Assessment of the photovoltaic potential at urban level based on 3D city models: A case study and new methodological approach

Rodríguez, Luis Pérez; Duminil, Éric; Ramos, José Sánchez; Eicker, Ursula

doi:10.1016/j.solener.2017.02.043

Cited by 141 publications

(64 citation statements)

References 33 publications

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“…Yet, it is unable to easily scale up from a few buildings to the citywide context. Non-BIM models based on CityGML, such as SimStadt [12] and Bremer et al [13], are also state-of-the-art because they feature complex radiation models, effortless computation for high spatial coverage, and establish relationships between the different elements represented.…”

Section: Introductionmentioning

confidence: 99%

3D Solar Potential in the Urban Environment: A Case Study in Lisbon

et al. 2019

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The assessment of solar potential in the urban environment is an important instrument for policy decision regarding renewable energy deployment in the city. This paper presents an experimentally validated 3D solar potential model for rooftops and facades from LIDAR data considering anisotropic diffuse irradiation. The data visualization is rendered in the ArcGIS platform using CityEngine to automatically generate 3D models from 2D geometries. The model is validated against summer and winter measurements of photovoltaic performance on a facade. A case study for two densely packed urban areas in Lisbon, Portugal, are presented. Facades are shown to increase the solar potential by 10 to 15%.

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Section: Introductionmentioning

confidence: 99%

3D Solar Potential in the Urban Environment: A Case Study in Lisbon

et al. 2019

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“…These methods have been used to estimate the suitability of rooftops and PV technical potential for numerous cities and countries, such as San Diego (Anders and Bialek 2006), Philadelphia (Boz et al 2015), Seoul (Hong et al 2017), Chile (Campos et al 2016), Ontario (Wiginton et al 2010), Lisbon (Brito et al 2012), Brazil (Miranda et al 2015), Minneapolis (Risse et al 2014), Austin (Wiese et al 2010), and Canada (Pelland and Poissant 2006). New methods are being developed continuously, including ones that utilize machine learning (Assouline et al 2017), 3D city models (Lukac et al 2016), and layer on economic considerations (Rodriguez et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Estimating rooftop solar technical potential across the US using a combination of GIS-based methods, lidar data, and statistical modeling

Gagnon

Margolis

Melius

et al. 2018

Environ. Res. Lett.

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“…SimStadt is still in a beta status and therefore not publicly available; however there are several studies and publications where the calculation method of SimStadt is described and the tool was used to calculate the heat demand or PV potential of different case studies [27,[34][35][36][37][38][39][40].…”

Section: Simulation Environmentmentioning

confidence: 99%

Renewable Energy Generation Scenarios Using 3D Urban Modeling Tools—Methodology for Heat Pump and Co-Generation Systems with Case Study Application †

2019

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In the paper, a method was developed to automatically dimensionalize and calculate central energy generation and supply scenarios with a district heating system for cities based on 3D building models in the CityGML format and their simulated heat demand. In addition, the roof geometry of every individual building is used to model photovoltaic energy generation potential. Two types of supply systems, namely a central heat pump (HP) system and a large co-generation (combined heat and power-CHP) system (both with a central storage and district distribution system), are modeled to supply the heat demand of the area under investigation. Both energy generation models are applied to a case study town of 1610 buildings. For the HP scenario, it can be shown that the case study town's heat demand can be covered by a monovalent, low-temperature system with storage, but that the PV only contributes 15% to the HP electricity requirement. For the CHP scenario, only 61% of the heat demand can be covered by the CHP, as it was designed for a minimum of 4000 operating hours. Both the PV and the CHP excess electricity are fully injected into the grid. As a result, the primary energy comparison of both systems strongly depends on the chosen primary energy factors (PEF): with given German regulations the CHP system performs better than the HP system, as the grid-injected electricity has a PEF of 2.8. In the future, with increasingly lower PEFs for electricity, the situation reverses, and HPs perform better, especially if the CHP continues to use natural gas. Even when renewable gas from a power to gas (P2G) process is used for the CHP, the primary energy balance of the HP system is better, because of high conversion losses in the P2G process.

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Assessment of the photovoltaic potential at urban level based on 3D city models: A case study and new methodological approach

Cited by 141 publications

References 33 publications

3D Solar Potential in the Urban Environment: A Case Study in Lisbon

3D Solar Potential in the Urban Environment: A Case Study in Lisbon

Estimating rooftop solar technical potential across the US using a combination of GIS-based methods, lidar data, and statistical modeling

Renewable Energy Generation Scenarios Using 3D Urban Modeling Tools—Methodology for Heat Pump and Co-Generation Systems with Case Study Application †

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