Buildings roofs photovoltaic potential assessment based on LiDAR (Light Detection And Ranging) data

Lukač, Niko; Seme, Sebastijan; Žlaus, Danijel; Štumberger, Gorazd; Žalik, Borut

doi:10.1016/j.energy.2013.12.066

Cited by 94 publications

(68 citation statements)

References 57 publications

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“…For instance, in order to validate the analysis-induced error of solar potential estimates it would be required to gauge the output of a myriad of solar panels or to place instruments (e.g. pyranometers) on many roofs (Erdélyi, Wang, Guo, Hanna, & Colantuono, 2014;Jakubiec & Reinhart, 2013;Lukač, Seme, Žlaus, Štumberger, & Žalik, 2014). Hence, when such scarce studies are available, they are limited to small sample sizes.…”

Section: Analysis-induced Errormentioning

confidence: 99%

The effect of acquisition error and level of detail on the accuracy of spatial analyses

Biljecki

Heuvelink

Ledoux

et al. 2017

Cartography and Geographic Information Science

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There has been a great deal of research about errors in geographic information and how they affect spatial analyses. A typical GIS process introduces various types of errors at different stages, and such errors usually propagate into errors in the result of a spatial analysis. However, most studies consider only a single error type thus preventing the understanding of the interaction and relative contributions of different types of errors. We focus on the level of detail (LOD) and positional error, and perform a multiple error propagation analysis combining both types of error. We experiment with three spatial analyses (computing gross volume, envelope area, and solar irradiation of buildings) performed with procedurally generated 3D city models to decouple and demonstrate the magnitude of the two types of error, and to show how they individually and jointly propagate to the output of the employed spatial analysis. The most notable result is that in the considered spatial analyses the positional error has a much higher impact than the LOD. As a consequence, we suggest that it is pointless to acquire geoinformation of a fine LOD if the acquisition method is not accurate, and instead we advise focusing on the accuracy of the data. ARTICLE HISTORY

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Section: Analysis-induced Errormentioning

confidence: 99%

The effect of acquisition error and level of detail on the accuracy of spatial analyses

Biljecki

Heuvelink

Ledoux

et al. 2017

Cartography and Geographic Information Science

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“…On the one hand, there are studies where the PV yield is calculated by merely multiplying the total solar energy cumulated in a surface in a year by a certain efficiency factor (see, e.g., [35]). On the other hand, there are cases where the yield is calculated in high temporal resolution, considering effects of shadowing, ambient and roof-top temperature (see, e.g., [36][37][38]). …”

Section: State Of the Art Of Photovoltaic Potential Evaluationmentioning

confidence: 99%

Technical, Economical and Social Assessment of Photovoltaics in the Frame of the Net-Metering Law for the Province of Salta, Argentina

et al. 2016

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Central and Northern Argentinean regions possess a high potential for the generation of solar energy. The realization of this potential is an alternative to alleviate the strong dependence on imports of fossil energy and to reduce the CO 2 emissions of the country. However, the adoption of photovoltaics (PV) is still in an incipient state. It is undermined by a context of heavily subsidized electricity prices, high equipment and installation costs and a lack of information, training and experience in handling PV technology. This paper presents a techno-economical assessment of the application of the recently enacted net-metering law for promoting renewable energies (RE) in the Province of Salta (Northwest Argentina) for the case of PV. The assessment shows under which conditions and for which types of consumers it is profitable to adopt PV in the context of the law. This analysis is supported by a participatory planning approach as a study of stakeholders' attitudes towards RE, intentions to adopt PV and their knowledge about the law. The results of this study and the economical analysis serve to provide recommendations aimed at increasing the level of PV adoption in the province.

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“…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%

“…slope and aspect), as well as to estimate shadowing effects from nearby obstructions. 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].…”

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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Buildings roofs photovoltaic potential assessment based on LiDAR (Light Detection And Ranging) data

Cited by 94 publications

References 57 publications

The effect of acquisition error and level of detail on the accuracy of spatial analyses

The effect of acquisition error and level of detail on the accuracy of spatial analyses

Technical, Economical and Social Assessment of Photovoltaics in the Frame of the Net-Metering Law for the Province of Salta, Argentina

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

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