3D model discretization in assessing urban solar potential: the effect of grid spacing on predicted solar irradiation

Peronato, Giuseppe; Rey, Emmanuel; Andersen, Marilyne

doi:10.1016/j.solener.2018.10.011

Cited by 33 publications

(13 citation statements)

References 33 publications

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“…If we did not consider these limitations, the resulting roof area would be overestimated and probably all the performed analyzes would indicate only the theoretical (technical potential) of these areas. We encountered similar conclusions in study [57]. We assumed that the PV system could be installed in an area with a minimum size of 8 m 2 [47] (Figure 9a).…”

Section: Data Processing For the Purpose Of Roof Surface Area Delimitsupporting

confidence: 57%

Roof’s Potential and Suitability for PV Systems Based on LiDAR: A Case Study of Komárno, Slovakia

et al. 2020

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The case study focuses on evaluating the suitability of roof surfaces in terms of their solar potential based on their geometric parameters. The selected processing methodology detects segments of roof surfaces from the LiDAR base, supplemented with spatial information (orthophoto map, real estate cadastre (REC)—footprint, basic database for the geographic information system (ZBGIS)—classification of buildings—current use). The approach based on spatial analyses takes into account the limit conditions for determining the impact of solar radiation resulting from the roof area, slope, aspect, and hillshade. Considering to the available subsidy scheme for family houses in the conditions of the Slovak Republic, a narrower sample of 35 family houses was selected from the total number of typologically represented buildings (194). A 3D model of the building created by combining REC and LiDAR substrates shows the roof surface without overlap, while another 3D model made of LiDAR substrates alone represents the actual dimension of the roof surface. The results presented for each selected building show good agreement with each other, and their visualizations were obtained using two GIS environment approaches. In the area of family houses, up to 94% of the roof areas of buildings registered in the REC meet the conditions for the installation of a PV system with an output of 2.6/3.3 kW.

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Section: Data Processing For the Purpose Of Roof Surface Area Delimitsupporting

confidence: 57%

Roof’s Potential and Suitability for PV Systems Based on LiDAR: A Case Study of Komárno, Slovakia

et al. 2020

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“…For a neighborhood in Geneva, Switzerland, Peronato et al (2018) have explored grids with spacings 1 to 4 m, showing that the error increases linearly with spacing, with maximum errors of the order 7%. [ 13 ]…”

Section: Discussionmentioning

confidence: 99%

“…neighborhood in Geneva, Switzerland, Peronato et al 2018have explored grids with spacings 1 to 4 m, showing that the error increases linearly with spacing, with maximum errors of the order 7%. [13] The third factor of uncertainty is associated with the conversion of solar irradiance to PV power. The common approach for 3D solar potential assessment models is to consider a temperature-corrected single-point efficiency model, assuming that the PV power is proportional to the incoming irradiance on the surface, considering an effective performance ratio (PV system conversion efficiency including the effect of temperature).…”

Section: Discussionmentioning

confidence: 99%

Characteristic Declination—A Useful Concept for Accelerating 3D Solar Potential Calculations

Brito

Silva

Freitas³

2021

Energy Tech

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The characteristic declination is the declination for the day on which the daily extraterrestrial irradiation on a horizontal surface is identical to its monthly average value. It was introduced as a means to determine monthly average values of irradiation. Herein, its potential usefulness to reduce computing time when mapping solar potential in complex urban areas is explored. This simplification reduces computing demand by a factor of 30× while introducing a +5% to +8% error in the annual monthly irradiation on a typical urban neighborhood for low and midlatitudes. Errors are larger (+10% to +12%) for high latitudes. The magnitude of the errors is comparable to other relevant uncertainties in solar mapping tools, associated with solar radiation modeling, the layout and details of the buildings, or the photovoltaic (PV) energy yield models.

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“…For selecting and analysing energy retrofits for each building, they used a 3D city model definition of UBEM based on the CityBES platform and GIS software. Peronato et al [111] investigated the estimated error in assessing the solar potential based on 3D models used to simulate solar radiation on all building surfaces. Correspondingly, the researchers aimed to analyse the impact of grid resolution on predicted solar irradiation.…”

Section: Gis Techniques For Energy Efficiency Managementmentioning

confidence: 99%

Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review

et al. 2021

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The development of sustainable energy systems is very important to addressing the economic, environmental, and social pressures of the energy sector. Globally, buildings consume up to 40% of the world’s total energy. By 2030, it is expected to increase to 50%. Therefore, the world is facing a great challenge to overcome these problems related to global energy production. Malaysia is one of the top consumers of primary energy in Asia. In 2018, primary energy consumption for Malaysia was 3.79 quadrillion btu at an average annual rate of 4.58%. In this paper, we have carried out a detailed literature review on several previous studies of energy consumption in the world, especially in Malaysia, and how geographical information system (GIS) methods have been used for the spatial assessment of energy efficiency. Indeed, strategies of energy efficiency are essential in energy policy that could be created using various approaches used for energy savings in buildings. The findings of this review reveal that, for estimating energy consumption, exploring renewable energy sources, and investigating solar radiation, several geographic information system techniques such as multiple criteria decision analysis (MCDA), machine learning (ML), and deep learning (DL) are mainly utilized. The result indicates that the fuzzy DS method can more reliably determine the optimal PV farm locations. The 3D models are also regarded as an effective tool for estimating solar radiation, since this method generates a 3D model exportable to software tools. In addition, GIS and 3D can contribute to several purposes, such as sunlight access to buildings in urban areas, city growth prediction models and analysis of the habitability of public places.

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3D model discretization in assessing urban solar potential: the effect of grid spacing on predicted solar irradiation

Cited by 33 publications

References 33 publications

Roof’s Potential and Suitability for PV Systems Based on LiDAR: A Case Study of Komárno, Slovakia

Roof’s Potential and Suitability for PV Systems Based on LiDAR: A Case Study of Komárno, Slovakia

Characteristic Declination—A Useful Concept for Accelerating 3D Solar Potential Calculations

Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review

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