Incorporating shading losses in solar photovoltaic potential assessment at the municipal scale

Nguyên, Hà Trần; Pearce, Joshua M.

doi:10.1016/j.solener.2012.01.017

Cited by 103 publications

(58 citation statements)

References 37 publications

(63 reference statements)

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“…Figure 5 illustrates a visualisation of a shadow analysis. This use case is also essential in the estimation of the solar potential of buildings, which may negatively affect the photovoltaic yield of a solar panel [102,112,[222][223][224][225][226][227]. In this context, this use case is closely related to the previously mentioned one of estimating the insolation of buildings, and they are often used together.…”

Section: Estimation Of Shadows Cast By Urban Featuresmentioning

confidence: 99%

Applications of 3D City Models: State of the Art Review

Biljecki

Stoter

Ledoux

et al. 2015

IJGI

610

380

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In the last decades, 3D city models appear to have been predominantly used for visualisation; however, today they are being increasingly employed in a number of domains and for a large range of tasks beyond visualisation. In this paper, we seek to understand and document the state of the art regarding the utilisation of 3D city models across multiple domains based on a comprehensive literature study including hundreds of research papers, technical reports and online resources. A challenge in a study such as ours is that the ways in which 3D city models are used cannot be readily listed due to fuzziness, terminological ambiguity, unclear added-value of 3D geoinformation in some instances, and absence of technical information. To address this challenge, we delineate a hierarchical terminology (spatial operations, use cases, applications), and develop a theoretical reasoning to segment and categorise the diverse uses of 3D city models. Following this framework, we provide a list of identified use cases of 3D city models (with a description of each), and their applications. Our study demonstrates that 3D city models are employed in at least 29 use cases that are a part of more than 100 applications. The classified inventory could be useful for scientists as well as stakeholders in the geospatial industry, such as companies and national mapping agencies, as it may serve as a reference document to better position their operations, design product portfolios, and to better understand the market.

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Section: Estimation Of Shadows Cast By Urban Featuresmentioning

confidence: 99%

Applications of 3D City Models: State of the Art Review

Biljecki

Stoter

Ledoux

et al. 2015

IJGI

610

380

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“…A significant relationship was found between SVF and urban heat islands at a local scale [9]. Sky obstruction can substantially reduce the amount of solar radiation reaching the ground [10], and hence SVF serves an important role in solar radiation modeling [11,12]. It was found that SVF was significantly correlated with surface emissivity in urban canyons [13].…”

Section: Introductionmentioning

confidence: 94%

Automatic Sky View Factor Estimation from Street View Photographs—A Big Data Approach

et al. 2017

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Hemispherical (fisheye) photography is a well-established approach for estimating the sky view factor (SVF). High-resolution urban models from LiDAR and oblique airborne photogrammetry can provide continuous SVF estimates over a large urban area, but such data are not always available and are difficult to acquire. Street view panoramas have become widely available in urban areas worldwide: Google Street View (GSV) maintains a global network of panoramas excluding China and several other countries; Baidu Street View (BSV) and Tencent Street View (TSV) focus their panorama acquisition efforts within China, and have covered hundreds of cities therein. In this paper, we approach this issue from a big data perspective by presenting and validating a method for automatic estimation of SVF from massive amounts of street view photographs. Comparisons were made with SVF estimates derived from two independent sources: a LiDAR-based Digital Surface Model (DSM) and an oblique airborne photogrammetry-based 3D city model (OAP3D), resulting in a correlation coefficient of 0.863 and 0.987, respectively. The comparisons demonstrated the capacity of the proposed method to provide reliable SVF estimates. Additionally, we present an application of the proposed method with about 12,000 GSV panoramas to characterize the spatial distribution of SVF over Manhattan Island in New York City. Although this is a proof-of-concept study, it has shown the potential of the proposed approach to assist urban climate and urban planning research. However, further development is needed before this approach can be finally delivered to the urban climate and urban planning communities for practical applications.

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“…State-of-the-art methods also consider shadowing from vegetation by either using semitransparent vegetation modelling [6] or light transmission estimation by using satellite-derived Leaf Area Index (LAI) [10]. Most of the state-of-the-art also consider only the constant efficiency of a PV module when estimating the PV potential [8]. Recently, it has been shown that it has bias in accuracy, in comparison to using the nonlinear efficiency characteristics of a PV module and a solar inverter [10].…”

Section: Introductionmentioning

confidence: 99%

Photovoltaic potential assessment and ranking of rooftops segments based on LiDAR data

Lukač¹,

Žalik²,

Štumberger³

2017

REPQJ

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This paper deals with a method for determining the rating of roofs' segments in urban areas regarding their suitability for the installation of different photovoltaic (PV) systems. In order to determine the received irradiance of individual roofs, their geometry is described based on LiDAR (Light Detection And Ranging) data, in order to estimate accurately the effect of shadowing and topography. The input irradiance is based on a Typical Meteorological Year (TMY), which is established over long-term irradiance measurements. The PV potential is then estimated by integrating estimated per-surface direct and anisotropic diffuse irradiances filtered with nonlinear efficiency characteristics of a given PV system. Afterwards, the roofs' segments are rated based on the estimated PV potential from low to high suitability. The proposed method was applied over a large urban area scanned by airborne LiDAR, and validated with local power plant, where 96.49% agreement was reached.

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Incorporating shading losses in solar photovoltaic potential assessment at the municipal scale

Cited by 103 publications

References 37 publications

Applications of 3D City Models: State of the Art Review

Applications of 3D City Models: State of the Art Review

Automatic Sky View Factor Estimation from Street View Photographs—A Big Data Approach

Photovoltaic potential assessment and ranking of rooftops segments based on LiDAR data

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