Assessing the Potential for Rooftop Electricity Generation Using 3D Building Data Supporting Cost-Effective Energy Management through Digital Twin Technology

Rising energy costs have become a major challenge for households, businesses, and urban management. This trend is driven by growing electricity demand in daily life, rising temperatures caused by climate change, and fluctuations in global fuel and energy prices. Meanwhile, Thailand still relies on imported fossil fuels.
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As a result, various sectors are turning their attention to “solar energy” as a clean and sustainable power source with strong potential in Thailand. By generating electricity from their own rooftops, users can shift from being energy consumers to energy producers, helping to reduce electricity costs in a more sustainable way.
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However, despite government measures to promote household solar panel installation, the investment cost remains relatively high. Therefore, accurate information on the “actual return on investment” is a crucial factor before making an investment decision.
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Previous studies on solar energy have shown that Thailand has high potential for producing electricity from solar power, especially in the northeastern region, which receives some of the highest average annual solar radiation in the country. However, not every area can generate energy at full capacity, and not all locations perform equally well throughout a year. Even within the same area, buildings may differ in terms of available rooftop space for solar panel installation and their ability to generate electricity consistently throughout the day.
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To address this issue, the Geo-Informatics and Space Technology Development Agency (Public Organization), or GISTDA, has developed a system for assessing solar power generation potential and calculating the cost-effectiveness of solar cell installation through a Digital Twin platform. It is based on spatial and environmental factors, including solar radiation levels, roof orientation, roof type and shape, and shadows cast by buildings and trees at different times of the day, as well as atmospheric dust and water vapor. These factors help estimate the amount of solar radiation reaching rooftop surfaces more accurately, leading to better calculations of electricity generation potential and the cost-effectiveness of solar cell installation.
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Dr. Jiratiwan Kruasilp, a Geoinformatics Specialist at GISTDA, explained that this project began in 2024. It builds on the 3D infrastructure data previously developed by GISTDA and has been further developed into Digital Twins platform to support smart city development. The platform applies space technology to enhance urban management in various dimensions, including safety monitoring via CCTV, flood prediction management, urban air pollution monitoring, accessibility of public facilities for the elderly and people with disabilities, and rooftop solar power potential evaluation.
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The rooftop solar potential evaluation system developed by GISTDA is based on 3D building data combined with a solar radiation intensity model. The system does not consider only roof area or building height, it also calculates the position and movement path of the sun at different times, using factors such as the solar hour angle, azimuth angle, and radiation transmittance coefficient to estimate the amount of energy reaching rooftop surfaces over time.
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In the atmospheric component, the system uses air pollution data and satellite data to analyze the effects of scattering, absorption, and attenuation of solar radiation, all of which directly affect the efficiency of electricity generation from solar cells. Furthermore, the system can analyze the shadow-casting simulation based on the sun's position throughout the year to estimate when nearby buildings, trees, or other obstructions would block the rooftop surface. This allows the system to evaluate the solar potential of each building in greater detail and with greater accuracy.
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Rooftop type and shape also directly affect the installation area and the amount of energy received. Therefore, the system supports various rooftop models, including hip, flat, gable, and complex roof types, to identify suitable installation areas and reduce errors in rooftop assessment.
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The model mentioned above was verified by the experts from the Department of Physics, Silpakorn University, who have experience in developing a solar radiation intensity map of Thailand. Preliminary verification results showed an accuracy level of over 80% under the specified data and evaluation methodologies.
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The system is designed as an online platform that is easily accessible to the public. Its key feature is the assessment of investment cost-effectiveness. The system can calculate monthly electricity generation potential and analyze investment feasibility based on the standard criteria of the Provincial Electricity Authority (PEA), making the results easier for users to understand. Its environmental assessment can also estimate the amount of carbon dioxide emissions reduced through solar cell installation and the equivalent number of trees planted. In addition, users can pin their location on the Digital Twin platform to directly view the solar energy potential reaching their own rooftops.
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Currently, GISTDA has launched a pilot system in four main areas where 3D infrastructure data is available on the Digital Twin platform: Khon Kaen City Municipality, Nakhon Ratchasima City Municipality, Laemchabang City Municipality, and Chonburi Town Municipality.
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In the future, GISTDA plans to expand the service to cover 15 municipal areas currently being developed as smart cities, before extending the service to other areas across the country. The agency also plans to enhance the technology by developing a system to extract information on existing solar panels from satellite imagery. This data will support analysis, comparison, and the promotion of additional installations in high-potential areas where solar panels have not yet been installed.
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For more information, please visit: https://gistdaportal.gistda.or.th/digital-twins/