A Sparse Voxel Octree-Based Framework for Computing Solar Radiation Using 3D City Models

abstract: An effective three-dimensional (3D) data representation is required to assess the spatial distribution of the photovoltaic potential over urban building roofs and facades using 3D city models. Voxels have long been used as a spatial data representation, but practical applications of the voxel representation have been limited compared with rasters in traditional two-dimensional (2D) geographic information systems (GIS). We propose to use sparse voxel octree (SVO) as a data representation to extend the GRASS GIS r.sun solar radiation model from 2D to 3D. The GRASS GIS r.sun model is nested in an SVO-based computing framework. The presented 3D solar radiation computing framework was applied to 3D building groups of different geometric complexities to demonstrate its efficiency and scalability. We presented a method to explicitly compute diffuse shading losses in r.sun, and found that diffuse shading losses can reduce up to 10% of the annual global radiation under clear sky conditions. Hence, diffuse shading losses are of significant importance especially in complex urban environments

Data driven tools to assess the location of photovoltaic facilities in urban areas

Urban sustainability is a significant factor in combating climate change. Replacing polluting by renewable energies is fundamental to reduce the emission of greenhouse gases. Photovoltaic (PV) facilities harnessing solar energy, and particularly self-consumption PV facilities, can be widely used in cities throughout most countries. Therefore, locating spaces where photovoltaic installations can be integrated into urban areas is essential to reduce climate change and improve urban sustainability. An open-source software (URSUS-PV) to aid decision-making regarding possible optimal locations for photovoltaic panel installations in cities is presented in this paper. URSUS-PV is the result of a data mining process, and it can extract the characteristics of the roofs (orientation, inclination, latitude, longitude, area) in the urban areas of interest. By combining this information with meteorological data and characteristics of the photovoltaic systems, the system can predict both the next-day hourly photovoltaic energy production and the long-term photovoltaic daily average energy production.This work has been supported by the project RTI2018-095097-B-I00 at the 2018 call for I+D+i Project of the Ministerio de Ciencia, Innovación y Universidades, Spain. Funding for open access charge: Universidad de Málaga/CBUA, Spain

The Application of LiDAR Data for the Solar Potential Analysis Based on Urban 3D Model

Solar maps are becoming a popular resource and are available via the web to help plan investments for the benefits of renewable energy. These maps are especially useful when the results have high accuracy. LiDAR technology currently offers high-resolution data sources that are very suitable for obtaining an urban 3D geometry with high precision. Three-dimensional visualization also offers a more accurate and intuitive perspective of reality than 2D maps. This paper presents a new method for the calculation and visualization of the solar potential of building roofs on an urban 3D model, based on LiDAR data. The paper describes the proposed methodology to (1) calculate the solar potential, (2) generate an urban 3D model, (3) semantize the urban 3D model with different existing and calculated data, and (4) visualize the urban 3D model in a 3D web environment. The urban 3D model is based on the CityGML standard, which offers the ability to consistently combine geometry and semantics and enable the integration of different levels (building and city) in a continuous model. The paper presents the workflow and results of application to the city of Vitoria-Gasteiz in Spain. This paper also shows the potential use of LiDAR data in different domains that can be connected using different technologies and different scales.The European Union’s Horizon 2020 research and innovation program under grant agreement No 691883, SMARTENCITY supported and funded this study

Circular statistics applied to the study of the solar radiation potential of rooftops in a medium-sized city

La energía solar constituye una de las fuentes de energía alternativa más eficaces para combatir el cambio climático. Sin embargo, el potencial solar de una ciudad puede variar dependiendo de la morfología urbana. El propósito de este trabajo es realizar un análisis estadístico direccional de la distribución del potencial solar mensual de los tejados de la ciudad de Cáceres, España, en relación con las orientaciones e inclinaciones de los tejados. Se han evaluado dos zonas residenciales, una en el centro de la ciudad y otra en las afueras de la misma, y una zona industrial, todas ellas con diferentes morfologías urbanas. Se han evaluado las estadísticas teniendo en cuenta los valores de orientación y pendiente de las azoteas como datos circulares, y los valores de radiación como datos lineales. Las tres morfologías urbanas disímiles dan como resultado diferentes valores de potencial solar, y la desagregación mensual de los datos permite detectar las diferencias existentes en el potencial solar entre cada zona, durante cada mes. El análisis propuesto también podría extrapolarse a la planificación urbana para el diseño de ciudades más sostenibles para hacer frente a los desafíos asociados al cambio climático.Solar energy constitutes one of the most effective alternative energy sources for combating climate change. However, the solar potential in a city can vary depending on the urban morphology. The purpose of this paper is to perform a directional statistical analysis of the distribution of the monthly solar potential of rooftops in the city of Cáceres, Spain, in relation to the orientations and slopes of the rooftops. Two residential areas, one in the city center and one on the outskirts of the city, and an industrial zone, all of which exhibit different urban morphologies, have been evaluated. Statistics have been assessed in consideration of the orientation and slope values of the rooftopsas circular data, and the radiation values as linear data. The three dissimilar urban morphologies result in different solar potential values, and the monthly disaggregation of the data enables theability to detect the differences existing in the solar potential between each zone, during each month. The proposed analysis could also be extrapolated to urban planning for the design of more sustainable cities to face the challenges associated with climate change.• Gobierno de Extremadura y Fondo de desarrollo Regional Europeo. Proyecto GR15129peerReviewe

Solar energy potential assessment on rooftops and facades in large built environments based on LiDAR data, image processing and cloud computing. Methodological background, application and validation in Geneva (solar cadaster)

The paper presents the core methodology for assessing solar radiation and energy production on building rooftops and vertical facades (still rarely considered) of the inner-city. This integrated tool is based on the use of LiDAR, 2D and 3D cadastral data. Together with solar radiation and astronomical models it calculates the global irradiance for a set of points located on roofs, ground and facades. Although the tool takes simultaneously roofs, ground and facades, different methods of shadow casting are applied. Shadow casting on rooftops is based on image processing techniques. On the other hand, the assessment on facade involves first to create and interpolate points along the facades and then to implement a point-by-point shadow casting routine. The paper is structured in five parts: (i) state of the art on the use of 3D GIS and automated processes in assessing solar radiation in the built environment, (ii) overview on the methodological framework used in the paper, (iii) detailed presentation of the method proposed for solar modelling and shadow casting, in particular by introducing an innovative approach for modelling the Sky View Factor (SVF), (iv) demonstration of the solar model introduced in this paper through applications in Geneva’s building roofs (solar cadaster) and facades, (v) validation of the solar model in some Geneva’s spots, focusing especially on two distinct comparisons: solar model versus fisheye catchments on partially inclined surfaces (roof component); solar model versus photovoltaic simulation tool PVSyst on vertical surfaces (facades). Concerning the roof component, validation results emphasize global sensitivity related to the density of light sources on the sky vault to model the SVF. The low dense sky model with 145 light sources gives satisfying results, especially when processing solar cadasters in large urban areas, thus allowing to save computation time. In the case of building facades, introducing weighting factor in SVF calculation leads to outputs close to those obtained by PVSyst. Such good validation results make the proposed model a reliable tool to: (i) automatically process solar cadaster on building rooftops and facades at large urban scales, (ii) support solar energy planning and energy transition policies

Method for estimating solar energy potential based on photogrammetry from unmanned aerial vehicles

This study presents a method to estimate the solar energy potential based on 3D data taken from unmanned aerial devices. The solar energy potential on the roof of a building was estimated before the placement of solar panels using photogrammetric data analyzed in a geographic information system, and the predictions were compared with the data recorded after installation. The areas of the roofs were chosen using digital surface models and the hemispherical viewshed algorithm, considering how the solar radiation on the roof surface would be affected by the orientation of the surface with respect to the sun, the shade of trees, surrounding objects, topography, and the atmospheric conditions. The results show that the efficiency percentages of the panels and the data modeled by the proposed method from surface models are very similar to the theoretical efficiency of the panels. Radiation potential can be estimated from photogrammetric data and a 3D model in great detail and at low cost. This method allows the estimation of solar potential as well as the optimization of the location and orientation of solar panels

Methodology for the assessment of PV capacity over a city region using low-resolution LiDAR data and application to the City of Leeds (UK)

An assessment of roof-mounted PV capacity over a local region can be accurately calculated by established roof segmentation algorithms using high-resolution light detection and ranging (LiDAR) datasets. However, over larger city regions often only low-resolution LiDAR data is available where such algorithms prove unreliable for small rooftops. A methodology optimised for low-resolution LiDAR datasets is presented, where small and large buildings are considered separately. The roof segmentation algorithm for small buildings, which are typically residential properties, assigns a roof profile to each building from a catalogue of common profiles after identifying LiDAR points within the building footprint. Large buildings, such as warehouses, offer a more diverse range of roof profiles but geometric features are generally large, so a direct approach is taken to segmentation where each LiDAR point within the building footprint contributes a separate roof segment. The methodology is demonstrated by application to the city region of Leeds, UK. Validation by comparison to aerial photography indicates that the assignment of an appropriate roof profile to a small building is correct in 81% of cases

The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET v1.0) : an efficient and user-friendly model of city cooling

The adverse impacts of urban heat and global climate change are leading policymakers to consider green and blue infrastructure (GBI) for heat mitigation benefits. Though many models exist to evaluate the cooling impacts of GBI, their complexity and computational demand leaves most of them largely inaccessible to those without specialist expertise and computing facilities. Here a new model called The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET) is presented. TARGET is designed to be efficient and easy to use, with fewer user-defined parameters and less model input data required than other urban climate models. TARGET can be used to model average street-level air temperature at canyon-to-block scales (e.g. 100 m resolution), meaning it can be used to assess temperature impacts of suburb-to-city-scale GBI proposals. The model aims to balance realistic representation of physical processes and computation efficiency. An evaluation against two different datasets shows that TARGET can reproduce the magnitude and patterns of both air temperature and surface temperature within suburban environments. To demonstrate the utility of the model for planners and policymakers, the results from two precinct-scale heat mitigation scenarios are presented. TARGET is available to the public, and ongoing development, including a graphical user interface, is planned for future work