researchers have also published works and approaches that exploit the derived information from shadow analysis.…”

Section: The Importance Of Shadow Detection In Urban Environmentsmentioning

confidence: 99%

Shadow Detection From Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

Kadhim

Mourshed

Bray

2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-theart shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of the ratio algorithm. The differences in the characteristics of the two satellite imageries in terms of spatial and spectral resolution can play an important role in the estimation and detection of the shadow of urban objects.

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A hierarchical methodology for the mesoscale assessment of building integrated roof solar energy systems

Cited by 61 publications

References 10 publications

Identifying Potential Area and Financial Prospects of Rooftop Solar Photovoltaics (PV)

Identifying Potential Area and Financial Prospects of Rooftop Solar Photovoltaics (PV)

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

Shadow Detection From Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

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