Publications

The three-dimensional urban geometry induces complex variations of incident solar radiation spanning multiple spatial and temporal scales, which need to be characterised. Benefits of higher-order orthogonal decomposition over conventional linear low-rank approximation methods for the detailed analysis of irradiance variability in urban fabrics is investigated. A backward Monte Carlo method is used to estimate the annual shortwave radiative flux density on the envelope of a cubic building at the centre of a theoretical district presenting regional variations in its total site coverage and global aspect ratio. The simulated field is represented as a three-way array from its a priori known temporal patterns (daily, seasonal) and decomposed by Tucker Higher-Order Singular Value Decomposition (HOSVD), for comparison with Principal Component Analysis (PCA). Dominant modes of variation are extracted and ordered by maximum influence. Both methods show complementary advantages for the identification of intra-urban regions subject to specific variations of irradiance in space and time. Information about daily and seasonal periods of high variability is provided, and corresponding disruptions to its spatial distribution are portrayed. The influence of prominent geometries on the direct radiative component variation is especially highlighted. Findings eventually pave the way to applications in urban planning (e.g. implementation of decision support systems for the optimal positioning of solar collectors) and studies (e.g. improvement of solar cadastres, definition of low-rank surrogates for large-scale microclimate models).

With the rapid expansion of Rooftop Photovoltaic (RPV) systems, accurately identifying the location of these installations has become essential for urban planning, grid management, and socio-economic analysis. However, existing European datasets of RPV systems are often limited in both spatial coverage and precision, especially in regions with diverse architectural styles. This study presents a novel methodology for identifying RPV systems by employing a convolutional neural network (CNN) trained on high-resolution aerial imagery and building registry data. Alternatively to traditional tile-based methods, we propose a building-by-building approach, ensuring that each building is individually assessed. The model was trained and validated on five French departments representing a variety of roofing materials and urban typologies. It demonstrates a high correlation between predicted and registered RPV systems, though detection performance varies with roofing materials—achieving better accuracy on tiled roofs than slate roofs. When applied to the entire metropolitan French territory, the model processed images of more than 40 million buildings, identifying approximately 600,000 RPV systems. The results’ accuracy is evaluated, taking into account factors such as data quality and local urban characteristics. All data and the model are publicly available for further research and applications.

The three-dimensional urban geometry introduces complex variations in incident solar radiation across multiple spatiotemporal scales. This study relies on multilinear modal decomposition for characterising the simultaneous variability of the urban solar resource in space and time. The annual irradiance on building envelopes in a theoretical district granted structural and material heterogeneity is estimated using a backward Monte Carlo method. The simulated field is arranged as a three-way tensor from its known temporal characteristics and decomposed using Higher-Order Singular Value Decomposition (HOSVD). Dominant spatial and temporal (daily and seasonal) modes of variation are extracted and ranked according to their influence, enabling the identification of main variability-prone intra-urban regions. The approach provides insights into specific periods of heightened irradiance variations throughout the year and day, while revealing corresponding disruptions to its spatial distribution. The impact of prominent features on the direct sunlight obstruction is especially portrayed.

The European targets for the Energy Transition by 2030 are strongly oriented toward the massive diffusion of PV plants, both at the building level and in large-scale utility systems on land. The expected PV capacity in Europe by 2030 is 900 GW, 4.3 times the 2022 level. Bifacial modules are currently the best solution for utility-scale PV systems, offering higher solar energy yields with minimal additional costs. This paper helps improve the efficiency of bifacial PV power plants at the European scale through the optimization of tilt angles in various configurations. Typical Meteorological Year data are retrieved from the PVGIS platform for a series of 2382 points uniformly distributed across Europe according to a regular 50 km × 50 km grid. A cumulative sky radiance is built for each location and an iterative search for the best tilt angle is performed to maximize the annual energy yield (on both front and back surfaces considering direct, diffuse and reflected energy) of south-facing modules, with both ground albedo and PV row spacing taken as parameters. Latitude is the primary influencing factor for optimal tilt angles, with an average value ranging from 26 • for Greece to 36 • for Finland. The results indicate that the Ground Coverage Ratio is also a significant parameter, while albedo has only a minor effect. The study of an Alpine region with a finer grid shows that mountainous terrain leads to reduced optimal tilt angles. A free web-based tool has been developed to provide optimal tilt angles for any location in Europe.

With the increasing integration of photovoltaic (PV) systems in residential buildings and their growing deployment in urban areas, it is essential to adopt a bottomup approach and systematically examine the optimal placement of PV panels at the building scale. This study evaluates key building criteria and analyzes the correlation between energy production and consumption across different orientations. To determine the optimal placement of PV panels, a holistic approach is adopted, incorporating energy, economic, and environmental indicators such as load matching, net present value, payback period, levelized cost of energy, and annual carbon emissions. Additionally, a new flexibility factor, load-Match pricing, is utilized to assess the influence of electricity pricing on the load matching factor. Each indicator is first optimized as a single objective, followed by a multi-objective optimization approach to balance trade-offs between energy, economic, and environmental indicators. The results highlight that façades are more effective in enhancing load matching, whereas roofs offer greater economic benefits. Further insights of optimization process are discussed.

With the photovoltaic (PV) market significantly growing thanks to the support of environmental incentives, it is essential to address the influence of climate change on PV performances. In the literature, several methodologies have been suggested to measure the effect of climate change through module temperature losses and natural degradation rates, but no work has been found to combine both of them. This paper tackles this issue through a numerical approach in order to quantify to which extent climate change impacts the performance of a PV installation over its lifetime. The methodology has been applied in different French cities where climate change is found to have a moderate effect on the Performance Ratio.

The spatial quantification of solar resources is necessary for the deployment of solar systems and must consider the local specificities of territories, such as complex topography in mountainous areas. This paper presents a methodology for obtaining solar cadastres, based on the Solar Energy on Building Envelopes (SEBE) model incorporated in QGIS and applied to French municipalities. The differences in solar potential between plain and mountain villages are analyzed through the simulation of 92 carefully selected villages located in these two types of regions. The distributions of annual rooftop irradiation per building are obtained for each studied village and approximated with a Johnson’s SU density function. From this arises the definition of two statistical indicators: the mode and the spread at one-third maximum. Main results include a mean decrease in the mode of 189 kWh/m² and a higher dispersion of 69 kWh/m² between mountain and plain villages. Two physical indicators, the Sky View Index (SVI) and the Diffuse Fraction Index (DFI), are defined to explain these differences in the shape of the distributions. Higher cloud covers (high DFI) and the presence of distant shading effects (low SVI), caused by terrain relief, explains respectively the smaller modes and the higher dispersion observed in mountainous areas. SVI, DFI and latitude are fed to a multiple linear regression model, allowing the estimation of distributions with smaller computational costs than the developed methodology. Overall, this analysis demonstrates that the characteristics of mountainous environments greatly influence solar resources and should be considered in energy planning.

As cities are major energy consumers challenges arise in densely populated areas that limit solar resources, hindering the deployment of urban solar power plants. To address this, the paper underscores the importance of digital tools for modeling solar energy accessibility within the urban fabric, focusing on rooftops, building facades, and other relevant locations. In this context, the development of the solar cadaster in Greater Geneva is presented in the paper within the framework of the European INTERREG G2 Solar project (2019–2022). The solar cadaster relies on a rich database from the Geneva Land Information System (SITG), offering comprehensive data on Digital Surface Models, building and roof cadasters, land cover, and more. Notably, this data, including the solar cadaster outputs, is accessible to the public as open data, fostering its extensive use in academia for teaching and research. It serves as a living laboratory for urban solar studies, with its open data approach contributing to widespread adoption. The project, a collaborative effort involving academia, energy utilities, and public institutions on both sides of the border, aims to unite stakeholders and foster a dialogue on solar energy in the region, in line with its commitment to addressing climate change, striving for carbon neutrality by 2050. The paper articulates the steps, methods, and outcomes of the project, offering insights into the challenges of implementing a shared online application tool in a cross-border territory. The propositions are based on feedbacks from stakeholders and lessons learned from case studies. The paper also delves into the shift in the business model for solar photovoltaic installations, emphasizing the need to model self-consumption in buildings. It concludes by highlighting the solar cadaster as a unifying means, fostering cohesion among diverse stakeholders in the region’s energy sector and propelling them toward common governance around solar energy.

Extremely high urban temperatures adversely affect photovoltaic (PV) system performance. Accurate PV cell temperature assessment relies on local weather conditions, exacerbated by urban overheating, often overlooked by inadequate temperature models and non-local data. This study investigates the electrical and thermal PV performance, considering mounting configurations and local conditions. Data from ten weather stations in Greater Sydney (NSW) during 2016-2017, including a hot summer, are used. The Sandia model is used to predict cell temperatures and power output for four mounting configurations, from open rack to building-integrated (BIPV). A PV thermal model is implemented to analyse daytime convection, crucial for understanding PV impact on local climate. Results show peak cell temperatures of 60°C (open rack) to over 90°C (BIPV), causing up to 50% power loss and 11% reduction in monthly performance ratio. Local climate variations impact PV energy output up to 6%, with mounting configuration effects up to 11%. Daytime convective flux averages 150-180 W/m², peaking at 700 W/m². Convective release varies up to 22% based on local climate, generally higher for open rack than close roof mounts, with potential reversals under low wind speed conditions. These findings can improve the knowledge of PV performances in urban areas facing extreme temperatures.

This study presents a fully reproducible clustering-based methodology for the assessment of the urban heat island intensity (UHII) at the territory scale, using parametric microclimate models and limited computational resources. In large-scale climate modeling, a common preliminary operation is to utilize the well-established Local Climate Zone classification to characterize the thermal response of urban areas based on morphology. With the increasing availability of urban datasets, data-driven approaches can be implemented to quantitatively derive meaningful urban features without relying on a standardized classification. The proposed methodology employs a Gaussian Mixture Model clustering algorithm to partition the urban territory into a suitable number of homogeneous microclimate zones, enabling the calculation and mapping of the UHII for each zone through the Urban Weather Generator (UWG) tool. The developed approach is applied to the Canton of Geneva, Switzerland, identifying ten microclimatic areas and analyzing the spatiotemporal variation of UHII. Results show yearly average values of UHII ranging from 1.7°C to 2.2°C, depending on urban morphology. The simulated values are partially validated by comparison with on-site measurements from two urban weather stations, yielding a satisfactory agreement. The methodology can support urban planning with the goal of avoid overheating through a large-scale mapping.

Building rooftops represent one of the most valuable resources to harvest solar energy in cities. Nevertheless, this potential is limited by the urban morphology impacting the shading conditions. This study suggests a general methodology to assess the impact of urban form on solar harvesting. To this aim, a new GIS-based approach is developed to extract meaningful morphological parameters at a very large scale. The rooftop overall shading rate is here defined as a benchmark, and it is measured through a scaled insolation representing the ratio between the insolation of a surface within the urban context and its unshaded theoretical maximum. A set of 40 morphological features is calculated for 60,000 buildings in the Canton of Geneva (Switzerland), and the scaled solar insolation of about 350,000 roof pieces is derived from the Solar Cadaster of Geneva. The results outline the insolation distribution within the city and as a function of urban morphology. The rooftop overall shading rate shows moderate Pearson coefficients (r = 0.2/0.4) towards some parameters, namely building height, volume, and height difference with surroundings, while others seem irrelevant. Analysing the 48 Geneva municipalities one at a time, the denser downtown areas reach higher correlation levels (r = 0.4/0.6) compared to the suburban ones.

In the context of a rapid and massive deployment or renewable energy and in particular solar photovoltaic, it is necessary to develop methods and tools to guide this deployment. To this end, this work proposes a multicriteria approach for evaluating the suitability of a building to be equipped with photovoltaic (PV) systems (PV suitability). In the present case, technical (roof complexity), economic (payback period), environmental (CO2 reduction), energetic (self-consumption), as well as social (heritage constraint) criteria are considered. These criteria are evaluated for each building of the Greater Geneva Agglomeration (GGA), a cross-border French–Swiss territory of nearly 270 000 buildings. A multicriteria method, ELECTRE TRI, makes it possible to sort these buildings into three categories, A, B, and C, that correspond to “very high,” “high,” and “moderate” PV suitabilities, respectively. Large differences are observed within the 210 municipalities of the GGA since some of them have almost no A-ranked buildings whereas others comprise more than 70% of these buildings. It is shown that, by prioritizing the A-ranked buildings, almost 50% of the annual electricity consumption of the Geneva Canton could be produced by PV systems. Finally, the method developed here offers a decision-aiding tool that could be used at a territory scale to achieve energy transition goals in terms of solar PV deployment.

The achievement of the targets for reducing greenhouse gas emissions set by the Paris Agreements and the Swiss federal law on the reduction of greenhouse gas emissions (CO2 law) requires massive use of renewable energies, which cannot be achieved without their adoption by the general public. The solar cadaster developed as part of the INTERREG G2 Solar project is intended to assess the solar potential of buildings at the scale of Greater Geneva—for both industrial buildings and for individual residential buildings—at a resolution of 1 m. The new version of the solar cadaster is intended to assess the solar potential of roofs, as well as that of vertical facades. The study presented here aims to validate this new version through a comparison with results obtained with two other simulation tools that are widely used and validated by the scientific community. The good accordance with the results obtained with ENVI-met and DIVA-for-Rhino demonstrates the capability of the radiative model developed for the solar cadaster of Greater Geneva to accurately predict the radiation levels of building facades in configurations with randomly distributed buildings (horizontally or vertically).

The massive deployment of Photovoltaic (PV) energy in cities, which is expected in the coming years, brings new challenges when it comes to controlling power variations inherent to the impact of high PV penetration on the economy, energy exchanges and grid stability. In this perspective, self-consumption, which consists in consuming locally a part of the produced PV energy, allows to smooth the variations in the solar power production, and therefore reduce the stress on the grid. Among other strategies, self-consumption can be enhanced by the adequate use of all the surfaces of a building (roof and façades). In the present work, the optimization of the PV integration on the roof and façades of a building, is performed in order to optimize objectives related to selfconsumption. These objectives are based on different aspects of self-consumption: minimizing the exchanges of energy with the grid, improving grid stability, or maximizing the economic profitability. The case of France will be considered. The influence of different parameters, namely, the load profile, the building consumption and height, on the optimal integration of PV will be investigated. It is shown that the optimal PV integration is drastically impacted by the studied parameters, and the goal of the optimization. Furthermore, integration on façades appears to be most of the time relevant in order to enhance self-consumption.

The current climate and energy context is triggering the massive deployment of solar energy technologies in the short term. As a consequence, the number of Photovoltaic (PV) systems that will be set up in urban areas will drastically increase. Such large-scale integration must be guided by careful consideration of a diverse set of criteria, including energy resources and demand, as well as socioeconomic and environmental factors. In this paper, a decision aiding approach is introduced to rank a set of buildings based on their suitability to host photovoltaic systems in the particular case of urban environments. The study takes place in the context of a Franco-Swiss project covering the Grand Genève (Greater Geneva) agglomeration. A list of decision criteria is defined and the ELECTRE III outranking method is used to solve the problem and provide efficient ranking of the different solutions.

Authors would like to thanks the program INTERREG V Suisse-France for providing financial support to conduct this study in the framework of the project G2 Solar which aims at extending the solar cadaster to the Greater Geneva and intensify energy solar production at this level. We greatly acknowledge R. Giraudon at Urban Solar Energy, and B. Benchenafi at Reservoir Sun, for their helpful discussion and their expertise. We finally thank Manon Turban for her proofreading of the document.

The impact of the external thermal stratification on the flow behavior andthe mass flow rate in an open ended vertical channel with one side uniformlyheated is investigated experimentally and numerically. Both experimentaland numerical studies show that the increase of the external stratificationlowers the velocity and the mass flow rate but also displaces the transitionheight at a lower location in the channel. The numerical model was usedto study the cases of weak and negative thermal stratifications which arebarely achievable in non-controlled experimental laboratory conditions butare common in the atmosphere. Different flow regimes are identified with flowbeing fully laminar when the stratification is weak or negative and flow beingtransitional to turbulent for higher stratifications. Finally, the numericallyobtained mass flow rates with the various external thermal stratifications areshown to be in excellent agreement with a theoretical model developed in aprevious work.

A spatially developing transitional flow in a vertical channel with one side heated uniformly and subjected to random velocity fluctuations at theinlet is investigated in this experimental and numerical study. Two Rayleigh numbers are studied. Experimentally, Particle Image Velocimetry is used to obtain a complete two-dimensional velocity field of the streamwise flow development. A three-dimensional Large-Eddy-Simulation investigation isalso performed to obtain a complete streamwise evolution of the flow. The results allow the denition of three transition indicators on the basis of thetime-averaged velocities and temperatures elds as well as on the turbulent statistics of the flow. The detailed experimental and numerical spatial development of the transitional natural convective flow is then presented and the ability of the indicators to capture the early and the advanced stages of the transition is assessed. The numerical simulations were performed on the assumptions of a thermally stratied environment, submitted to an environmental noise, and for which wall to wall radiations were considered. These conditions aim at representing realistic experimental conditions.

Many works have been performed on heated vertical rectangular open-ended channels. Whilst in most cases, thermal fields are quite well predicted or reproducible, there were often large unexplained variations in the experimental flow rate for apparently the same conditions. An experimental and theoretical investigation has therefore been carried out to identify the effect of external thermal stratifications on the flow rate. Four values of steady and uniform heat flux, equivalent to Rayleigh numbers between 2.9×104 and 1.6×108 were imposed experimentally either on one or both sides of a vertical rectangular channel, with various ambient thermal gradients external to the channel. It was observed that the mass flow rate was significantly reduced as the positive upward, external thermal gradient increased. A theoretical model of the phenomenon was also developed. There is an excellent agreement between the theoretically predicted and experimentally measured mass flow rates. This clearly highlights that external temperature distributions are key driving factors and their influence is accurately quantified in this work.