Search Results (150)

To sustainably power future urban communities, cities require advanced solar energy planning tools that overcome the limitations of traditional approaches, such as data fragmentation and siloed decision-making. SDTs present a transformative opportunity by enabling precision urban modelling, integrated simulations, and iterative decision support. However, their application in solar energy planning remains underexplored. This study introduces SDT4Solar, a novel SDT-based framework designed to integrate city-scale rooftop solar planning through 3D building semantisation, solar modelling, and a unified geospatial database. By leveraging advanced spatial modelling and Internet of Things (IoT) technologies, SDT4Solar facilitates high-resolution 3D solar potential simulations, improving the accuracy and equity of solar infrastructure deployment. We demonstrate the framework through a proof-of-concept implementation in Ballarat East, Victoria, Australia, structured in four key stages: (a) spatial representation of the urban built environment, (b) integration of multi-source datasets into a unified geospatial database, (c) rooftop solar potential modelling using 3D simulation tools, and (d) dynamic visualization and analysis in a testbed environment. Results highlight SDT4Solar’s effectiveness in enabling data-driven, spatially explicit decision-making for rooftop PV deployment. This work advances the role of SDTs in urban energy transitions, demonstrating their potential to optimise efficiency in solar infrastructure planning. Full article

Evaluating the renewable energy potential, such as that of solar photovoltaics (PV), is important for developing renewable energy policies. This study investigated rooftop solar PV potential in Thailand based on open-source geographic information system (GIS) building footprints, solar PV power output, and the most recent land use data (2022). GIS-based overlay analysis, buffering, fishnet modeling, and spatial join operations were applied to assess rooftop availability across various building types, taking into account PV module installation parameters and optimal panel orientation. Economic feasibility and sensitivity analyses were conducted using standard economic metrics, including net present value (NPV), internal rate of return (IRR), payback period, and benefit–cost ratio (BCR). The findings showed a total rooftop solar PV power generation potential of 50.32 TWh/year, equivalent to 25.5% of Thailand’s total electricity demand in 2022. The Central region contributed the highest potential (19.59 TWh/year, 38.94%), followed by the Northeastern (10.49 TWh/year, 20.84%), Eastern (8.16 TWh/year, 16.22%), Northern (8.09 TWh/year, 16.09%), and Southern regions (3.99 TWh/year, 7.92%). Both commercial and industrial sectors reflect the financial viability of rooftop PV installations and significantly contribute to the overall energy output. These results demonstrate the importance of incorporating rooftop solar PV in renewable energy policy development in regions with similar data infrastructure, particularly the availability of detailed and standardized land use data for building type classification. Full article

Distributed photovoltaic (PV) generation is increasingly important for urban energy systems amid global climate change and the shift to renewable energy. Traditional PV deployment prioritizes maximizing energy output, often neglecting electricity price variability caused by time-of-use tariffs. This study develops a high-resolution planning and economic assessment model for building-integrated PV (BIPV) systems, incorporating hourly electricity real-time market prices, solar geometry, and submeter building spatial data. Wuhan (30.60° N, 114.05° E) serves as the case study to evaluate optimal PV placement and tilt angles on rooftops and façades, focusing on maximizing economic returns rather than energy production alone. The results indicate that adjusting rooftop PV tilt from a maximum generation angle (30°) to a maximum revenue angle (15°) slightly lowers generation but increases revenue, with west-facing orientations further improving returns by aligning output with peak electricity prices. For façades, south-facing panels yielded the highest output, while north-facing panels with tilt angles above 20° also showed significant potential. Façade PV systems demonstrated substantially higher generation potential—about 5 to 15 times that of rooftop PV systems under certain conditions. This model provides a spatially detailed, market-responsive framework supporting sustainable urban energy planning, quantifying economic and environmental benefits, and aligning with integrated approaches to urban sustainability. Full article

Accurate estimation of available rooftop areas for PV power generation at the city scale is critical for sustainable energy planning and policy development. In this study, using publicly available high-resolution satellite imagery, rooftop solar energy potential in urban, rural, and industrial areas is estimated using deep learning models. In order to identify roof areas, high-resolution open-source images were manually labeled, and the training dataset was trained with DeepLabv3+ architecture. The developed model performed roof area detection with high accuracy. Model outputs are integrated with a user-friendly interface for economic analysis such as cost, profitability, and amortization period. This interface automatically detects roof regions in the bird’s-eye -view images uploaded by users, calculates the total roof area, and classifies according to the potential of the area. The system, which is applied in 81 provinces of Turkey, provides sustainable energy projections such as PV installed capacity, installation cost, annual energy production, energy sales revenue, and amortization period depending on the panel type and region selection. This integrated system consists of a deep learning model that can extract the rooftop area with high accuracy and a user interface that automatically calculates all parameters related to PV installation for energy users. The results show that the DeepLabv3+ architecture and the Adam optimization algorithm provide superior performance in roof area estimation with accuracy between 67.21% and 99.27% and loss rates between 0.6% and 0.025%. Tests on 100 different regions yielded a maximum roof estimation accuracy IoU of 84.84% and an average of 77.11%. In the economic analysis, the amortization period reaches the lowest value of 4.5 years in high-density roof regions where polycrystalline panels are used, while this period increases up to 7.8 years for thin-film panels. In conclusion, this study presents an interactive user interface integrated with a deep learning model capable of high-accuracy rooftop area detection, enabling the assessment of sustainable PV energy potential at the city scale and easy economic analysis. This approach is a valuable tool for planning and decision support systems in the integration of renewable energy sources. Full article

Accurate assessment of urban rooftop solar photovoltaic (PV) potential is critical for the low-carbon energy transition. This study presents a deep learning-based approach using high-resolution (0.5 m) aerial imagery to automatically identify building rooftops in the central urban area of Wuhan, China (covering seven districts), and to estimate their PV installation potential. Two state-of-the-art semantic segmentation models (DeepLabv3+ and U-Net) were trained and evaluated on a local rooftop dataset; U-Net with a ResNet50 backbone achieved the best performance with an overall segmentation accuracy of ~94%. Using this optimized model, we extracted approximately 130 km² of suitable rooftop area, which could support an estimated 18.18 GW of PV capacity. These results demonstrate the effectiveness of deep learning for city-scale rooftop mapping and provide a data-driven basis for strategic planning of distributed PV installations to support carbon neutrality goals. The proposed framework can be generalized to facilitate large-scale solar energy assessments in other cities. Full article

To alleviate the impact of economic and environmental detriments caused by the increased demands of electric vehicle battery production and disposal, the use of spent batteries in second-life stationary applications such as energy storage for renewable sources or backup power systems, offers many benefits. This paper focuses on reducing the energy consumption cost and greenhouse gas emissions of Internet-of-Things-enabled campus microgrids by installing solar photovoltaic panels on rooftops alongside energy storage systems that leverage second-life batteries, a gas-fired campus power plant, and a wind turbine while considering the potential loads of a prosumer microgrid. A linear optimization problem is derived from the system by scheduling energy exchanges with the Ontario grid through net metering and solved by using Python 3.11. The aim of this work is to support Sustainable Development Goals, namely 7 (Affordable and Clean Energy), 11 (Sustainable Cities and Communities), 12 (Responsible Consumption and Production), and 13 (Climate Action). A comparison between a base case scenario and the results achieved with the proposed scenarios shows a significant reduction in electricity cost and greenhouse gas emissions and an increase in self-consumption rate and renewable fraction. This research work provides valuable insights and guidelines to policymakers. Full article

Understanding temperature variations within the complex urban canopy layer (UCL) is challenging due to limitations and discrepancies between temperature measurements taken in urban canyons and on rooftops. The key question is how much these measurements differ and what factors contribute to these differences. According to the guidance by the World Meteorological Organization (WMO), rooftop observations are not encouraged for urban monitoring, due to potentially anomalous microclimatic conditions, whereas measurements within urban canyons are recommended. This is particularly relevant given the increasing number of rooftop sensors deployed through citizen science, raising questions about the representativeness of such data. This study aimed to address this knowledge gap by comparing temperatures within the UCL using two sensors: one located on a rooftop, and the other positioned within the canyon. The temperature difference between these two nearby locations followed a clear diurnal cycle, peaking at over 1 °C between 12:00 and 16:00 local time, with the canyon warmer than the rooftop. This daytime warming was primarily driven by solar radiation and, to a lesser extent, by wind speed, but only under clear-sky conditions. During the rest of the day, the temperature difference remained negligible. Full article

With the rapid development of science and technology, the global demand for renewable energy is increasing. In the urban context, solar energy has become one of the key ways to increase urban energy self-sufficiency and reduce carbon emissions due to its flexibility in installation and ease of expansion of applications. Therefore, based on Geographic Information System (GIS) and deep learning modeling, this paper proposes a method to efficiently assess the potential of urban rooftop solar photovoltaic (PV), which is analyzed in a typical area of Lanzhou New District, which is divided into 8774 units with an area of 87.74 km². The results show that the method has a high accuracy for the identification of the roof area, with a maximum maxF_β of 0.889. The annual solar PV potential of industrial and residential buildings reached 293.602 GWh and 223.198 GWh, respectively, by using the PV panel simulation filling method for the calculation of the area of roofs where the PV panels can be installed. Furthermore, the rooftop PV potential of the industrial buildings in the research area provided can cover 75.17% of the industrial electricity consumption. This approach can provide scientific guidance and data support for regional solar PV planning, which should prioritize the development of solar potential of industrial buildings in the actual consideration of rooftop PV deployment planning. Full article

The transition to renewable energy is critical to enhance Puerto Rico’s energy resilience and reduce dependence on imported fossil fuels. Rooftop photovoltaic (PV) systems provide a scalable opportunity to meet these objectives. This study evaluates the potential of rooftop PV systems across Puerto Rico using the National Renewable Energy Laboratory’s (NREL) PV Rooftop Database, processing detailed roof surface data to estimate installed capacity, energy generation, Levelized Cost of Electricity (LCOE), and solar resource potential at municipal and barrio levels. Findings reveal high solar rooftop capacity in urban neighborhoods, with areas like Sabana Abajo and Hato Tejas each exceeding 450 GWh/year in potential generation. Solar rooftop resource values peak at 3.67 kWh/kW in coastal areas, with LCOE values (0.071–0.215 USD/kWh) below current electricity rates. All municipalities demonstrate technical potential to meet their electricity demand with rooftop PV system alone. This research contributes through (1) developing Puerto Rico’s first comprehensive solar rooftop potential map; (2) providing unprecedented barrio-level analysis; (3) introducing a methodology for estimating missing post-disaster consumption data; and (4) integrating technical, economic, and equity indicators to inform energy policy. These findings demonstrate the importance of rooftop solar in achieving renewable energy goals and provide an understanding of spatial energy inequalities. Full article

In Taiwan, large advertising billboards on commercial buildings consume significant energy, exacerbating environmental challenges and straining sustainability efforts. This study explores the potential of rooftop solar photovoltaic systems (SPVS) to power these billboards, offering a dual solution for energy reduction and financial viability. Using a fuzzy nonlinear multi-objective programming approach, the research demonstrates that SPVS investments become profitable by the ninth year (0.7232% return), rising to 5.4463% by the twentieth year, while a 26-day reduction in construction time cuts carbon emissions by 223.11 kg. The innovative Revenue–Time–Cost–Quality–Carbon Emissions (RTCQCE) framework balances economic gains with environmental benefits, leveraging advertising revenue to fund SPVS. This model bridges a research gap by integrating financial and ecological factors, providing a practical tool for sustainable urban development in Taiwan. Full article

This extensive study examines the solar rooftop photovoltaic potential (RTP) over polluted cities in major geographic and economic zones of India. The study examines the climatology of solar radiation attenuation due to aerosol, clouds, architectural effects, etc. The study exploits earth observations from ground, satellite, and radiative transfer modeling (RTM) in conjunction with geographic information systems tools. The study exploits long-term observations of cloud properties from the Meteosat Second Generation (MSG) satellites operated by EUMETSAT and aerosol properties data gathered from ground-based measurements provided by AERONET. The innovation in the study is defined in two steps. Firstly, we estimated the RTP using the current state of the art in the field, which involved using suitability factors and energy output based on the PVGIS simulations and extrapolating these for effective rooftop areas of the cities. Secondly, we advanced beyond the current state of the art by incorporating roof morphological characteristics and various area share factors to assess the RTP in more realistic terms. These two steps were applied under two different scenarios. The study determined that the optimum tilt angle is equal to the cities’ latitude for installing solar PV systems. In addition, the research emphasizes the advantages for the environment while offering energy and economic losses. According to our findings, the RTP in the rural city examined in this study is 31% greater than the urban city of India under both scenarios. The research has found that the metropolitan city, which boasts a maximum rooftop area of approximately 167 km², could host a significant RTP of around 13,005 ± 1210.71 (6970 ± 751.38) MWh per year under scenario 1 (scenario 2). Overall, solar radiation losses due to aerosol effects dominate radiation losses due to cloud effects on the city scale. Amongst all polluted cities, estimated financial losses due to aerosols, clouds, and shadows are 11,241.70 million, 4439 million, and 1167.65 million rupees, respectively. Our findings emphasize the necessity of accounting for air pollution for accurate solar potential assessments in thoughtful city planning. The creative approach that utilizes publicly available data establishes a strong foundation for penetrating solar photovoltaic (PV) technology into society. This integration could significantly contribute to climate change mitigation and adaptation efforts, promoting environmentally sustainable urban development and prevention strategies. Full article

Urban soiling, consisting of dust, industrial byproducts, and other pollutants, presents a significant risk to the effectiveness and safety of solar energy systems. To achieve the goal of net zero, having renewable energy systems such as solar panels in urban environments can help. This review will examine the composition and variety of urban soiling and evaluate its impact on PV installation. The study will analyze the efficiency loss attributable to soiling, focusing on its impact on small-scale installations such as rooftops, building integrated photovoltaics (BIPVs), and large-scale urban solar installations. Furthermore, this study will also investigate various developing technologies and strategies to reduce the effects of urban soiling. This encompasses the examination of automated cleaning systems and robotic maintenance, with a specific focus on their potential effectiveness. This review aims to underline the importance of addressing urban soiling within the framework of sustainable urban development and the expansion of solar energy, with further research into the development of soiling mitigation technologies. Finally, soil management and further research gaps will be discussed. Full article

An increasing trend towards the installation of photovoltaic (PV) solar energy generation capacity is driven by several factors including the desire for greater energy independence and, especially, the desire to decarbonize industrial economies. While large ‘solar farms’ can be installed in relatively open areas, urban environments also offer scope for significant energy generation, although the heterogeneous nature of the surface of the urban fabric complicates the task of forming an area-wide view of this potential. In this study, we investigate the potential offered by publicly available airborne LiDAR data, augmented using data from OpenStreetMap (OSM), to estimate rooftop PV generation capacities from individual buildings and regionalized across an entire small city. We focus on the island of Tromsøya in the city of Tromsø, Norway, which is located north (69.6° N) of the Arctic Circle, covers about 13.8 km², and has a population of approximately 42,800. A total of 16,377 buildings were analyzed. Local PV generation potential was estimated between 120 and 180 kWh m⁻² per year for suitable roof areas, with a total estimated generation potential of approximately 200 GWh per year, or approximately 30% of the city’s current total consumption. Regional averages within the city show significant variations in potential energy generation, highlighting the importance of roof orientation and building density, and suggesting that rooftop PV could play a much more substantial role in local energy supply than is commonly assumed at such high latitudes. The analysis method developed here is rapid, relatively simple, and easily adaptable to other locations. Full article

Rooftop photovoltaics (RPVs) are crucial in addressing energy shortages and environmental concerns caused by fossil fuel combustion. To promote the optimal deployment of RPVs in Tianjin, a region with abundant solar resources and dense buildings, this study proposes a framework that integrates building vector data with a deep learning model to extract currently installed RPVs from remote sensing images, and further estimate the development potential of RPVs. A total of 86,363 RPV polygons were extracted, covering an area of 10.34 km². More than 70% of these RPVs are concentrated on large and low-rise buildings, and a similar proportion is found in industrial buildings, as these buildings offer favorable installation conditions. Combining solar radiation and construction land development planning, we further determined the potential deployment zone of RPVs covering about 13% of the Tianjin’s land area, which represents 31.31 TWh per year of power generation potential. In the future, it is recommended to prioritize RPV installation on large and low-rise buildings or industrial buildings in the potential deployment zone, which could provide higher power generation and contribute significantly to environmental emission reduction goals. The proposed research framework can also be applied to other cities. Full article

This review article discusses the performance evaluation and integration strategies for solar façades, focusing on photovoltaic (PV) façades in diverse climatic conditions. It examines recent technology developments and methodologies for performance assessment, highlighting the potential of solar façades to enhance energy performance through on-site electricity generation. This study offers novel insights into the economic viability of façade-mounted photovoltaics, highlighting their potential in urban areas with constrained rooftop availability. Additionally, it emphasizes their distinct advantages in cold climates, such as reduced maintenance requirements and extended operational lifespans. Additionally, it addresses challenges such as technical complexity, esthetic considerations, and market awareness, emphasizing the balance between efficiency and design. Novel findings underscore the promise of advanced materials like perovskites in improving the flexibility and performance, as well as strategies to optimize BIPV integration in different climate zones. For stakeholders, this research highlights the importance of supportive policies and innovative solutions to overcome barriers, while offering researchers valuable perspectives on the advancement of solar façades toward zero-energy and zero-carbon building targets. Full article