Modeling global and regional potentials for building-integrated solar energy generation

With the Paris Agreement coming into force, global efforts will need to maximize opportunities through energy efficiency and renewable energy generation. Zero energy/carbon initiatives are mushrooming worldwide, but it has not been fully understood which building types in which climates and under which conditions can potentially be built to net zero energy standards. In order to inform these efforts, a new model was developed to estimate the technical potential for building¿integrated solar energy (BISE, the name of the model) generation in a high resolution regional, climate and building typology breakdown., The BISE model also evaluates the opportunities for potential net zero energy buildings based on the BISE findigns, combining these with the findings of two global low-energy building models. The BISE model has a very high resolution in terms of geographic regions, climate types, building types and vin- tages. Moreover, the model combines methods for bottom-up energy modeling and geospatial analysis. The thermal building energy demand estimation is based on the 3CSEP-HEB model and the plug load scenarios are based on the BUENAS model. Results are wide, due to intrinsic limitationso of the model detailed in the paper, but it is shown that there is a substantial potential for building-integrated solar energy generation in all world regions, and that the Deep Efficiency Scenario allows significantly more building types to meet net zero energy levels by 2050 in contrast to a scenario when only moderate energy efficiency improvements are implemented.The work presented in this paper was funded by Central European University as part of a PhD research and through other grants. Special gratitude is expressed Dr. M. McNeil for sharing the data and their expertise on building energy use and energy modelling. The authors would like to thank Mr. D. Leiszen for his creative approach to developing software and visulisation parts of the model

Assessment of potential rooftop solar PV electricity at a suburban scale, and a comparative analysis based on topographical obstruction and seasonality

Long-term climate change mitigation calls for a switch from the current global non-renewable energy system to low greenhouse gas (GHG) emission energy solutions. Many nations have started adopting energy-efficient technology as part of their climate change programs and the built environment has been identified as a key lever for reducing emissions linked to energy efficiency. Building rooftop photovoltaic (PV) system is an effective technology to reduce emissions through the use of solar energy. In recent years, rooftop PV systems have become the main source of solar-generated energy, and forecasting their output is critical when assessing a site\u27s PV energy potential. However, integrating topographical features with seasonal considerations to estimate solar PV energy is challenging. There are some studies available that estimate solar PV energy on rooftops using geospatial tool modeling, but these have limitations in functionality, accuracy, and calculation speed. This study uses a geospatial tool to assess the solar PV potential of suitable rooftops in the suburbs of Wollongong, Australia, namely, Wombarra and Cringila. The model used in this study compares the energy potential of these two suburbs based on the topographical feature (escarpment), seasonality, rooftop slope, and aspect. The digital surface model (DSM) is created using LiDAR data, and then the DSM, building footprints, and suburb boundaries data are used to calculate the solar PV energy potential. A total of 1594 buildings from two suburbs were considered. Subsequently, solar radiation modeling for four common seasons in a year and a comparison of solar radiation output, suitable rooftop area, and electricity output are being done for both suburbs. Wombarra\u27s building rooftops are shadowed by the escarpment, whereas Cringila\u27s aren\u27t. Even though the weather in both suburbs is similar, the escarpment\u27s shadow affects solar PV energy output. Wombarra has 178 kWh/m2/building lesser yearly solar radiation than Cringila. Hence, Cringila offers more solar rooftop installation potential per building. The average annual potential electricity generation per dwelling in Wombarra is 20.6 kWh/m2/day, and the same for Cringila is 27.6 kWh/m2/day. The outcome reveals that 1352 building rooftops, with a usable area of 75481 m2, are the best locations for installing solar panels. According to the Australian Government\u27s Energy Made Easy statistics, the annual electricity consumption per household in Wollongong is 5707.6 kWh (Australian Energy Regulator 2022). The estimated yearly electricity production is 12705 Mwh (Wombarra: 2778.3 Mwh, Cringila: 9926.7 Mwh), which would be sufficient to meet local electricity consumption. An excess of 17% from Wombarra and 48% from Cringila can be exported back to the grid, which can be used by 3 neighbouring areas. Tiseo (2021) reported that Australia\u27s power sector released 656.4 grams/kWh of CO2 in 2020. Therefore, solar PV panels on all suitable rooftops of both suburbs could prevent 8339.5 tonnes of CO2 emissions. To achieve the goal of clean energy, future development can use the study\u27s findings as a guide. The proposed approach can assist in influencing policies and subsidies to boost deployment. This research can be made more in-depth by taking into account social and economic factors like consumer choices and return on investment, and physically inspecting specific building rooftop impediments

Photovoltaic potential in building façades

Tese de doutoramento, Sistemas Sustentáveis de Energia, Universidade de Lisboa, Faculdade de Ciências, 2018Consistent reductions in the costs of photovoltaic (PV) systems have prompted interest in applications with less-than-optimum inclinations and orientations. That is the case of building façades, with plenty of free area for the deployment of solar systems. Lower sun heights benefit vertical façades, whereas rooftops are favoured when the sun is near the zenith, therefore the PV potential in urban environments can increase twofold when the contribution from building façades is added to that of the rooftops. This complementarity between façades and rooftops is helpful for a better match between electricity demand and supply. This thesis focuses on: i) the modelling of façade PV potential; ii) the optimization of façade PV yields; and iii) underlining the overall role that building façades will play in future solar cities. Digital surface and solar radiation modelling methodologies were reviewed. Special focus is given to the 3D LiDAR-based model SOL and the CAD/plugin models DIVA and LadyBug. Model SOL was validated against measurements from the BIPV system in the façade of the Solar XXI building (Lisbon), and used to evaluate façade PV potential in different urban sites in Lisbon and Geneva. The plugins DIVA and LadyBug helped assessing the potential for PV glare from façade integrated photovoltaics in distinct urban blocks. Technologies for PV integration in façades were also reviewed. Alternative façade designs, including louvers, geometric forms and balconies, were explored and optimized for the maximization of annual solar irradiation using DIVA. Partial shading impacts on rooftops and façades were addressed through SOL simulations and the interconnections between PV modules were optimized using a custom Multi-Objective Genetic Algorithm. The contribution of PV façades to the solar potential of two dissimilar neighbourhoods in Lisbon was quantified using SOL, considering local electricity consumption. Cost-efficient rooftop/façade PV mixes are proposed based on combined payback times. Impacts of larger scale PV deployment on the spare capacity of power distribution transformers were studied through LadyBug and SolarAnalyst simulations. A new empirical solar factor was proposed to account for PV potential in future upgrade interventions. The combined effect of aggregating building demand, photovoltaic generation and storage on the self-consumption of PV and net load variance was analysed using irradiation results from DIVA, metered distribution transformer loads and custom optimization algorithms. SOL is shown to be an accurate LiDAR-based model (nMBE ranging from around 7% to 51%, nMAE from 20% to 58% and nRMSE from 29% to 81%), being the isotropic diffuse radiation algorithm its current main limitation. In addition, building surface material properties should be regarded when handling façades, for both irradiance simulation and PV glare evaluation. The latter appears to be negligible in comparison to glare from typical glaze/mirror skins used in high-rises. Irradiation levels in the more sunlit façades reach about 50-60% of the rooftop levels. Latitude biases the potential towards the vertical surfaces, which can be enhanced when the proportion of diffuse radiation is high. Façade PV potential can be increased in about 30% if horizontal folded louvers becomes a more common design and in another 6 to 24% if the interconnection of PV modules are optimized. In 2030, a mix of PV systems featuring around 40% façade and 60% rooftop occupation is shown to comprehend a combined financial payback time of 10 years, if conventional module efficiencies reach 20%. This will trigger large-scale PV deployment that might overwhelm current grid assets and lead to electricity grid instability. This challenge can be resolved if the placement of PV modules is optimized to increase self-sufficiency while keeping low net load variance. Aggregated storage within solar communities might help resolving the conflicting interests between prosumers and grid, although the former can achieve self-sufficiency levels above 50% with storage capacities as small as 0.25kWh/kWpv. Business models ought to adapt in order to create conditions for both parts to share the added value of peak power reduction due to optimized solar façades.Fundação para a Ciência e a Tecnologia (FCT), SFRH/BD/52363/201

Solar potential for social benefit: Maps to sustainably address energy poverty utilizing open spatial data in data poor settings

Access to affordable sustainable energy is a significant challenge for many lowincome countries experiencing energy poverty. The United Nations (UN) Sustainable Development Goal (SDG) 7 aims to “ensure access to affordable, reliable, sustainable and modern energy for all.” Simultaneously, the European Union (EU) seeks to reduce emissions by 55 % by 2030. Decarbonization policies must be carefully considered to avoid adverse effects on vulnerable groups experiencing energy poverty. Solar technology offers a viable solution to decarbonize the building sector, reduce energy dependence on fossil fuels, and provide financial benefits to the public. Mapping solar potential is crucial to determine where investment in solar photovoltaic (PV) technology is most advantageous to the populations who stand to benefit the most. We combine a solar potential mapping approach incorporating socio-economic indicators indicative of energy poverty, using off-the-shelf Geographic Information Systems (GIS) tools that are easily replicated across cities facing energy poverty. Utilizing lowest common denominator data and analysis approaches, we offer creative and innovative mapping solutions. The socio-economic factors help to contextualise the benefits of distributed PV systems and highlight the need for mapping solar potential, in combination with energy poverty indicators for sustainable planning and policymaking. Our results for a case study in the city of Plovdiv, Bulgaria, demonstrate high solar energy potential that could meet 29 % of the city's electricity needs, save citizens about M€ 43.84 annually, and pinpoint where to invest first for the highest gains. Finally, we offer suggestions on how to use these results to inform decarbonization policies to benefit low-income populations that are often missed in existing energy policies

Facades and solar parking yield estimation at Ultrecht University

Solar energy born as one of the ways to produce energy using renewable resources (like wind, biomass, hydraulic, geothermal and wave energies). The solar energy is divided into three types: thermal, that generates heat (which can be used to produce energy), photovoltaic that only produces electricity and PVT, a hybrid way to generate heat and produce electricity. Photovoltaic (PV) technologies have several uses such as lighting, satellites, solar home systems, pumping, etc. This work pretends to estimate the potential of usage of solar cells and the yield potential at De Uithof campus located in Utrecht, Netherlands. Building attached photovoltaic (BAPV), solar parking lot and charging electric vehicles (EV) were the chosen uses of solar energy for this project. The work method is divided into four parts, firstly a 2D part that was done on ArcGIS software to create the shapefile with the buildings and solar parking information of the incoming radiation for the entire year in Wh/m2. Secondly, the 3D works on AutoCAD, Autodesk FBX Converter and PVsyst to create the 3D plant and to import the shading scene construction, to install the solar modules on the roofs, facades and solar parking lot. The third part is to choose the charging mode 3 combined with connector type 2 that full charge the Tesla model 3 (which has a battery of 50 kWh) in around five hours (charging 11kW per hour). The fourth part details the input data and calculate the economic viability considering the total cost of initial investment and operation/maintenance costs. Two tests were used to compare different options, VC0 (35.175 kWp) with the solar modules facing south and VC1 (50.796 kWp) on the west-east plus south direction. The chosen PV module was the LG 340 N1C-A5 by LG Electronics and the inverter was the AGILO 100.0-3 Outdoor by Fronius International because they are commercially available equipments. The VC0 has a system production of 27.229 MWh/year and the VC1, 35.285 MWh/year, both are feasible economically because they have the NPV greater than zero, being €68 million for VC0 and €83 million for VC1. In addition, the Payback is much lower than 25 years (lifetime of photovoltaic panels), being 7,69 years and 7,03 years, respectively for VC0 and VC1. Furthermore, the LCOE of the VC0 is 0.058 €/kWh, and for VC1, 0,064 €/kWh; RESUMO: A energia solar surgiu como uma das diversas maneiras para produzir energia elétrica utilizando recursos renováveis (como a energia eólica, biomassa, hidráulica, geotérmica e das ondas). A energia solar é dividida em três tipos: térmica, que gera calor (que também pode ser usado para produzir energia), fotovoltaica que somente produz eletricidade e PVT, maneira híbrida de gerar calor e produzir eletricidade. Tecnologia fotovoltaica tem diversos usos como iluminação, satélite, sistemas solares residenciais, bombeamento, entre outros. Este trabalho pretende estimar o potencial do uso de células solares e a potência anual no campus De Uithof que se localiza em Utrecht, Países Baixos. Building attached photovoltaic (BAPV), estacionamento solar e carregamento de veículos elétricos (EV) foram os usos da energia escolhidos para este projeto. O método do trabalho se divide em quarto partes, primeiramente a parte 2D que foi feita no software ArcGIS para criar shapefile com as informações da radiação que chega aos prédios e estacionamento durante todo o ano em Wh/m2. Segundamente, o 3D feito no AutoCAD, Autodesk FBX Converter e PVsyst para criar a planta 3D e importar no Shading scene construction, instalar os módulos solares nos telhados, fachadas e estacionamento solar. A terceira parte foi escolher o modo de carregamento 3 combinado com o conector 2 que carrega completamente o Tesla model 3 (possuindo bateria de 50 kWh) em aproximadamente em cinco horas (carregando 11 kW por hora). A quarta parte detalha os dados de entrada e calcula a viabilidade econômica considerando o custo total de investimento e custos de operação/manutenção. Dois testes foram feitos de modo a compará-los, VC0 (35.175 kWp) com os módulos solares virados para sul e VC1 (50.796 kWp) nas direções este-oeste e direção sul. O painel escolhido foi o LG 340 N1C-A5 da LG Electronics e o inversor AGILO 100.0-3 Outdoor da Fronius International porque são equipamentos comerciais. A produção do VC0 é de 27.229 MWh/ano e o VC1, 36.614 MWh/ano, os dois são economicamente viáveis porque possuem o VPL (NPV) maior que zero, sendo €68 millhões para o VC0 e €83 para o VC1. Adicionalmente, o Payback possui um valor bem abaixo de 25 anos (ciclo de vida dos paineis fotovoltaicos), sendo 7,69 anos e 7,03, respe

GIS and Remote Sensing for Renewable Energy Assessment and Maps

This book aims at providing the state-of-the-art on all of the aforementioned tools in different energy applications and at different scales, i.e., urban, regional, national, and even continental for renewable scenarios planning and policy making

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

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