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Maximizing Solar Potential: Estimating The Solar Energy Production on Falun's Roofs
Dalarna University, School of Information and Engineering, Energy Systems in Built Environments.
Dalarna University, School of Information and Engineering, Energy Systems in Built Environments.
2024 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The study aimed to prepare for future software to estimate the solar energy production on rooftops by establishing specific criteria and developing a method to estimate the solar energy potential for PV systems on rooftops. The research initiated with a comprehensive literature review and the gathering of geographical data which proceeded in parallel. To verify the study's findings, an existing roof were studied. The developed method involves converting the total roof area into the annual solar energy production output, which is visually represented in a flowchart. The method starts by adjusting the total roof area using LiDAR data and adhering to building regulations and guidelines concerning solar- and architectural suitability. The suitable area is then further refined into usable area based on the dimensions and installation requirements of the PV panels. The final step in the method calculates the solar energy production of the PV system considering the location and specific system conditions. This method was tested on an existing building to verify the results. The calculations indicated that 39% of the total roof area was suitable for horizontal (landscape)-oriented panels, producing an annual solar energy output of 6,900 kWh/year. For vertical (portrait)-oriented panels, 32% of the total roof area was applicable, yielding an annual solar energy production of 5,800 kWh/year. The study's conclusion highlights that criteria include distances from obstacles and solar viability. Integrating various geographical data would enhance the accuracy of solar energy production estimation, when planning PV panel installations. Future software should incorporate visualisation features representing physical barriers and shading elements that may prevent PV installations, as well as safety distance regulatory.

Place, publisher, year, edition, pages
2024.
Keywords [en]
PV panel, Photovoltaic, Roof area, Geographical data, LiDAR data, solar energy potential
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:du-49010OAI: oai:DiVA.org:du-49010DiVA, id: diva2:1883028
Subject / course
Energy Technology
Available from: 2024-07-08 Created: 2024-07-08

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf