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Optimization of PV Modules Layout on High-rise Building Skins Using a BIM-based Generative Design Approach

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Optimization of PV Modules Layout on High-rise Building Skins Using a BIM-based Generative Design Approach

Salimzadeh, Negar (2021) Optimization of PV Modules Layout on High-rise Building Skins Using a BIM-based Generative Design Approach. PhD thesis, Concordia University.

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Abstract

Growing urbanism and the resulting increase of energy demand coupled with depleting fossil energy resources are making the need for renewable energy resources progressively palpable and vital. In addition to reducing carbon dioxide emissions, renewable energy is crucial to improve health and well-being, and provide affordable energy access worldwide.
Photovoltaic (PV) solar energy, as a fast-evolving industry, has become a vital part of the global energy transformation in recent years that can contribute to the development of sustainable cities and the mitigation of global warming. In the urban environment, buildings are central to human activities. Given that buildings currently account for 40% of the global energy consumption, to achieve sustainable urban development, buildings are of particular importance for distributed renewable energy generation, which reduces energy transmission losses. PV panels are able to harvest the solar power and turn it into a clean source of energy. Furthermore, the increasing availability, affordability, and efficiency of PV panels are rendering them an attractive option for the users so that the worldwide use of photovoltaic electricity is growing rapidly by more than 50% a year.
Of different types of buildings in the built environment, high-rise buildings are of particular interest because of their high potentials for harvesting a considerable amount of PV energy on vertical and horizontal surfaces. Nevertheless, this high potential is seldom harnessed mainly because the deployment of PV modules on high-rise buildings requires considering a complex interplay between various factors that affect the installation of PV modules (e.g., neighborhood shadow effect, modules self-shadowing effect, surface-specific PV modules, etc.). This renders the design of PV modules in high-rise buildings a complex optimization problem, one that requires a generative design approach. There are many tools and models, from simple 2D evaluation to more comprehensive and complicated 3D analysis, that can help simulate the solar radiation potential of surfaces of a building. However, the majority of the methods do not discriminate between different types of surfaces of the building and treat the entire envelope as a single surface. In recent years, and with the advent and rising popularity of the Building Information Modeling (BIM) concept, the apparatus for the implementation of such a comprehensive generative design approach is becoming increasingly available. However, to the best of the author’s knowledge, there is currently no framework for the BIM-based generative design of PV modules for high-rise buildings.
Addressing the current issues, this research aims to: (1) Develop a parametric modeling platform for the design of surface-specific PV module layout on the entire skin of buildings, and (2) Develop a BIM-based generative design framework for the design of PV modules layout on high-rise building skins. In this framework, the surface-specific parametric model of PV modules is integrated with an optimization method to find the optimum design of PV modules layout considering the study period, profit margin, harvested PV energy, and cost. This framework will enable designers and investors to apply the generative design paradigm to the use of PV modules on building skin considering the complex interaction between building surface types (e.g., windows, walls, etc.), type of PV module (e.g., opaque, semi-transparent, etc.), their tilt and pan angles, and the financial aspect of the PV system (i.e., revenue vs. cost at different study periods).
The results generated by the elaborate case study demonstrated that the generative design framework is capable of offering more favourable solutions (i.e., either or both of reduced costs and increased energy revenue) compared to baseline scenarios. It is observed that in the majority of the studied scenario, the optimum solutions favored a more consistent orientation of the panels (i.e., consistent pan and tilt angles across all the panels).

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Thesis (PhD)
Authors:Salimzadeh, Negar
Institution:Concordia University
Degree Name:Ph. D.
Program:Civil Engineering
Date:25 July 2021
Thesis Supervisor(s):Hammad, Amin and Vahdatikhaki, Faridaddin
ID Code:988956
Deposited By: NEGAR SALIMZADEH
Deposited On:29 Nov 2021 16:50
Last Modified:29 Nov 2021 16:50

References:

Aarre Maehlum, M. (2014, May). Solar Energy Pros and Cons. Retrieved from Energy Informative: http://energyinformative.org/solar-energy-pros-and-cons/
Abanda, F. H., & Byers, L. (2016). An investigation of the impact of building orientation on energy consumption in a domestic building using emerging BIM (Building Information Modelling). Energy, 97, 517-527.
Abraham, A., & Jain, L. (2005). Evolutionary Multiobjective Optimization. Evolutionary Multiobjective Optimization (pp. 1-6). London: Springer.
AIA. (2021). Level of Development Specification. Retrieved 2018, from The American Institute of Architects: https://bimforum.org/lod/
Al-Janahi, S. A., Ellabban, O., & Al-Ghamdi, S. G. (2020). A Novel BIPV reconfiguration algorithm for maximum power generation under partial shading. Energies, 13(17), 44-70.
ArcGIS. (2021). Esri. Retrieved from http://www.esri.com/software/arcgis/arcgis-for-desktop
Attoye, D., Tabet Aoul, K., & Hassan, A. (2017). A review on building integrated photovoltaic façade customization potentials. Sustainability, 9(12), 1-24.
Autodesk. (2021). Project Refinery. Retrieved from https://dynamobim.org/project-refinery-0-62-2-now-available/
Autodesk. (2021). Revit. Retrieved from http://www.autodesk.com/education/free-software/revit
Bedrick, J. (2008). Organizing the development of a building information model. The American Institute of Architects.
Biyik, E., Araz, M., Hepbasli, A., Shahrestani, M., Yao, R., Shao, L., & Atlı, Y. B. (2017). A key review of building integrated photovoltaic (BIPV) systems. Engineering science and technology, 20(3), 833-858.
Bloomberg New Energy Finance. (2018). Wind & solar to account for 50% of world's power by 2050. Retrieved from Renewables Now: https://renewablesnow.com/news/wind-solar-to-account-for-50-of-worlds-power-by-2050-bnef-617007/
Brito, M. C., Gomes, N., Santos, T., & Tenedório, J. A. (2012). Photovoltaic potential in a Lisbon suburb using LiDAR data. Solar Energy, 86(1), 283-288.
Brown, D. (2016). How to Run a Solar Radiation Analysis in Revit. Retrieved from http://dylanbrowndesigns.com/tutorials/how-to-run-a-solar-radiation-analysis-in-revit/
Brown, L. R. (2015). The Great Transition: Shifting from Fossil Fuels to Solar and Wind Energy. Washington, D.C: W. W. Norton Company. doi:0393351149, 9780393351149
Bueno, L., Ibliha, M., Vizcarra, B., Chaudhry, G. M., & Siddiki, M. K. (2015). Feasibility analysis of a solar photovoltaic array integrated on façades of a commercial building. In 2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC) (pp. 1-4). IEEE.
Byrne, J., Taminiau, J., Kurdgelashvili, L., & Kim, K. N. (2015). A review of the solar city concept and methods to assess rooftop solar electric potential, with an illustrative application to the city of Seoul. Renewable and Sustainable Energy Reviews, 41, 830-844.
Caetano, I., Santos, L., & Leitão, A. (2020). Computational design in architecture: Defining parametric, generative, and algorithmic design. Frontiers of Architectural Research, 9(2), 287-300.
CanSIA. (2020). ROADMAP 2020: Powering Canada's Future with Solar Electricity. Retrieved from http://www.cansia.ca/uploads/7/2/5/1/72513707/cansia_roadmap_2020_final.pdf
Carl, C. (2014). Calculating solar photovoltaic potential on residential rooftops in Kailua Kona, Hawaii (Doctoral dissertation, University of Southern California).
Carneiro, C., Morello, E., Desthieux, G., & Golay, F. (2010). Urban environment quality indicators: application to solar radiation and morphological analysis on built area. In Proceedings of the 3rd WSEAS international conference on Visualization, imaging and simulation (pp. 141-148). World Scientific and Engineering Academy and Society (WSEAS).
Catita, C., Redweik, P., Pereira, J., & Brito, M. C. (2014). Extending solar potential analysis in buildings to vertical facades. Computers & Geosciences, 66, 1-12.
Celik, B., Karatepe, E., Silvestre, S., Gokmen, N., & Chouder, A. (2015). Analysis of spatial fixed PV arrays configurations to maximize energy harvesting in BIPV applications. Renewable energy, 75, 534-540.
Charabi, Y., Rhouma, M. B., & Gastli, A. (December 2010). GIS-based estimation of roof-PV capacity & energy production for the Seeb region in Oman. In Energy Conference and Exhibition (EnergyCon) (pp. 41-44). IEEE.
Cheng, C. L., Jimenez, C. S., & Lee, M. C. (2009). Research of BIPV optimal tilted angle, use of latitude concept for south orientated plans. Renewable Energy, 34(6), 1644-1650.
Chow, A., Fung, A. S., & Li, S. (2014). GIS modeling of solar neighborhood potential at a fine spatiotemporal resolution. Buildings, 4(2), 195-206.
City of Montreal. (2021). Maquette numérique (Bâtiments CityGML LOD2 avec textures). Retrieved from Portail des données ouvertes: http://donnees.ville.montreal.qc.ca/
CWCT ‘Cladding Forum’. (2000). CURTAIN WALL TYPES. Retrieved 2018, from http://www.cwct.co.uk/publications/tns/short14.pdf
de Sousa Freitas, J., Cronemberger, J., Soares, R. M., & Amorim, C. N. (2020). Modeling and assessing BIPV envelopes using parametric Rhinoceros plugins Grasshopper and Ladybug. Renewable Energy, 160, 1468-1479.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. Evolutionary Computation, IEEE Transactions, 6(2), 182-197.
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T., & Fast, A. (2002). A Fast and Elitist Multiobjective Genetic Algorithm:NSGA-II. IEEE transactions on evolutionary computation, 6(2), 182-197.
Dezeen. (2017). dezeen. Retrieved from https://www.dezeen.com/2017/08/23/copenhagen-international-school-c-f-moller-architects-12000-solar-panels-denmark/
Diwekar, U. (2008). Introduction to applied optimization (Vol. 22). Springer Science & Business Media.
Dubayah, R., & Rich, P. M. (1995). Topographic solar radiation models for GIS. International Journal of Geographical Information Systems, 9(4), 405-419.
Dynamo. (2021). Open source graphical programming for design. Retrieved from http://dynamobim.org/
Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2011). BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors. John Wiley & Sons.
Eke, R., & Demircan, C. (2015). Shading effect on the energy rating of two identical PV systems on a building façade. Solar Energy, 122, 48-57.
Electric Choice. (2021). Retrieved from https://www.electricchoice.com/electricity-prices-by-state/
Energysage. (2018). Size and weight of solar panels. Retrieved from Energysage: https://news.energysage.com/average-solar-panel-size-weight/
Energysage. (2021). Retrieved from https://news.energysage.com/types-of-solar-panels/
Erdélyi, R., Wang, Y., Guo, W., Hanna, E., & Colantuono, G. (2014). Three-dimensional SOlar RAdiation Model (SORAM) and its application to 3-D urban planning. Solar Energy, 101, 63-73.
Esclapés, J., Ferreiro, I., Piera, J., & Teller, J. (2014). A method to evaluate the adaptability of photovoltaic energy on urban façades. Solar Energy, 105, 414-427.
ESRI. (2021). ArcGIS CityEngine. Retrieved from https://www.esri.com/en-us/arcgis/products/arcgis-cityengine/overview
Fernando, R., Drogemuller, R., & Burden, A. (2012). Parametric and generative methods with building information modelling: Connecting BIM with explorative design modelling. Proceedings of the 17th International Conference on Computer-Aided Architectural Design Research in Asia (pp. 537–546). Hong Kong: Association for Computer-Aided Architectural Design Research in Asia (CAADRIA).
Ferreira, B., & Leitão, A. (2015). Generative design for building information modeling. Computer Aided Architectural Design. CumInCAD-eCAADe.
Finance Formulas. (2021). Present Value of a Growing Annuity. Retrieved from http://financeformulas.net/Present_Value_of_Growing_Annuity.html
Freitas, S., & Brito, M. C. (2015). Maximizing the solar photovoltaic yield in different building facade layouts. (pp. 14-18). Hamburg, Germany: In Proceedings of the European Photovoltaic Solar Energy Conference and Exhibition.
Freitas, S., Serra, F., & Brito, M. C. (2015). PV layout optimization: String tiling using a multi-objective genetic algorithm. Solar Energy, 118, 562-574.
Fu, P., & Rich, P. M. (1999). Design and implementation of the Solar Analyst: an ArcView extension for modeling solar radiation at landscape scales. In Proceedings of the Nineteenth Annual ESRI User Conference, (pp. 1-31).
Fu, R., Feldman, D., Margolis, R., woodhouse, M., & Ardani, K. (2018). U.S. Solar Photovoltaic System Cost Benchmark: Q1 2018. National Renewable Energy Laboratory.
Gastli, A., & Charabi, Y. (2010). Solar electricity prospects in Oman using GIS-based solar radiation maps. Renewable and Sustainable Energy Reviews, 14(2), 790-797.
Gooding, J., Edwards, H., Giesekam, J., & Crook, R. (2013). Solar City Indicator: A methodology to predict city level PV installed capacity by combining physical capacity and socio-economic factors. Solar Energy, 95, 325-335.
Google Earth. (2021). Retrieved from https://earth.google.com
Gourlis, G., & Kovacic, I. (2017). Building Information Modelling for analysis of energy efficient industrial buildings–A case study. Renewable and Sustainable Energy Reviews, 68, 953-963.
Habibi, S. (2017). The promise of BIM for improving building performance. Energy and Buildings, 153, 525-548.
Hagerty, K., & Cormican, J. (2019). Components for solar panel (PV) system. Retrieved from altestore.com: https://www.altestore.com/howto/components-for-your-solar-panel-photovoltaic-system-a82/
Hassan, R., Cohanim, B., De Weck, O., & Venter, G. (2005). A comparison of particle swarm optimization and the genetic algorithm. 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, (p. 1897).
Hetrick, W. A., Rich, P. M., & Weiss, S. B. (1993). Modeling insolation on complex surfaces. In Thirteen Annual ESRI User Conference, 2, pp. 447-458.
Historical Climate Data. (2018). Retrieved from Government of Canada: http://climate.weather.gc.ca/
Hofierka, J., & Kaňuk, J. (2009). Assessment of photovoltaic potential in urban areas using open-source solar radiation tools. Renewable Energy, 34(10), 2206-2214.
Hofierka, J., & Suri, M. (2002). The solar radiation model for Open source GIS: implementation and applications. In Proceedings of the Open source GIS-GRASS users conference, (pp. 51-70).
Hofierka, J., & Zlocha, M. (2012). A New 3‐D Solar Radiation Model for 3‐D City Models. Transactions in GIS, 16(5), Transactions in GIS.
Hong, T., Koo, C., Park, J., & Park, H. S. (2014). A GIS (geographic information system)-based optimization model for estimating the electricity generation of the rooftop PV (photovoltaic) system. Energy, 65, 190-199.
Husain, A. A., Hasan, W. Z., Shafie, S., Hamidon, M. N., & Pandey, S. S. (2018). A review of transparent solar photovoltaic technologies. Renewable and Sustainable Energy Reviews, 94, 779-791.
Hwang, T., Kang, S., & Kim, J. T. (2012). Optimization of the building integrated photovoltaic system in office buildings—Focus on the orientation, inclined angle and installed area. Energy and Buildings, 46, 92-104.
International Energy Agency (IEA). (2018). Renewables. Retrieved from https://www.iea.org/topics/renewables/subtopics/solar/ .
Introduction to Shading. (2021). Retrieved from www.scratchapixel.com: https://www.scratchapixel.com/lessons/3d-basic-rendering/introduction-to-shading/ligth-and-shadows
IRENA. (2021). Clean Energy Corridors. Retrieved from International Renewable Energy Agency: https://www.irena.org/cleanenergycorridors
Jacobson, M. Z., & Jadhav, V. (2018). World estimates of PV optimal tilt angles and ratios of sunlight incident upon tilted and tracked PV panels relative to horizontal panels. Solar Energy, 169, 55-66.
Jakubiec, J. A., & Reinhart, C. F. (2013). A method for predicting city-wide electricity gains from photovoltaic panels based on LiDAR and GIS data combined with hourly Daysim simulations. Solar Energy, 93, 127-143.
Jelle, B. P., Breivik, C., & Røkenes, H. D. (2012). Building integrated photovoltaic products: A state-of-the-art review and future research opportunities. Solar Energy Materials and Solar Cells, 100, 69-96.
Jochem, A., Höfle, B., Rutzinger, M., & Pfeifer, N. (2009). Automatic roof plane detection and analysis in airborne lidar point clouds for solar potential assessment. Sensors, 9(7), 5241-5262.
Karteris, M., Slini, T., & Papadopoulos, A. M. (2013). Urban solar energy potential in Greece: A statistical calculation model of suitable built roof areas for photovoltaics. Energy and Buildings, 62, 459-468.
Kemery, B. P., Beausoleil-Morrison, I., & Rowlands, I. H. (2012). Optimal PV orientation and geographic dispersion: a study of 10 Canadian cities and 16 Ontario locations. (pp. 1- 4). Halifax, NS, Canada: In Proceedings of the Canadian Conference on Building Simulation.
Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization (PSO). In Proc. IEEE International Conference on Neural Networks, Perth, Australia, (pp. 1942-1948).
Kim, H., Asl, M. R., & Yan, W. (2015). Parametric BIM-based energy simulation for buildings with complex kinetic façades. In Proceedings of the 33rd eCAADe Conference, 1, pp. 657-664.
Koo, C., Hong, T., Lee, M., & Kim, J. (2016). An integrated multi-objective optimization model for determining the optimal solution in implementing the rooftop photovoltaic system. Renewable and Sustainable Energy Reviews, 57, 822-837.
Kucuksari, S., Khaleghi, A. M., Hamidi, M., Zhang, Y., Szidarovszky, F., Bayraksan, G., & Son, Y. J. (2014). An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments. Applied Energy, 113, 1601-1613.
Kumar, L., Skidmore, A. K., & Knowles, E. (1997). Modelling topographic variation in solar radiation in a GIS environment. International Journal of Geographical Information Science, 11(5), 475-497.
Ladybug Tools. (2021). Retrieved from https://www.ladybug.tools/ladybug.html
Li, Y., & Liu, C. (2018). Techno-economic analysis for constructing solar photovoltaic projects on building envelopes. Building and Environment, 127, 37-46.
Liang, J., Gong, J., Li, W., & Ibrahim, A. N. (2014). A visualization-oriented 3D method for efficient computation of urban solar radiation based on 3D–2D surface mapping. International Journal of Geographical Information Science, 28(4), 780-798.
Lin, Q., Kensek, K., Schiler, M., & Choi, J. (2021). Streamlining sustainable design in building information modeling BIM-based PV design and analysis tools. Architectural Science Review, 1-11.
Liu, S., Meng, X., & Tam, C. (2015). Building information modeling based building design optimization for sustainability. Energy and Buildings, 105, 139-153.
Ludwig, D., Lanig, S., & Klärle, M. (2009). Sun-area towards location-based analysis for solar panels by high resolution remote sensors (LiDAR). In Proceedings of International Cartograhy Conference. Santiago de Chile.
LunchBox. (2021). Retrieved from proving ground: https://provingground.io/tools/lunchbox/
Ma, W., Wang, X., Wang, J., Xiang, X., & Sun, J. (2021). Generative Design in Building Information Modelling (BIM): Approaches and Requirements. Sensors, 21(16), 5439.
Mallawaarachchi, V. (2021). Towards Data Science. Retrieved 2018, from https://towardsdatascience.com/
Mardaljevic, J. (2000). Simulation of annual daylighting profiles for internal illuminance. International Journal of Lighting Research and Technology, 32(3), 111-118.
Marsh, A. (2003). ECOTECT and EnergyPlus. Building Energy Simulation User News.
Marszal, A. J., Bourrelle, J. S., Musall, E., Voss, K., Sartori, I., & Napolitano, A. (2011). Zero Energy Building–A review of definitions and calculation methodologies. Energy and buildings, 43(4), 971-979.
Martín, A. M., Domínguez, J., & Amador, J. (2015). Applying LiDAR datasets and GIS based model to evaluate solar potential over roofs: A review. AIMS Energy, 11(2), 326-343.
Mawlana, M. (2015). Improving Stochastic Simulation-based Optimization for Selecting Construction Method of Precast Box Girder Bridges. PhD thesis. Concordia University.
McCall, J. (2005). Genetic algorithms for modelling and optimisation. Journal of Computational and Applied Mathematics, 184(1), 205-222.
McCormack, J., Dorin, A., & Innocent, T. (2004). Generative Design: A Paradigm for Design Research. Futureground - DRS International Conference. Melbourne, Australia: Design Research Society (DRS).
Mellouk, L., Aaroud, A., Benhaddou, D., Zine-Dine, K., & Boulmalf, M. (2015). Overview of mathematical methods for energy management optimization in smart grids. In Renewable and Sustainable Energy Conference (IRSEC), 2015 3rd International (pp. In Renewable and Sustainable Energy Conference (IRSEC), 2015 3rd International (pp. 1-5). IEEE.
Melo. (2021). Retrieved from https://www.teses.usp.br/teses/disponiveis/3/3143/tde-21062013-105044/publico/Solar3DBR_SourceCode.pdf
Melo, E. G., Almeida, M. P., Zilles, R., & Grimoni, J. A. (2013). Using a shading matrix to estimate the shading factor and the irradiation in a three-dimensional model of a receiving surface in an urban environment. Solar Energy, 92, 15-25.
Mitchell, W. J. (1975). The theoretical foundation of computer-aided architectural design. Environment planning and design, 127-150.
Morris, F. A. (2013). Definition and Types of Curtain Walls. In Curtain Wall Systems. ASCE.
Natural Resources Canada. (2019). Solar Photovoltaic Energy in Buildings. Retrieved from https://www.nrcan.gc.ca/energy/efficiency/data-research-and-insights-energy-efficiency/buildings-innovation/solar-photovoltaic-energy-buildings/3907
Nguyen, H. T., Pearce, J. M., Harrap, R., & Barber, G. (2012). The application of LiDAR to assessment of rooftop solar photovoltaic deployment potential in a municipal district unit. Sensors, 12(4), 4534-4558.
Ning, G., Junnan, L., Yansong, D., Zhifeng, Q., Qingshan, J., Weihua, G., & Geert, D. (2017). BIM-based PV system optimization and deployment. Energy and Buildings, 150, 13-22.
Ning, G., Kan, H., Zhifeng, Q., Weihua, G., & Geert, D. (2018). e-BIM: a BIM-centric design and analysis software for Building Integrated Photovoltaics. Automation in Construction, 87, 127-137.
Norton, B., Eames, P. C., Mallick, T. K., Huang, M. J., McCormack, S. J., Mondol, J. D., & Yohanis, Y. G. (2011). Enhancing the performance of building integrated photovoltaics. Solar Energy, 85(8), 1629-1664.
Onyx Solar . (2019). Photovoltaic Glass for Buildings. Retrieved from ONYX: https://www.onyxsolar.com/
Ordóñez, J., Jadraque, E., Alegre, J., & Martínez, G. (2010). Analysis of the photovoltaic solar energy capacity of residential rooftops in Andalusia (Spain). Renewable and Sustainable Energy Reviews, 14(7), 2122-2130.
Paulescu, M., Paulescu, E., Gravila, P., & Badescu, V. (2012). Weather modeling and forecasting of PV systems operation. Springer Science & Business Media.
Peng, C., Huang, Y., & Wu, Z. (2011). Building-integrated photovoltaics (BIPV) in architectural design in China. Energy and Buildings, 43(12), 3592-3598.
Perez, R., Ineichen, P., Seals, R., Michalsky, J., & Stewart, R. (1990). Modeling daylight availability and irradiance components from direct and global irradiance. Solar energy, 44(5), 271-289.
r.sun. (2006). Retrieved from https://docs.huihoo.com/grass/6.3/manuals/r.sun.html
Raugei, M., & Frankl, P. (2009). Life cycle impacts and costs of photovoltaic systems: current state of the art and future outlooks. Energy, 34(3), 392-399.
Redweik, P., Catita, C., & Brito, M. (2013). Solar energy potential on roofs and facades in an urban landscape. Solar Energy, 97, 332-341.
Rhinoceros. (2021). Retrieved from https://www.rhino3d.com/6/new/grasshopper/
Robinson, D., & Stone, A. (2004). Irradiation modelling made simple: the cumulative sky approach and its applications. In PLEA conference , (pp. 19-22).
Salimi, S., Mawlana, M., & Hammad, A. (2018). Performance analysis of simulation-based optimization of construction projects using high performance computing. Automation in Construction, 87, 158-172.
Salimzadeh, N., Sharif, S. A., & Hammad, A. (2016). Visualizing and Analyzing Urban Energy Consumption: A Critical Review and Case Study. In Construction Research Congress, (pp. 1323-1331).
Schmitt, L. M. (2001). Theory of genetic algorithms. Theoretical Computer Science, 259(1-2), 1-61.
SEIA. (2018). Solar Means Bussiness.
S-Energy. (2018). BIPV Module. Retrieved from http://www.s-energy.com/epage.php?it_id=1426727258
Shin, D., & Choi, S. H. (2018). Recent Studies of Semitransparent Solar Cells. Coatings, 8(10), 329.
Simulation and design of solar systems. (2021). Retrieved from photovoltaic-software.com: https://photovoltaic-software.com/principle-ressources/how-calculate-solar-energy-power-pv-systems
Smith, A., & Gill, G. (2014). FKI Tower. Retrieved 2018, from http://smithgill.com/work/fki/
Solar Analysis. (2021). Retrieved from Autodesk: https://knowledge.autodesk.com/support/revit-products/learn-explore/caas/CloudHelp/cloudhelp/2021/ENU/Revit-Analyze/files/GUID-925CBF1E-2B91-41A7-8CA8-C87F69F7BBC1-htm.html
Solar Power Farm. (2021). Retrieved from https://www.solarpowerfam.com/cost-of-solar-panels-per-square-meter/
Solconpro. (2018). Retrieved from solconpro: http://www.solconpro.de
Srinivas, N., & Deb, K. (1994). Muiltiobjective optimization using nondominated sorting in genetic algorithms. . Evolutionary computation, 2(3), 221-248.
SUNMetrix. (2021). Cost of Solar Panels. Retrieved from SUNMetrix: https://sunmetrix.com/cost-of-solar-panels/#solar1
Šúri, M. H., & Dunlop, E. D. (2005). PV-GIS: a web-based solar radiation database for the calculation of PV potential in Europe. International Journal of Sustainable Energy, 24(2), 55-67.
Šúri, M., Huld, T. A., Dunlop, E. D., & Ossenbrink, H. A. (2007). Potential of solar electricity generation in the European Union member states and candidate countries. Solar energy, 81(10), 1295-1305.
Svarc, J. (2021). Clean Energy Reviews. Retrieved from https://www.cleanenergyreviews.info/blog/most-efficient-solar-panels
Sydora, C., & Stroulia, E. (2020). Rule-based compliance checking and generative design for building interiors using BIM. Automation in Construction(120).
The eco experts. (2021). Solar panels. Retrieved from The eco experts: https://www.theecoexperts.co.uk/solar-panels/how-much-electricity
Tooke, T. R., Coops, N. C., Christen, A., Gurtuna, O., & Prévot, A. (2012). Integrated irradiance modelling in the urban environment based on remotely sensed data. Solar Energy, 86(10), 2923-2934.
Touloupaki, E., & Theodosiou, T. (2017). Energy performance optimization as a generative design tool for nearly zero energy buildings. Procedia engineering, 180, 1178-1185.
Traverse, C. J., Pandey, R., Barr, M. C., & Lunt, R. R. (2017). Emergence of highly transparent photovoltaics for distributed applications. Nature Energy, 2(11), 849–860.
United Nations. (2015). World Urbanization Prospects: The 2014 Revision. Department of Economic and Social Affairs, Population Division.
Vermeulen, D., & El Ayoubi, M. (2021). Using generative design in construction applications. Retrieved from Autodesk University: https://medium.com/autodesk-university/using-generative-design-in-construction-applications-e268c785b004
Wang, J. L., & Chen, X. (2010). Parametric design based on building information modeling for sustainable buildings. International Conference on Challenges in Environmental Science and Computer Engineering. 2, pp. 236-239. IEEE.
Wang, R. (2016). An Improved Nondominated Sorting Genetic Algorithm for Multiobjective Problem. Mathematical Problems in Engineering (pp. 1-7). Hindawi Publishing Corporation.
Wang, X., Song, Y., & Tang, P. (2020). Generative urban design using shape grammar and block morphological analysis. Frontiers of Architectural Research, 9(4), 914-924.
Ward, G. J. (1994). The RADIANCE lighting simulation and rendering system. In Proceedings of the 21st annual conference on Computer graphics and interactive techniques (pp. 459-472). ACM.
Wiginton, L. K., Nguyen, H. T., & Pearce, J. M. (2010). Quantifying rooftop solar photovoltaic potential for regional renewable energy policy. Computers, Environment and Urban Systems, 34(4), 345-357.
Yoon, J. H., Song, J., & Lee, S. J. (2011). Practical application of building integrated photovoltaic (BIPV) system using transparent amorphous silicon thin-film PV module. Solar Energy, 85(5), 723-733.
Zhang, J., Liu, N., & Wang, S. (2021). Generative design and performance optimization of residential buildings based on parametric algorithm. Energy and Buildings, 244, 111033.
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