Solar Energy Planning Research Articles

Exploring the climatic conditions effect on spatial urban photovoltaic systems development using a spatial multi-criteria decision analysis: A multi-city analysis

Identifying suitable locations for urban photovoltaic systems (UPVS) is crucial for achieving sustainable energy objectives and designing smart, eco-friendly cities. This study assesses the potential for UPVS expansion in eight cities across different climatic zones in Iran using a spatial multi-criteria decision-making method. Two scenarios were analyzed: the first compared spatial potential within each city, and the second compared potential between cities. The findings indicate that rooftops of the tallest buildings in densely populated areas, especially those with high solar energy output and sky view factor, hold the greatest potential for UPVS development. These locations are often near parks, commercial centers, and road networks. In the first scenario, Ardabil (5.70%), Gorgan (4.65%), Mashhad (5.46%), Tehran (8.10%), Kermanshah (5.76%), Shahrekord (3.41%), Kerman (8.67%), and Zahedan (8.56%) show significant potential for photovoltaic development. In the second scenario, cities in hot, dry climates like Zahedan and Kerman exhibit greater potential compared to cities in moderate, humid climates like Ardabil and Gorgan. Based on the analysis of this scenario, Ardabil (0.04%), Gorgan (1.49%), Mashhad (5.58%), Tehran (5.06%), Kermanshah (0.00%), Shaherkord (0.03%), Kerman (21.70%) and Zahedan (39.11%) showed a very high potential for UPVS development. The results of this study offer valuable insights for urban solar energy planning.

Examining effects of air pollution on photovoltaic systems via interpretable random forest model

Renewable energy plays a vital role in power generation and solar photovoltaic systems due to resource availability throughout the year. This work aims to investigate the impact of air pollutants and meteorological parameters on the performance of the photovoltaic systems locally, taking into consideration the advantages of the photovoltaic power potential of the SW part of Romania, where Craiova is located (average solar radiation intensity >1350 kWh/m2/year). This study is based on a one-year dataset provided by a sensor that monitors particulate matter concentrations, volatile organic compounds, dioxide of carbon, ozone, noise, formaldehyde and three climate parameters (temperature, pressure, and relative humidity). The research methodology applies an innovative interpretable random forest model emphasising the implications of air pollution for photovoltaic systems. The proposed machine learning model was trained to predict the particulate matter level in air based on the basic environmental variable measurements. The study presents six random forest models of varying complexity, which reach the accuracy of classification for the selected problem up to 99 %, and applies the Shapley Additive Explanations technique to interpret the decision-making model. The observation regarding the highest concentration of particulate matter occurring during cold months, which typically do not align with peak solar irradiance, underscores the importance of considering various environmental factors in solar energy planning. With its practical implications, this insight offers decision-makers valuable information about the feasibility of optimising solar energy generation despite seasonal variations in air pollution levels, directly addressing their needs and concerns.

Stakeholders' awareness of urban form effects on rooftop solar photovoltaic in Ghana: Implications for integrated solar energy and urban planning

Integrating solar energy considerations into urban planning practices, a socio-technical and multi-stakeholder approach known as solar urban planning, is essential for maximizing solar photovoltaic (PV) potential in the built environment. While the need for such an approach is articulated in solar energy studies and urban planning, very few research explore the extent to which key stakeholders critical to this process are aware of the connections between urban form and rooftop solar PV and its implication for solar urban planning. This study examines stakeholders' awareness of the effects of selected urban form attributes on residential rooftop solar PV and its implications for solar urban planning in Ghana. Primary data were collected using surveys and interviews of households, real estate developers, licensed solar home system (SHS) installation companies, and government agencies responsible for energy and urban planning. SHS installation companies affirmed that buildings' roof type and shape, roofing material, the height of neighboring buildings, and the trees' position significantly affect rooftop solar PV installation and performance in Ghana. However, households have a low awareness of how these urban form attributes affect rooftop solar PV. Despite the affirmed effects of urban form on rooftop PV, current planning legislations do not necessitate considering such systems in preparing urban and building plans. A robust institutional collaboration is necessary among urban planning authorities, energy regulators, and real estate developers to develop effective strategies for solar urban planning in Ghana.

Scenario and Policies of the Energy Planning: Solar Energy and Territorial Planning Needs

O aumento do consumo de energia elétrica na sociedade é constante. O homem torna-se cada vez mais dependente de eletroeletrônicos além disso, o mundo enfrenta um quadro de mudanças climáticas que afetam o desempenho rentável das hidrelétricas, principal fonte de energia elétrica do Brasil, enfatizando a necessidade de buscar outra fonte de energia renovável, como a energia solar. Para promover um ambiente que impulsione a melhor eficiência deste tipo de energia, torna-se essencial o planejamento territorial das cidades e estados brasileiros pautado em políticas públicas específicas. Este trabalho tem como objetivo avaliar a implementação do planejamento energético nas políticas públicas brasileiras. Através de pesquisa quali-quantitativa, realizou-se primeiramente o levantamento de dados de irradiação solar no território brasileiro, enfatizando o Estado de Santa Catarina e de investimentos no setor fotovoltaico realizados na área de estudo, desenvolveu-se uma análise sobre a Lei de Ordenamento Territorial do Município de Joinville, SC. Desta forma, concluiu-se que o país ainda não apresenta planos ou políticas eficientes que preparem o desenho urbano das cidades para otimizar a geração eficiente de energia solar.

Effect of adjusting orientation for solar energy applications in multiple climatic zones

South-facing collectors are the optimum choice for solar applications in the northern hemisphere. However, obstacles may limit the feasibility of this orientation. Therefore, altering the orientation of the collector impacts solar insolation. In this study, the Perez model is utilized to evaluate incoming solar radiation on tilted surfaces for solar collectors in four climatic zones across Pakistan. The results are presented in contour plots to analyze the optimal tilt and orientation for solar applications. The findings of the study indicate substantial energy gains when collectors are placed at optimum angles. More specifically, Quetta leads with a 14.54% increase, followed by Karachi and Multan at 9.81% and 9.3%, respectively, compared to horizontally placed collectors. Analysis of vertical surfaces reveals a notable decrease in monthly solar radiation, especially in Peshawar (37.22%). Monthly adjustments in tilt angles outperform fixed positions, enhancing solar energy intensity. When comparing yearly adjustments with monthly adjustments, Quetta shows the maximum increase of 5.92%, followed by Karachi (4.86%), Multan (4.01%), and Peshawar (3.65%). It is also observed that ±15° azimuth angle change from the south ensures receiving up to 98% of insolation, regardless of the climatic region. Lastly, the validation against the NASA SSE database further highlights the reliability of our simulation model. Overall, the outcomes of the study will contribute to informed solar energy planning in the studied regions.

Multicriteria Decision-Making Approach for Optimum Site Selection for Off-Grid Solar Photovoltaic Microgrids in Mozambique

Given the constraints associated with grid expansion costs, limited access to reliable electricity, and priorities in addressing the climate agenda and Sustainable Development Goals in low-income countries, microgrids and off-grid solar projects represent a viable solution for rural electrification. This type of solution has the advantage of being less expensive than conventional technologies, is rapidly scalable, affordable, environmentally sustainable, and can play a critical role in empowering rural communities. In this context, this study proposed a spatial framework for off-grid solar energy planning based on a Geographical Information System and Boolean logic, Fuzzy logic, and Analytic Hierarchy Process Multicriteria Decision-Making methods. The results of the applied methodology show that the selection of optimal locations for off-grid solar photovoltaic microgrid projects in Mozambique is significantly influenced by the following order of criteria: climatology, orography, technical and location, social, and institutional criteria. Geographically, about 49% or 344,664.36 km2 of the total study area is initially suitable for an off-grid solar photovoltaic microgrid project; 4% is low suitable, 14% is moderately suitable, 18% is suitable, and 13% is highly suitable. However, 51% of the ranked areas fall into the not feasible and restricted areas, mainly in conservation areas, protected areas, and areas at high risk of flooding and cyclones, covering a total of 387,005.5 km2 within the study area. In general, the approach helps to reduce uncertainty and increase flexibility to identify appropriate sites and strengthen indicators of sustainable development impacts of decentralized rural electrification.

A method for global potential assessment of roof integrated two-stage solar concentrators (TSSCs) at district scale

This paper proposes a core method for integrating two-stage solar concentrators (TSSCs) as roof-integrated energy supply systems at the district scale. However, the performance of these systems not only depends on good configurations but also on optimal building typologies. The design process of buildings-integrated TSSCs on a district scale reflects a complex multi-criteria problem, where several conflicting concerns from multiple stakeholders need to be addressed. Thus, the proposed method aims to support the multi-criteria decision-making process in the early-stage design of sustainable districts utilizing TSSC technology. The method contributes to the design of the TSSCs relative to district designs. Our method enables design generation according to a set of decision variables related to the district (roof type and slope, orientation, building height, width, and length), and TSSC (type, geometric ratio, separation distance between mirrors, modules number, and solar cell size). The method uses a parametric modeling approach combined with a multi-objective optimization algorithm (NSGA-II) that enables design optimization of the district and TSSCs in two consecutive steps. The two-step design optimization allows finding optimal district designs for maximizing cumulative direct normal irradiance (DNI) and minimizing the total energy demand, and TSSC designs for maximizing average monthly load match index (av.LMI) (a ratio of energy yield to demand) and minimizing the average covered roof area occupied by modules. We validated the proposed method in an illustrative case study of ‘Buckower Felder’, a district in the city of Berlin (Germany). The illustrative application shows that our method enables the performance-driven, generative design of both; district and building-integrated TSSCs and searches for the most appropriate solutions i.e., urban designs for maximum DNI and minimum demand, and TSSC designs for maximum av.LMI and minimum covered roof area. Results indicate that there is a trade-off between objectives, where district design with high DNI (>4500 kW/m2/h/month) reflects high energy demand (8.6e + 05 kWh/month). Similarly, TSSC designs ensuring high av.LMI (>1.0) require a large roof area (>47 %). Given these trade-offs, the method can meaningfully support the decision-making process. Thus, the method allows for large-scale integration of TSSCs with buildings at an urban scale and supports solar energy planning and energy transition policies for sustainable districts.

Assessing the potential and utilization of solar energy at the building-scale in Shanghai

The assessment of potential and utilization of solar energy for each building has become an essential precondition of urban sustainable development. Currently, there are two challenges, namely high computation cost for an assessment within a large city and missing rooftop information for each building. In this study, by taking the downtown area in Shanghai as sample, a grid scheme with buffer was proposed to alleviate the computational burden and successfully estimate solar radiation with an accuracy of 0.91. Also, a quadrant-based segmentation method was developed to classify rooftop types with an overall accuracy of 83.63%, which helps better calculate solar energy utilization cost. Finally, we assumed PhotoVoltaic conversion (PV) systems or Domestic Solar Water Heater (DSWH) systems are installed on all suitable rooftops and analyzed their utilization cost, as well as economic and ecological benefits. The results show that 165,529 and 52,131 buildings are suitable for PV and DSWH systems, respectively. PV system's average payback time is about five years with reducing standard coal consumption of 1.85 × 1011kg. The DSWH system requires three more years to balance the cost and benefits. The criteria of further solar energy planning are also concluded from three perspectives: building height and density, and rooftop structure.

Estimating surface solar irradiance from geostationary Himawari-8 over Australia: A physics-based method with calibration

Surface Solar Irradiance (SSI) is required for solar energy planning and adoption, and is a fundamental parameter in modelling weather, climate, ecosystem and agricultural activities. Herein a time series based radiative transfer model was developed to simultaneously retrieve properties of clouds, aerosols and surface albedo, which were in turn used to calculate the components of SSI: i.e., global, direct and diffuse irradiance. The calculated results were calibrated across the Australian continent against in-situ measurements to account for minor factors (e.g., water vapor) not considered by the physics-based method. Detailed validation of the SSI components was performed against three years of in-situ measurements at 11 sites across Australia, at a range of time scales (i.e., instantaneous, hourly, daily and monthly) and under both all-sky and cloudy-sky conditions. The main advantage of the present method is the reliable separation of the direct and diffuse components with consistently low biases (~4 W/m2) at all four time scales, while still maintaining relatively low RMSE (root-mean-square-error) and MAE (mean-absolute-error). Once calibration has been performed the model does not require any ancillary data when implemented operationally: that is the model only requires geostationary satellite data. This model may be implemented across the globe using widely available next generation geostationary satellite data with a handful of ground-data for calibration.

Combined Engineering—Statistical Method for Assessing Solar Photovoltaic Potential on Residential Rooftops: Case of Laghouat in Central Southern Algeria

Solar energy planning becomes crucial to develop adaptive policies ensuring both energy efficiency and climate change mitigation. Cities, particularly building’s rooftops, constitute a promising infrastructure for enabling the use of locale solar resources. This study proposes a combined engineering–statistical methodology to assess the photovoltaic potential of residential rooftops. Using validated algorithms for solar simulation and geographical information system (GIS) for spatial dissemination, the proposed methodology deals with the lack of data and allows an accurate investigation of the geographical and technical potential. Applied to the municipality of Laghouat, the results reveal that suitable rooftops areas for PV installations in the examined typologies were approximately between 18 and 35%. Moreover, the deployment of distributed PV systems on residential rooftops provides significant technical potential, which could cover up to 55% of the annual electricity needs. These original findings offer a realistic assessment of the usable solar potential within municipalities, which helps decision-makers establish energy efficiency strategies by reducing energy consumption and increasing the share of renewable electricity production. Additionally, the discussion offers valuable insight into energy management and investigates eventual energy sharing among residential buildings to achieve a net-zero energy balance at the municipal level.

The use of LiDAR versus unmanned aerial systems (UAS) to assess rooftop solar energy potential

Remotely sensed data provide many opportunities for enhancing our understanding of the built and natural environment. Representations of the urban landscape from light detection and ranging (LiDAR) sensors and digital orthophotography from unmanned aerial systems (UAS) are quickly becoming essential for examining and maintaining infrastructure systems, estimating risk from extreme events, and improving urban sustainability. This includes community efforts toward energy resilience and the development of alternative energy systems, such as solar and wind. While LiDAR provides the means to model key characteristics of the urban landscape for solar energy planning, including slope, aspect and elevation, issues of spatial uncertainty and error persist in LiDAR data and have the potential to reduce the fidelity of solar energy assessments. In this paper, we use extremely high-resolution UAS data to improve solar energy audits and mitigate uncertainties associated with LiDAR data. The results suggest improvements in aggregate irradiation estimates by as much as 36 % when using digital orthophotos from a UAS when compared to LiDAR. This paper concludes with a detailed discussion of potential strategies for improving solar energy estimates for both researchers and practitioners.

An innovative approach to local solar energy planning in Riva Trigoso, Italy

This paper aims at introducing an approach for improving the renewable sources technologies inclusion in the municipality planning process and calls to revisit the current governance to strengthen the implementation effectiveness. The solar energy potential and the local energy requirements of the city of Riva Trigoso are analyzed and two types of solar technologies are tested. An analytical methodology based on the exposition of the buildings present in the considered location is developed. The method allows to identify the areas where it is more convenient to invest and the specific technology to be used. The effectiveness of the optimization method is validated via comparison with random allocation of the same total surface of panels. The results have been translated into GIS maps where the municipality can identify the areas at best solar energy potential and the more suitable technology. The proposed approach can be used for any location and it allows to define detailed scenarios for local energy planning processes.

Economic analysis of solar energy development in North Africa

The economic analysis of solar energy development is the basis of promoting the solar energy planning in north Africa and realizing the clean energy power transmission among continents. In this paper, the cost development trend of photovoltaic(PV) power and concentrating solar power(CSP) generation is analyzed, and the levelized cost of energy (LCOE) of solar power generation is forecasted. Then, taking the development of Tunisian solar energy as an example in the context of transcontinental transmission, PV power with energy storage and PV-CSP power generation are given as two kinds of development plan respectively. The installed capacity configurations of the two schemes are given with production simulation method, and comprehensive LCOE are calculated. The studies show that based on the LCOE forecast value, the LCOE of PV-CSP combined power generation will decrease when the annual utilization hours of transmission channel is increased. It can be chosen as one of important mode of the North Africa solar energy development.

Earth-Observation-Based Estimation and Forecasting of Particulate Matter Impact on Solar Energy in Egypt

This study estimates the impact of dust aerosols on surface solar radiation and solar energy in Egypt based on Earth Observation (EO) related techniques. For this purpose, we exploited the synergy of monthly mean and daily post processed satellite remote sensing observations from the MODerate resolution Imaging Spectroradiometer (MODIS), radiative transfer model (RTM) simulations utilizing machine learning, in conjunction with 1-day forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). As cloudy conditions in this region are rare, aerosols in particular dust, are the most common sources of solar irradiance attenuation, causing performance issues in the photovoltaic (PV) and concentrated solar power (CSP) plant installations. The proposed EO-based methodology is based on the solar energy nowcasting system (SENSE) that quantifies the impact of aerosol and dust on solar energy potential by using the aerosol optical depth (AOD) in terms of climatological values and day-to-day monitoring and forecasting variability from MODIS and CAMS, respectively. The forecast accuracy was evaluated at various locations in Egypt with substantial PV and CSP capacity installed and found to be within 5–12% of that obtained from the satellite observations, highlighting the ability to use such modelling approaches for solar energy management and planning (M&P). Particulate matter resulted in attenuation by up to 64–107 kWh/m2 for global horizontal irradiance (GHI) and 192–329 kWh/m2 for direct normal irradiance (DNI) annually. This energy reduction is climatologically distributed between 0.7% and 12.9% in GHI and 2.9% to 41% in DNI with the maximum values observed in spring following the frequent dust activity of Khamaseen. Under extreme dust conditions the AOD is able to exceed 3.5 resulting in daily energy losses of more than 4 kWh/m2 for a 10 MW system. Such reductions are able to cause financial losses that exceed the daily revenue values. This work aims to show EO capabilities and techniques to be incorporated and utilized in solar energy studies and applications in sun-privileged locations with permanent aerosol sources such as Egypt.

Assessing visibility in multi-scale urban planning: A contribution to a method enhancing social acceptability of solar energy in cities

Urban areas are facing a growing deployment of solar photovoltaic and thermal technologies on building envelopes, both on roofs and on façades. An effective solar energy planning process considers social acceptance, in relation to the landscape alteration induced by the solar modules. “Visual impact” is often considered as a major component of social acceptance but comprehensive visibility assessment models are lacking at the scale of the city. This paper presents a scale-dependent methodology to assess the visibility of building envelope surfaces exposed to solar radiation, which could host solar modules, in urban areas. A match between annual solar radiation, visibility and socio-cultural sensitivity of the built environment are proposed in a multi-criteria decision framework.Results are illustrated for the city of Geneva (Switzerland), as a case study: a partial overlap between highly sensitive urban areas and high visual interest is identified at the broad, strategic planning scale. In a second more detailed phase, a frequency breakdown of buildings is provided, according to the (non-) visible share of useful roof area for solar energy production. Less visible roofs are more likely to be situated in courtyards, far from the streets, in deep urban canyons or on low-pitched roofs. The outcomes indicate that stakeholders can reasonably expect to harvest a serious amount of solar energy by means of building integrated solar systems without crucially affecting public perception. In Geneva, more than 50 m2/building of non-visible roof surface receiving sufficient solar radiation for an economically viable solar refurbishment is available over half of the buildings.This method is valuable for large districts or cities (i) to spot more/less visible building sets and to estimate adapted precinct refurbishment strategies; (ii) to compare visibility on a common conventional basis and to detect zones deserving further investigations at the finer scale.

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.

AOT Retrieval Procedure for Distributed Measurements With Low‐Cost Sun Photometers

AbstractWe propose a new application of inexpensive light‐emitting diode (LED)‐based Sun photometers, consisting of measuring the aerosol optical thickness (AOT) with high resolution within metropolitan scales. Previously, these instruments have been used at continental scales by the GLOBE program, but this extension is already covered by more expensive and higher‐precision instruments of the AERONET global network. For this we built an open source two‐channeled LED‐based Sun photometer based on previous developments, with improvements in the hardware, software, and modifications on the calibration procedure. Among these we highlight the use of MODTRAN to characterize the effect introduced by using LED sensors in the AOT retrieval, an open design available for the scientific community and a calibration procedure that takes advantage of a CIMEL Sun photometer located within the city, enables the intercomparison of several LED Sun photometers with a common reference. We estimated the root‐mean‐square error in the AOT retrieved by the prototypes as 0.006 at the 564 nm and 0.009 at the 408 nm. This error is way under the magnitude of the AOT daily cycle variability measured by us in our campaigns, even for distances closer than 15 km. In addition to inner city campaigns, we also show aerosol‐tracing applications by measuring AOT variations from the city of Santiago to the Andes glaciers. Measuring AOT at high spatial resolution in urban areas can improve our understanding of urban scale aerosol circulation, providing information for solar energy planning, health policies, and climatological studies, among others.

Study of inter-correlations of solar radiation, wind speed and precipitation under the influence of El Niño Southern Oscillation (ENSO) in California

Abstract El Nino Southern Oscillation (ENSO) is recognized as an influential climate pattern on meteorological variables such as global solar radiation (H), wind speed (V) and precipitation (P). California as one of the leading States in increasing renewable energy utilization, having established a Renewables Portfolios to meet its electricity demand from renewable energy resources. In this study, long-term 50 years datasets (1961–2010) of eight locations representing different climate conditions of California are utilized. The main objective of this work is to investigate the sensitivity of H, V and P and their variation to El Nino events (very strong and strong El Nino) and La Nina events (strong and moderate La Nino) in different regions of California. The results showed distinct impacts of El Nino and La Nina events on the magnitude and distribution of the studied meteorological variables. The impact of ENSO events on these variables are found to be geographically and seasonally dependent. Furthermore, the degree to which the variables link to ENSO depends on intensity of the events. Overall, the results suggest that ENSO is a potentially useful prognostic tool for California solar and wind energy and hydropower planning for upcoming events.

Putting solar energy on the urban map: a new GIS-based approach for dwellings

This paper describes some aspects of prototype software designed to assist local authority planners and energy advisers in their efforts to increase the uptake of solar hot water systems in cities. To estimate the potential yield from installed systems, the Solar Energy Planning system implements an adaptation of the method for calculating the thermal performance of solar heating systems for domestic hot water in BS5918. A much-enhanced version of the BREDEM-8 domestic energy model provides the basis for predicting the delivered energy savings. Reductions in CO 2 emissions can also be quantified. A trial of the prototype in an urban area of Leicester, UK, is illustrated and some encouraging results are reported.

Irradiation mapping of complex urban environments: an image-based approach

This paper describes a novel approach for evaluating the total annual/monthly irradiation incident on building facades in urban settings. The analysis is founded on a physically-based rendering approach and uses data-visualisation techniques to generate ‘maps’ (i.e. false-colour images) of annual/monthly irradiation. The irradiation ‘maps’ are derived from hourly time-series data for 1 year and take accurate account of shading by, and inter-reflection from, other buildings and surfaces. The sun and sky irradiation images are evaluated separately. The sky contribution is calculated using realistic, non-isotropic models for the sky radiance distribution. The ‘maps’ can be used to confidently identify facade-locations where there is high irradiation, for example to aid the siting of photovoltaic (PV) panels. The technique can be applied to scenes of arbitrary complexity from a single building to fully ‘worked-up’ city models. The results of the analysis have been linked to a geographical information system (GIS)-based solar energy planning system. The system is targeted at city planners and one of its aims is to encourage the consideration of solar energy in the urban planning process.