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Energy efficiency, sustainability, and renewable energy sources are becoming increasingly relevant topics in today's world. Buildings are one of the largest consumers of energy in society, and as such, improving their energy efficiency by reducing unnecessary energy loss and utilizing solar power is crucial. This paper comprehensively analyzes a neighborhood with buildings characteristic of the researched area by applying empirical and theoretical methods and calculations that have been proven in numerous individual cases. The main contribution of this paper is its demonstration that implementing methods to increase the energy efficiency of buildings and utilizing the potential of solar power can result in significant savings in energy consumption, increase the energy sustainability of the analyzed buildings, and substantially reduce the negative environmental impact. The novelty of this study lies in the location and multiple software applications for data analysis. The data and conclusions obtained in this paper serve as a foundation and path towards sustainable development in the field of energy efficiency for buildings in this and similar areas. Heat loss was calculated by analyzing households in the urban neighborhood of Nova Kolonija. All analyzed houses exceeded the maximum allowed annual required energy for household heating (75 kWh/m2). After the reconstruction and implementation of the proposed measures to increase energy efficiency, all houses met the requirements and entered a higher energy class, C. Energy for heating was reduced from 9294.68 kWh/a to 4641.84 kWh/a, representing a reduction of 50.03%. Simulations were conducted regarding solar rooftop power plant installation of 5655 Wp capacity. Software that was used included: a Photovoltaic Geographical Information System (PVGIS), Photovoltaic System software (PVsyst 7.3.), and Photovoltaic Design and Simulation software (PV*SOL). The results of the analysis indicated that the average amount of electricity produced is 6186.98 kWh, which meets 98.12% of households' annual electricity consumption of 6278.41 kWh. The paper contributes to the existing body of literature and provides significant insight for both practical implications and future studies. [ABSTRACT FROM AUTHOR]

• Plot ratio, building density, building floor and perimeter shape factor are the four key factors. • Key factors should be considered carefully when studying solar potential and photovoltaic. • Location, amount and transparency of photovoltaic are optimized by Genetic Algorithm. • The minimum payback period and maximum power generation of photovoltaic were optimized. The relationship between solar potential on building façade and urban morphology at urban scale remains unclear, and the design of façade integrated photovoltaic (FIPV) lacks evidence. This study investigates high-rise, high-density commercial districts in Hong Kong (HK), using Random Forest algorithm combined with the SHapley Additive exPlanations method to assess the importance of urban morphology on solar irradiance on building facades. The results indicate that plot ratio, building floor, building density, and perimeter shape factor are the four key parameters influencing solar irradiance, with the importance rate and contribution value of the four parameters reach 43.9 % and 48.7 %, respectively. Based on these parameters and actual urban blocks in HK, typical urban typologies were constructed. Four scenarios were generated with plot ratio as the control parameter. The positions, amounts, and transparency of PV glass on the south and east facades were optimized to minimize the payback period and maximize power generation, using Non-dominated Sorting Genetic Algorithm II algorithm. The south façade of Scenario 1 (when the heights of surrounding buildings are lower than that of the targeted building) obtained the optimal payback period (8.44 years) and power generation (55961 kWh), with 77 opaque PV panels and 49 semi-transparent ones. [ABSTRACT FROM AUTHOR]

Building Integrated Photovoltaics (BIPV) is a promising technology to decarbonize urban energy systems via harnessing solar energy available on building envelopes. While methods to assess solar irradiation, especially on rooftops, are well established, the assessment on building facades usually involves a higher effort due to more complex urban features and obstructions. The drawback of existing physics-based simulation programs are that they require significant manual modeling effort and computing time for generating time resolved deterministic results. Yet, solar irradiation is highly intermittent and representing its inherent uncertainty may be required for designing robust BIPV energy systems. Targeting on these drawbacks, this paper proposes a data-driven model based on Deep Generative Networks (DGN) to efficiently generate stochastic ensembles of annual hourly solar irradiance time series on building facades with uncompromised spatiotemporal resolution at the urban scale. The only input required are easily obtainable fisheye images as categorical shading masks captured from 3D models. In principle, even actual photographs of urban contexts can be utilized, given they are semantically segmented. The potential of our approach is that it may be applied as a surrogate for time-consuming simulations, when facing lacking information (e.g., no 3D model exists), and to use the generated stochastic time-series ensembles in robust energy systems planning. Our validations exemplify a good fidelity of the generated time series when compared to the physics-based simulator. Due to the nature of the used DGNs, it remains an open challenge to precisely reconstruct the ground truth one-to-one for each hour of the year. However, we consider the benefits of the approach to outweigh the shortcomings. To demonstrate the model’s relevance for urban energy planning, we showcase its potential for generative design by parametrically altering characteristic features of the urban environment and producing corresponding time series on building facades under different climatic contexts in real-time.

[Display omitted] • Assessment of rooftop solar potential at high latitudes. • Mapping urban solar potential and linking it to urban form using 3D GIS methods. • Use of machine learning to identify key morphological indicators that influence urban solar potential. • Five typical urban form archetypes were identified through cluster analysis. • Low-energy potential of cities calculated and analyzed to inform policies for carbon neutrality. The complexity of urban form can have a significant impact on the utilization of solar energy. While numerous studies have examined the influence of urban form on solar potential, the optimization of solar energy use in cities located at high latitudes remains a challenging subject. In this study, we focus on the high-latitude city of Glasgow, using residential buildings in urban grid cells as our sample. We calculate solar potential and urban form indicators for these buildings using the Digimap database and the ArcGIS Pro platform. Employing eight machine learning algorithms, we analyze the data and extract eight key morphological indicators that affect the solar potential of urban grid cells. Among these indicators, we select four indicators—roof slope, building density, plot ratio, and building perimeter shape factor—for cluster analysis, enabling us to classify urban building forms into five types based on their characteristics and solar potential. Our calculations demonstrate that effective utilization of solar energy offers significant zero energy potential for Glasgow. The findings of this research can provide valuable guidance in the early stages of urban planning and design, assisting policymakers in rationalizing the use of solar energy resources for sustainable urban development. Furthermore, the results help urban stakeholders identify variations in the solar potential of different building forms, aiding them in selecting appropriate building types and zones to maximize solar energy utilization. [ABSTRACT FROM AUTHOR]

Cities are expected to be protagonists of the energy transition and, among other challenges, the decarbonation of the residential consumption could greatly benefit from photovoltaic generation in the built environment. To assess its potential, the present study analyses the possibility to cover the electric demand of the city of Valencia with rooftop-installed PV panels. Specific types of buildings has been selected to study the potential of each one of them with respect to their demand and with a specific production/consumption model. The total potential energy production for the city of Valencia is estimated to be enough to satisfy the demand of domestic electricity. The economic investment scenario has been analysed (best- and worst-case scenarios), and the corresponding environmental benefits have been studied. The results of the present article are encouraging in the context of a global energy transition, necessary in the present times to keep human consumption within the planetary limits. • Potential energy generation with rooftop PV panels has been estimated. • Rooftop PV can cover almost completely the domestic electricity demand. • Best- and worst-case scenarios for economic investments have been estimated. • Environmental considerations and emission estimations are reported. [ABSTRACT FROM AUTHOR]

The large-scale use of solar energy is an important means of achieving carbon neutrality. In cities, large stocks of building roofs are ideal for photovoltaic (PV) installations. However, the difficulty in acquiring urban building stock data limits the assessment of urban roof PV potential. Therefore, an instance segmentation model was used to extract all the roofs and their corresponding deep features from high-resolution open-source satellite maps. Subsequently, a multi-round semi-supervised clustering process was proposed to classify similar roofs. Finally, the total urban roof area was evaluated, involving pitched roof area correction. The PV available area ratios of all roofs were estimated by sampling each roof cluster to obtain the available roof area for PV installation. The corresponding urban PV potential capacity and energy generation were calculated. The proposed method was applied and validated in the Yangpu District of Shanghai, China. The results showed that the total building roof area of Yangpu District was 11.16 km2, and the roof PV available area ratio (R a s) varied between 0.4 and 0.92. The available roof area for PV installation was 7.46 km2. The PV installation area and capacity were 4.14 km2 and 913.74 MW, respectively. The annual PV energy production was 940.34 GW h. • Instance segmentation model was used for city-scale building roofs extraction. • A multi-rounds semi-supervised clustering process was proposed to classify roofs. • Potential roof PV capacity and energy production in Yangpu District were evaluated. [ABSTRACT FROM AUTHOR]

Highlights • We assess the potential for building PV systems in urban areas. • We use pairwise comparisons to calculate a solar score and rank spatial locations. • The score is computed for some relevant performance indicators and spatial aggregates. • The method accounts for crucial environmental uncertainties (weather and vegetation). • A 3D-mapping tool overlaying the spatial aggregates supports decision-making. Abstract Many municipalities and public authorities have supported the creation of solar cadastres to map the solar energy-generation potential of existing buildings. Despite advancements in modelling solar potential, most of these tools provide simple evaluations based on benchmarks, neglecting the effect of uncertain environmental conditions and that of the spatial aggregation of multiple buildings. We argue that including such information in the evaluation process can lead to more robust planning decisions and a fairer allocation of public subsidies. To this end, this paper presents a novel method to incorporate uncertainty in the evaluation of the solar electricity generation potential of existing buildings using a multi-scale approach. It also presents a technique to visualise the results through their integration in a 3D-mapping environment and the use of false-colour overlays at different scales. Using multiple simulation scenarios, the method is able to provide information about confidence intervals of summary statistics of production due to variation in two typical uncertain factors: vegetation and weather. The uncertainty in production introduced by these factors is taken into account through pairwise comparisons of nominal values of indicators, calculating a comprehensive ranking of the energy potential of different spatial locations and a corresponding solar score. The analysis is run at different scales, using space- and time-aggregated results, to provide results relevant to decision-makers. [ABSTRACT FROM AUTHOR]

• Walls have significant solar potential despite receiving less solar radiation than the roof areas. • Quantifying the solar potential of building facades in different urban forms is an important task. • This study explores the façade solar potential of different block types in Adelaide. • It simulates solar potential of building rooftops and facades across city boundaries. • Five prototypes are identified to provide a benchmark in the early urban planning and design stage. The decarbonization of urban energy systems relies heavily on Building Integrated Photovoltaic (BIPV) technology, which harnesses solar energy from building envelopes. While rooftops have been the focus of solar potential studies, walls also hold significant potential despite receiving less solar radiation. This study aims to quantify the solar potential of building facades in various urban forms, using Adelaide as an example. It first simulated and predicted the solar radiation potential of building facades, then conducted a cluster analysis of urban morphology factors and wall solar potential based on parameters chosen from existing studies to yield five clusters. Five block prototypes were identified for deploying solar on the walls in mixed-use urban neighborhoods. The solar potential was evaluated by calculating the electricity output from solar photovoltaic systems. The results indicate that the ranking of the solar potential of walls from highest to lowest is Cluster 4 (low density and nonuniform size, 1079.83 kWh/m2/year), Cluster 5 (low-rise, low density and uniform size, 1048.83 kWh/m2/year), Cluster 2 (low-rise and high density, 1027.80 kWh/m2/year), Cluster 3 (high-low mixed rise and high density, 985.59 kWh/m2/year), and Cluster 1 (high-rise and high density, 926.16 kWh/m2/year). The rooftop solar potential in Adelaide is capable of meeting the electricity demand, while the total facade solar potential in the entire city can reach 76% of the electricity demand. Specifically, the facade solar power generation of commercial buildings can account for 28% of the electricity demand, and the façade solar power generation of residential buildings can reach 39% of the electricity demand. The results of this study provide a simplified process to explore the solar potential of building facades and rooftops in different block types, which may provide a design benchmark for mixed types of blocks with high solar potential in the early phases of city planning and building design. [ABSTRACT FROM AUTHOR]

The use of 3D city models combined with simulation functionalities allows to quantify energy demand and renewable generation for a very large set of buildings. The scope of this paper is to determine the solar photovoltaic potential at an urban and regional scale using CityGML geometry descriptions of every building. An innovative urban simulation platform is used to calculate the PV potential of the Ludwigsburg County in south-west Germany, in which every building was simulated by using 3D city models. Both technical and economic potential (considering roof area and insolation thresholds) are investigated, as well as two different PV efficiency scenarios. In this way, it was possible to determine the fraction of the electricity demand that can be covered in each municipality and the whole region, deciding the best strategy, the profitability of the investments and determining optimal locations. Additionally, another important contribution is a literature review regarding the different methods of PV potential estimation and the available roof area reduction coefficients. An economic analysis and emission assessment has also been developed. The results of the study show that it is possible to achieve high annual rates of covered electricity demand in several municipalities for some of the considered scenarios, reaching even more than 100% in some cases. The use of all available roof space (technical potential) could cover 77% of the region’s electricity consumption and 56% as an economic potential with only high irradiance roofs considered. The proposed methodological approach should contribute valuably in helping policy-making processes and communicating the advantages of distributed generation and PV systems in buildings to regulators, researchers and the general public. [ABSTRACT FROM AUTHOR]

Previous research has assessed the potential of solar energy against possible demand; however, the sustainability issues associated with the use of large-scale photovoltaic deployment in urban areas have not been jointly established. In this paper, the impact of photovoltaic energy in the total urban energy mix is estimated using a series of indicators that consider the economic, environmental and social dimensions. These indicators have been previously applied at the country level; the main contribution of this research is applying them at the urban level to the city of Cuenca, Ecuador. Cuenca is close to the equatorial line and at a high altitude, enabling this area to reach the maximum self-supply index because of the high irradiation levels and reduced demand. The solar potential was estimated using a simple methodology that applies several indexes that were proven reliable in a local context considering this particular sun path. The results demonstrate that the solar potential can meet the electric power demand of this city, and only the indicator related to employment is positive and substantially affected. The indicators related to the price of energy, emissions and fossil fuel dependency do not change significantly, unless a fuel-to-electricity transport system conversions take place.

Energy economy restructuring at the city level is an essential prong in any strategy that aims to address the dual energy and climate change challenges. Cities form hubs of human activity that are accompanied by high levels of energy consumption and emissions but also contain existing resources and infrastructure to transition to a greener energy economy. This paper reviews efforts to date to define the ‘solar city’ concept and assessment methods for estimating the solar electric potential of an often neglected but vital city resource in energy matters – its rooftop real estate. From this review, an application of the solar city concept is formulated and an assessment method is offered for its investigation. An illustrative case study is provided, using the City of Seoul, South Korea. Representing nearly one-quarter of South Korea’s population and a one-third of its economic activity, the application of the solar city concept to the city can have significant consequences for the future energy development pathway of the municipality and the country (the metropolitan area of Seoul encompasses nearly one-half of the national population). The research demonstrates that a technical potential equivalent to almost 30% of the city’s annual electricity consumption can be supplied by widespread deployment of rooftop-based distributed photovoltaic systems. Using the methodology developed in the paper, we estimate that sixty-six percent of the annual daylight-hours electricity needs of the City of Seoul can be served by distributed solar power systems on a typical day. It is additionally found that considerable peak shaving is possible, lessening the pressure on the city’s electricity grid. These findings can be expected to extend to other large cities when the solar city concept is thoughtfully applied. [ABSTRACT FROM AUTHOR]

Urban areas can be considered high-potential energy producers alongside their notable portion of energy consumption. Solar energy is the most promising sustainable energy in which urban environments can produce electricity by using rooftop-mounted photovoltaic systems. While the precise knowledge of electricity production from solar energy resources as well as the needed parameters to define the optimal locations require an adequate study, effective guidelines for optimal installation of solar photovoltaics remain a challenge. This paper aims to make a complete systematic review and states the vital steps with their data resources to find the urban rooftop PV potential. Organizing the methodologies is another novelty of this paper to create a complete global basis for future studies and improve a more detailed degree in this particular field. [ABSTRACT FROM AUTHOR]

Previous research has assessed the potential of solar energy against possible demand; however, the sustainability issues associated with the use of large-scale photovoltaic deployment in urban areas have not been jointly established. In this paper, the impact of photovoltaic energy in the total urban energy mix is estimated using a series of indicators that consider the economic, environmental and social dimensions. These indicators have been previously applied at the country level; the main contribution of this research is applying them at the urban level to the city of Cuenca, Ecuador. Cuenca is close to the equatorial line and at a high altitude, enabling this area to reach the maximum self-supply index because of the high irradiation levels and reduced demand. The solar potential was estimated using a simple methodology that applies several indexes that were proven reliable in a local context considering this particular sun path. The results demonstrate that the solar potential can meet the electric power demand of this city, and only the indicator related to employment is positive and substantially affected. The indicators related to the price of energy, emissions and fossil fuel dependency do not change significantly, unless a fuel-to-electricity transport system conversions take place. [ABSTRACT FROM AUTHOR]